@misc{kolm_european_2016, address = {St. Pölten}, type = {Invited talk}, title = {European {Project} {IMPECD} – {Improvement} of {Education} and {Competences} in {Dietetics}}, author = {Kolm, Alexandra}, month = jun, year = {2016}, note = {Projekt: IMPECD}, keywords = {2016, Department Gesundheit, Einladung, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, Publikationstyp Vortrag, SP IGW Education \& Lifelong Learning for Health Professionals, Studiengang Diätologie, best}, } @misc{leitner_einfluss_2015, address = {Hagenberg}, title = {Einfluss von {Ernährungsverhalten} und {Lebensstil} auf {Gesundheitsindikatoren} 17-19-jähriger junger {Männer} in {Niederösterreich}}, author = {Leitner, Gabriele}, month = apr, year = {2015}, keywords = {2015, Bewerbungsverfahren, Department Gesundheit, Department Gesundheit und Soziales, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, Publikationstyp Vortrag, SP IGW Health Promotion \& Healthy Ageing, Studiengang Diätologie, best}, } @misc{kolm_improvement_2016, address = {Wolfsburg, D}, type = {Invited talk}, title = {Improvement of {Education} and {Competences} in {Dietetics}. {Hintergrund} und {Inhalt} des europäischen {Projekts} {IMPECD}}, author = {Kolm, Alexandra}, month = apr, year = {2016}, keywords = {2016, Department Gesundheit, Einladung, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, Publikationstyp Vortrag, SP IGW Education \& Lifelong Learning for Health Professionals, Studiengang Diätologie, best}, } @misc{kolm_diatetische_2015, address = {Bregenz}, type = {Invited talk}, title = {Diätetische {Beeinflussung} der {Hypertonie}}, author = {Kolm, Alexandra}, month = may, year = {2015}, keywords = {2015, Department Gesundheit, Department Gesundheit und Soziales, Einladung, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, Publikationstyp Vortrag, SP IGW Clinical \& Healthcare Research, Studiengang Diätologie, best}, } @misc{moseneder_ernahrungswissen_2013, address = {Bonn, Deutschland}, type = {Posterpräsentation}, title = {Ernährungswissen von {Eltern} mit/ohne {Migrationshintergrund} zu einer bedarfsgerechten {Kleinkinderernährung} und dem {Obst}- und {Gemüsekonsum} von {Kleinkindern} in {Bonn}}, author = {Möseneder, Jutta M. and Ganahl, Elisa and Kohlmaier, Barbara and Karner, Gabriele}, month = mar, year = {2013}, keywords = {2013, Bewerbungsverfahren, Department Gesundheit und Soziales, Institut für Gesundheitswissenschaften, Poster, Publikationstyp Poster, Publikationstyp Präsentation, SP IGW Health Promotion \& Healthy Ageing, Studiengang Diätologie, best}, } @misc{schwingenschlogl_erhebung_2014, address = {Bad Hofgastein}, type = {Posterpräsentation}, title = {Erhebung der {Mangelernährung} in österreichischen {Pflege}- und {Seniorenheimen}}, author = {Schwingenschlögl, Tina and Kohlmaier, Barbara and Möseneder, Jutta M. and Karner, Gabriele}, month = mar, year = {2014}, keywords = {2014, Bewerbungsverfahren, Department Gesundheit und Soziales, Institut für Gesundheitswissenschaften, Poster, Publikationstyp Poster, Publikationstyp Präsentation, SP IGW Clinical \& Healthcare Research, Studiengang Diätologie, best}, } @misc{ramler_get_2018, address = {Genua}, type = {Posterpräsentation}, title = {Get the {Kidney}! {Nutrition} for {Haemodialysis} {Patients} – {A} {Training} {Video} for {Students} in {Dietetics}}, author = {Ramler, Heidemarie and Freisleben-Teutscher, Christian F.}, month = jun, year = {2018}, keywords = {2018, Bewerbungsverfahren, Department Gesundheit, Institut für Gesundheitswissenschaften, Publikationstyp Poster, Publikationstyp Präsentation, SP IGW Clinical \& Healthcare Research, Studiengang Diätologie, best}, } @misc{bauer_assessment_2015, address = {Berlin}, title = {Assessment zur {Erstellung} eines diätologischen {Gutachtens} für bariatrische {PatientInnen}}, author = {Bauer, Manuela and Lindorfer, Carina and Satzinger, Cornelia and Wagner, Stefanie and Winter, Anna-Katharina and Lötsch, Birgit and Kolm, Alexandra and Möseneder, Jutta M. and Karner, Gabriele}, month = oct, year = {2015}, keywords = {2015, Bewerbungsverfahren, Department Gesundheit, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, Publikationstyp Vortrag, SP IGW Education \& Lifelong Learning for Health Professionals, Studiengang Diätologie, best}, } @misc{bauer_assessment_2015, address = {Wien}, title = {Assessment zur {Erstellung} eines diätologischen {Gutachtens} für bariatrische {PatientInnen}}, author = {Bauer, Manuela and Lindorfer, Carina and Satzinger, Cornelia and Wagner, Stefanie and Winter, Anna-Katharina and Lötsch, Birgit and Kolm, Alexandra and Möseneder, Jutta M. and Karner, Gabriele}, month = oct, year = {2015}, keywords = {2015, Bewerbungsverfahren, Department Gesundheit, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, Publikationstyp Vortrag, SP IGW Education \& Lifelong Learning for Health Professionals, Studiengang Diätologie, best}, } @misc{werkman_education_2017, address = {Setubal (Portugal)}, type = {Posterpräsentation}, title = {Education of {European} dietitians using a {MOOC}: the {IMPECD} project}, author = {Werkman, Andrea and Vanherle, Koen and Valentini, Luzia and Kohlenberg-Müller, Kathrin and Heine-Bröring, Renate and Roemeling-Walters, Maaike and Adam, Marleen and Aerts, Hanna and Baete, Eline and Le Bruyn, Bente and Van Vlaslaer, Veerle and Buchholz, Daniel and Rachman-Elbaum, Shelly and Gast, Christina and Hahn, Sigrid and Huber, Marie-Luise and Höld, Elisabeth and Wewerka-Kreimel, Daniela and Höld, Elisabeth and Kolm, Alexandra}, month = apr, year = {2017}, note = {Projekt: IMPECD}, keywords = {2017, Bewerbungsverfahren, Center for Digital Health Innovation, Department Gesundheit, Institut für Gesundheitswissenschaften, Publikationstyp Poster, Publikationstyp Präsentation, SP IGW Education \& Lifelong Learning for Health Professionals, Studiengang Diätologie, best}, } @misc{neuhold_entwicklung_2015, address = {Alpbach}, type = {Posterpräsentation}, title = {Entwicklung eines {Schnell}-{Screenings} zur {Abklärung} der {Verdachtsdiagnose} einer {Essstörung} im {Rahmenn} einer {Ernährungsberatung}}, author = {Neuhold, Kerstin and Kolm, Alexandra and Gnauer, Sandra and Möseneder, Jutta M. and Karner, Gabriele}, month = oct, year = {2015}, keywords = {2015, Bewerbungsverfahren, Department Gesundheit, Institut für Gesundheitswissenschaften, Publikationstyp Poster, Publikationstyp Präsentation, SP IGW Clinical \& Healthcare Research, Studiengang Diätologie, best}, } @misc{kolm_innovatives_2017, address = {Bielefeld}, type = {Posterpräsentation}, title = {Innovatives {Lernkonzept} für die {Diätetik} im {Rahmen} des {EU}-{Projektes} {IMPECD}}, author = {Kolm, Alexandra and Valentini, Luzia and Kohlenberg-Müller, Kathrin and Werkman, Andrea and Vanherle, Koen}, month = mar, year = {2017}, note = {Projekt: IMPECD}, keywords = {2017, Bewerbungsverfahren, Department Gesundheit, Institut für Gesundheitswissenschaften, Publikationstyp Poster, Publikationstyp Präsentation, SP IGW Education \& Lifelong Learning for Health Professionals, Studiengang Diätologie, best}, } @article{horsak_concurrent_2023, title = {Concurrent validity of smartphone-based markerless motion capturing to quantify lower-limb joint kinematics in healthy and pathological gait}, volume = {159}, copyright = {CC-BY}, issn = {0021-9290}, url = {https://www.sciencedirect.com/science/article/pii/S002192902300372X}, doi = {10.1016/j.jbiomech.2023.111801}, abstract = {Markerless motion capturing has the potential to provide a low-cost and accessible alternative to traditional marker-based systems for real-world biomechanical assessment. However, before these systems can be put into practice, we need to rigorously evaluate their accuracy in estimating joint kinematics for various gait patterns. This study evaluated the accuracy of a low-cost, open-source, and smartphone-based markerless motion capture system, namely OpenCap, for measuring 3D joint kinematics in healthy and pathological gait compared to a marker-based system. 21 healthy volunteers were instructed to walk with four different gait patterns: physiological, crouch, circumduction, and equinus gait. Three-dimensional kinematic data were simultaneously recorded using the markerless and a marker-based motion capture system. The root mean square error (RMSE) and the peak error were calculated between every joint kinematic variable obtained by both systems. We found an overall RMSE of 5.8 (SD: 1.8 degrees) and a peak error of 11.3 degrees (SD: 3.9). A repeated measures ANOVA with post hoc tests indicated significant differences in RMSE and peak errors between the four gait patterns (p ¡ 0.05). Physiological gait presented the lowest, crouch and circumduction gait the highest errors. Our findings indicate a roughly comparable accuracy to IMU-based approaches and commercial markerless multi-camera solutions. However, errors are still above clinically desirable thresholds of two to five degrees. While our findings highlight the potential of markerless systems for assessing gait kinematics, they also underpin the need to further improve the underlying deep learning algorithms to make markerless pose estimation a valuable tool in clinical settings.}, urldate = {2023-09-21}, journal = {Journal of Biomechanics}, author = {Horsak, Brian and Eichmann, Anna and Lauer, Kerstin and Prock, Kerstin and Krondorfer, Philipp and Siragy, Tarique and Dumphart, Bernhard}, month = oct, year = {2023}, keywords = {Center for Digital Health and Social Innovation, Deep learning, Gait analysis, Institut für Gesundheitswissenschaften, Markerless motion capture, OpenCap, Phaidra, Pose estimation, Publikationstyp Schriftpublikation, SP CDHSI Motor Rehabilitation, Wiss. Beitrag, best, best-bhorsak, peer-reviewed}, pages = {111801}, } @inproceedings{guggenberger_different_2023, address = {Heidelberg}, series = {{GAMMA} 2023 {Abstracts}}, title = {Different walking strategies impact patella cartilage pressure in individuals with patellofemoral instability}, volume = {100}, copyright = {Copyright}, url = {https://www.sciencedirect.com/science/article/pii/S0966636222006622}, doi = {10.1016/j.gaitpost.2022.11.025}, language = {en}, urldate = {2023-03-10}, booktitle = {Gait \& {Posture}}, author = {Guggenberger, Bernhard and Horsak, Brian and Habersack, Andreas and Smith, Colin R. and Kainz, Hans and Svehlik, Martin}, month = mar, year = {2023}, keywords = {Biomechanics, Center for Digital Health and Social Innovation, Gait Analysis, Institut für Gesundheitswissenschaften, Musculoskeletal Simulations, SP CDHSI Motor Rehabilitation, Vortrag, Wiss. Beitrag, best, peer-reviewed}, pages = {9--10}, } @inproceedings{durstberger_effects_2023, address = {Heidelberg}, series = {{GAMMA} 2023 {Abstracts}}, title = {Effects of three different regression-based hip joint center localization methods in adolescents with obesity on kinematics and kinetics - preliminary results of the {HIPstar} study}, volume = {100}, copyright = {Copyright}, url = {https://www.sciencedirect.com/science/article/pii/S0966636222006932}, doi = {10.1016/j.gaitpost.2022.11.056}, language = {en}, urldate = {2023-03-10}, booktitle = {Gait \& {Posture}}, author = {Durstberger, Sebastian and Kranzl, Andreas and Horsak, Brian}, month = mar, year = {2023}, note = {Projekt: HIPstar}, keywords = {Biomechanics, Center for Digital Health and Social Innovation, Gait Analysis, Institut für Gesundheitswissenschaften, Musculoskeletal Simulations, SP CDHSI Motor Rehabilitation, Vortrag, Wiss. Beitrag, best, peer-reviewed}, pages = {42--43}, } @misc{kolm_essen_2015, address = {St. Pölten}, type = {Invited talk}, title = {Essen und {Trinken} bei {Hypertonie} – {Ernährung} nimmt den {Druck}}, author = {Kolm, Alexandra}, month = apr, year = {2015}, keywords = {2015, Department Gesundheit, Department Gesundheit und Soziales, Einladung, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, Publikationstyp Vortrag, SP IGW Clinical \& Healthcare Research, Studiengang Diätologie, best}, } @misc{kohlmaier_ernahrungsaspekte_2016, address = {St. Pölten}, type = {Invited talk and workshop}, title = {Ernährungsaspekte der {LMIV} \& {Konsumentenverhalten}}, author = {Kohlmaier, Barbara}, month = nov, year = {2016}, keywords = {2016, Department Gesundheit, Einladung, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, Publikationstyp Vortrag, SP IGW Health Promotion \& Healthy Ageing, Studiengang Diätologie, best}, } @misc{wagner_bariatrisches_2016, address = {Wien}, type = {Invited talk}, title = {Bariatrisches {Assessment} - {Eine} {Hilfe} zur {Erstellung} eines diätologischen {Gutachtens} für bariatri-sche {PatientInnen}}, author = {Wagner, Stefanie and Bauer, Manuela and Lindorfer, Carina and Satzinger, Cornelia and Winter, Anna-Katharina and Lötsch, Birgit and Kolm, Alexandra and Möseneder, Jutta M. and Karner, Gabriele}, month = mar, year = {2016}, keywords = {2016, Department Gesundheit, Einladung, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, Publikationstyp Vortrag, SP IGW Education \& Lifelong Learning for Health Professionals, Studiengang Diätologie, best}, } @book{schmutz_tales_2014, address = {St. Pölten, Austria}, title = {Tales of {Taste} - international cookbook}, language = {English}, publisher = {Eigenverlag FH St. Pölten}, author = {Schmutz, Teresa and Zöchling, Elisabeth and Gruber, Kathrin and Harlander, Malina and Kohlmaier, Barbara and Bergmann, Cornelia and Karner, Gabriele}, year = {2014}, keywords = {2014, Department Gesundheit und Soziales, Institut für Gesundheitswissenschaften, Publikationstyp Buch, Publikationstyp Schriftpublikation, SP IGW Education \& Lifelong Learning for Health Professionals, Studiengang Diätologie, best}, } @misc{karl_bna_2016, address = {Wien}, type = {Invited talk}, title = {{BNA} – {Bariatric} {Assessment} zur {Erstellung} eines {Diaetologischen} {Gutachtens}}, author = {Karl, Veronika and Leonhartsberger, Andrea and Lötsch, Birgit and Kolm, Alexandra and Möseneder, Jutta M. and Karner, Gabriele}, month = jul, year = {2016}, keywords = {2016, Department Gesundheit, Einladung, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, Publikationstyp Vortrag, SP IGW Education \& Lifelong Learning for Health Professionals, Studiengang Diätologie, best}, } @misc{kohlmaier_tales_2016, title = {Tales of {Taste}: {What} is special about {Austrian} {Eating} {Culture}?}, url = {https://www.youtube.com/channel/UC5bMmS05E9tARb1O-AU4pQw}, collaborator = {Kohlmaier, Barbara and Auffret, Irene and Scharfmüller, Beate and Grasl, Julia and Meyr, Julia and Toifl, Marlene and Bujokova, Pavlina and Kovaleva, Polina and Baran, Vlad}, year = {2016}, keywords = {2016, Department Gesundheit, Institut für Gesundheitswissenschaften, Publikationstyp Medienbeitrag, SP IGW Education \& Lifelong Learning for Health Professionals, Studiengang Diätologie, best}, } @book{kohlmaier_wohlfuhlen_2015, address = {Wien}, series = {Broschüre}, title = {Wohlfühlen ein {Leben} lang}, publisher = {Eigenverlag}, author = {Kohlmaier, Barbara and Ramler, Heidemarie and Lasar, Doris}, editor = {forum ernährung heute}, year = {2015}, keywords = {2015, Department Gesundheit, Institut für Gesundheitswissenschaften, Publikationstyp Schriftpublikation, SP IGW Health Promotion \& Healthy Ageing, Studiengang Diätologie, best}, } @article{horsak_inter-trial_2024, title = {Inter-trial variability is higher in {3D} markerless compared to marker-based motion capture: {Implications} for data post-processing and analysis}, issn = {0021-9290}, shorttitle = {Inter-trial variability is higher in {3D} markerless compared to marker-based motion capture}, url = {https://www.sciencedirect.com/science/article/pii/S002192902400126X}, doi = {10.1016/j.jbiomech.2024.112049}, abstract = {Markerless motion capture has recently attracted significant interest in clinical gait analysis and human movement science. Its ease of use and potential to streamline motion capture recordings bear great potential for out-of-the-laboratory measurements in large cohorts. While previous studies have shown that markerless systems can achieve acceptable accuracy and reliability for kinematic parameters of gait, they also noted higher inter-trial variability of markerless data. Since increased inter-trial variability can have important implications for data post-processing and analysis, this study compared the inter-trial variability of simultaneously recorded markerless and marker-based data. For this purpose, the data of 18 healthy volunteers were used who were instructed to simulate four different gait patterns: physiological, crouch, circumduction, and equinus gait. Gait analysis was performed using the smartphone-based markerless system OpenCap and a marker-based motion capture system. We compared the inter-trial variability of both systems and also evaluated if changes in inter-trial variability may depend on the analyzed gait pattern. Compared to the marker-based data, we observed an increase of inter-trial variability for the markerless system ranging from 6.6\% to 22.0\% for the different gait patterns. Our findings demonstrate that the markerless pose estimation pipelines can introduce additionally variability in the kinematic data across different gait patterns and levels of natural variability. We recommend using averaged waveforms rather than single ones to mitigate this problem. Further, caution is advised when using variability-based metrics in gait and human movement analysis based on markerless data as increased inter-trial variability can lead to misleading results.}, urldate = {2024-03-13}, journal = {Journal of Biomechanics}, author = {Horsak, Brian and Prock, Kerstin and Krondorfer, Philipp and Siragy, Tarique and Simonlehner, Mark and Dumphart, Bernhard}, year = {2024}, keywords = {Center for Digital Health and Social Innovation, Deep learning, Departement Gesundheit, Gait analysis, Institut für Gesundheitswissenschaften, Intra-session variability, OpenCap, Pose estimation, SP CDHSI Motor Rehabilitation, Wiss. Beitrag, best, best-bhorsak, markerless motion capture, peer-reviewed}, pages = {112049}, } @inproceedings{vulpe-grigorasi_cognitive_2023, address = {New York, NY, USA}, series = {{MUM} '23}, title = {Cognitive load assessment based on {VR} eye-tracking and biosensors}, isbn = {9798400709210}, url = {https://dl.acm.org/doi/10.1145/3626705.3632618}, doi = {10.1145/3626705.3632618}, abstract = {In this paper I present the status of my doctoral research project, a general overview of the research topic and future developments. The main research focus will be to study and develop an extended reality solution for cognitive load assessment in adaptive virtual environments, based on eye tracking and bio-signals. The main objective is to respond to the need for healthcare and training becoming more personalized and location- and time-independent. The end goal is to establish a framework that serves as a quantitative basis for adaptive rehabilitation and training by pushing cognitive load assessment towards ubiquitous computing through immersive technologies.}, urldate = {2024-01-23}, booktitle = {Proceedings of the 22nd {International} {Conference} on {Mobile} and {Ubiquitous} {Multimedia}}, publisher = {Association for Computing Machinery}, author = {Vulpe-Grigorasi, Adrian}, year = {2023}, note = {Projekt: EyeQTrack}, keywords = {Center for Digital Health and Social Innovation, Institut für Gesundheitswissenschaften, SP CDHSI Digital Wellbeing, Vortrag, Wiss. Beitrag, best, peer-reviewed}, pages = {589--591}, } @inproceedings{dumphart_is_2023, series = {{ESMAC} 2023 {Abstracts}}, title = {Is it time to re-think the appropriateness of autocorrelation for gait event detection? {Preliminary} results of an ongoing study}, volume = {106}, shorttitle = {Is it time to re-think the appropriateness of autocorrelation for gait event detection?}, url = {https://www.sciencedirect.com/science/article/pii/S0966636223009840}, doi = {10.1016/j.gaitpost.2023.07.064}, abstract = {Introduction Recent developments in machine learning (ML)-based gait event detection have demonstrated superior results in terms of robustness and temporal accuracy compared to heuristic approaches [1–3]. “Autocorrelation” (AC) is an implemented heuristic algorithm in the Vicon Nexus application, which identifies events based on a recurring pattern of a certain marker. Clinicians often rely on the use of AC or other heuristic approaches to identify initial contact (IC) and foot off (FO) events. However, no literature exists on the accuracy of AC for event detection. We have recently developed IntellEvent [4], a ML-based event detection algorithm which has superior accuracy compared to current state-of-the-art methods [1,5]. We aim to evaluate its applicability in daily clinical use compared to the AC method. Research question How large are the temporal differences of gait events detected by IntellEvent and the AC method? Methods The retrospective dataset for this study comprises 3DGA data. Patients were classified having either malrotation deformities (MD, n=20) or infantile cerebral palsy (ICP, n=18). IntellEvent was used to detect all IC and FO events using the left and right velocity of the heel, ankle, and toe trajectories. For the AC method a threshold of 20N was used to detect all IC and FO events on force plates. Subsequently, AC was used to detect all other events using the least square method of the x-axis trajectory (direction of motion). We validated IntellEvent by comparing its predictions to events solely identified with force plates. Afterwards, we calculated the differences between the remaining events of IntellEvent and the AC method. Results Mean absolute errors (95\% confidence interval) of IntellEvent compared to the ground truth for IC (MD: 2.4ms (2.1-2.8), ICP: 3.7ms (3.2–4.1)) and FO (MD: 7.5ms (6.8–8.1), ICP: 10.5 (9.5–11.4)) events showed a high temporal accuracy for both pathologies (Fig. 1). The comparison between IntellEvent and the AC events shows greater deviations for IC (MD: 10.1ms (9.6–0.6), ICP: 11.5ms (10.9–12.1)) and FO (MD: 9.3ms (8.8–9.7), ICP: 15.4ms (14.6–16.2)). Fig. 1. Temporal errors between IntellEvent vs. force plate data (blue) and IntellEvent vs. Autocorrelation (orange). Dotted grey lines indicate an error of 6.67ms (= 1 frames) and dotted red lines an error of 26.66ms (= 4 frames). Discussion IntellEvent achieves a very high temporal accuracy and robustness when compared to ground truth data. For the IC events, a high deviation between IntellEvent and AC was observed. Therefore, the results suggest that the AC can potentially introduce errors that may affect clinical decision making. Our preliminary results indicate that AC events need to be used with care when applied to pathological gait patterns and ML-based methods such as IntellEvent could improve the overall accuracy of gait event detection.}, urldate = {2023-09-18}, booktitle = {Gait \& {Posture}}, author = {Dumphart, Bernhard and Slijepcevic, Djordje and Kranz, Andreas and Zeppelzauer, Matthias and Horsak, Brian}, month = sep, year = {2023}, keywords = {Biomechanics, Center for Artificial Intelligence, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, Department Gesundheit, Department Medien und Digitale Technologien, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Gait Analysis, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Machine Learning, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Vortrag, Wiss. Beitrag, best, best-bhorsak, peer-reviewed}, pages = {S50--S51}, } @inproceedings{slijepcevic_towards_2023, series = {{ESMAC} 2023 {Abstracts}}, title = {Towards personalized gait rehabilitation: {How} robustly can we identify personal gait signatures with machine learning?}, volume = {106}, copyright = {Copyright}, shorttitle = {Towards personalized gait rehabilitation}, url = {https://www.sciencedirect.com/science/article/pii/S0966636223012523}, doi = {10.1016/j.gaitpost.2023.07.232}, abstract = {Introduction Personalizing gait rehabilitation requires a comprehensive understanding of the unique gait characteristics of an individual patient, i.e., personal gait signature. Utilizing machine learning to classify individuals based on their gait can help to identify gait signatures [1]. This work exemplifies how an explainable artificial intelligence method can identify the most important input features that characterize the personal gait signature. Research question How robust can gait signatures be identified with machine learning and how sensitive are these signatures with respect to the amount of training data per person? Methods We utilized subsets of the AIST Gait Database 2019 [2], the GaitRec dataset [3], and the Gutenberg Gait Database [4] containing bilateral ground reaction forces (GRFs) during level walking at a self-selected speed. Eight GRF samples from each of 2,092 individuals (1,410/680 male/female, 809/1,283 health control/gait disorder, 1,355/737 shod/barefoot) were used for a gait-based person classification with a (linear) support vector machine (SVM). Two randomly selected samples from each individual served as test data. Gait signatures were identified using relevance scores obtained with layer-wise relevance propagation [5]. To assess the robustness of the identified gait signatures, we compared the relevance scores using Pearson’s correlation coefficient between step-wise reduced training data, from k=6 to k=1 training samples per individual. Results For the baseline setup (k=6), the SVM achieved a test classification accuracy of 99.1\% with 36 out of 4184 test samples being misclassified. The results for the setups with reduced training samples are visualized in Fig. 1. Fig. 1: Overview of the experimental results. Discussion A reduction of training samples per individual causes a decrease in classification accuracy (e.g., by 17.7\% in the case of one training sample per individual). The results show that at least five training samples per individual are necessary to achieve a classification accuracy of approximately 99\% for over 2,000 individuals. A similar effect is observed for gait signatures, which also show a slight degradation in robustness as the number of training samples decreases. In some cases, a model trained with less data per individual learns a different gait signature than a model trained with more data. In the test sample with the lowest correlation (see Fig. 1E), we observe a significant deviation in relevance for some input features. However, only 114 test samples (2.7\%) are below a moderate correlation of r=0.4 [6], indicating that gait signatures are quite robust, even when using one training sample per individual. This is supported by a strong median correlation of r=0.71 [6] (and the highest correlation of r=0.96) between the gait signatures. As automatically identified gait signatures seem to be robust, this approach has the potential to serve as a basis for tailoring interventions to each patient’s specific needs.}, urldate = {2023-09-21}, booktitle = {Gait \& {Posture}}, author = {Slijepcevic, Djordje and Horst, Fabian and Simak, Marvin and Schöllhorn, Wolfgang Immanuel and Zeppelzauer, Matthias and Horsak, Brian}, month = sep, year = {2023}, keywords = {Center for Artificial Intelligence, Center for Digital Health and Social Innovation, Department Medien und Digitale Technologien, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, SP CDHSI Motor Rehabilitation, Vortrag, Wiss. Beitrag, best, best-bhorsak, peer-reviewed}, pages = {S192--S193}, } @inproceedings{holder_comparative_2023, series = {{ESMAC} 2023 {Abstracts}}, title = {A comparative analysis of kinematic simulation results obtained by manually and automated scaled {OpenSim} models during walking – preliminary findings}, volume = {106}, copyright = {Copyright}, url = {https://www.sciencedirect.com/science/article/pii/S0966636223010196}, doi = {10.1016/j.gaitpost.2023.07.099}, abstract = {Introduction Musculoskeletal simulations provide a deeper understanding of human movement by not only estimating joint movements and external joint loadings but also muscle forces, and internal joint loading parameters [1]. To date, the scaling and personalization of musculoskeletal models are performed manually in an iterative and time-consuming process [2]. This might hinder their use in clinical settings, impedes evaluating a large amount of individuals with knee malalignment and, thus, also prevents usage of trending technologies such as Machine Learning and Big Data analysis [3]. To address this, a Matlab pipeline was developed to automate the scaling process and subsequent personalization steps in OpenSim. This study’s primary objective is to evaluate the kinematic differences between the two methods. Research question To what extent does the kinematic output of automatically scaled models correspond with by-hand scaled model output? Methods Sixteen children and adolescents with valgus malalignment of at least one lower limb participated in this study. Manual scaling was performed by an experienced user in OpenSim 3.3 via the GUI [2] with a modified generic model [4,5]. Frontal knee alignment was manually adjusted based on X-ray imaging data. Automatic processing was done through a custom Matlab workflow using the same generic model with one accompanied standardized markerset. A static trial was used to automatically adjust each model’s frontal knee alignment based on the knee valgus angle angles of the static trial [4], run initial marker registration, and finally OpenSim’s scaling tool. Time-normalized kinematic parameters of the pelvis, hip, knee, and ankle joints were compared using parametric t-tests from the Statistical Parameter Mapping package (SPM) [6]. Mean differences and root mean squared errors (RMSE) were calculated for all kinematic parameters. Results The RMSE varied between 1.3°±0.6 (pelvic rotation) and 5.7°±2.8 (hip flexion-extension) (Fig. 1). Discussion The literature suggests that errors of 2 degrees or less are likely to be generally acceptable, while errors of up to 5 degrees require consideration in data interpretation [7,8]. Our observed RMSE varied between 1.8° and 5.7°. Greatest errors were found for the pelvis tilt and hip flexion, presumably caused by an inaccurate placement of the sacrum marker for the automated marker registration. Our data suggest that automated processing seems able to generate sufficiently enough accurate participant-specific simulations. Approaches such as recently described bilevel optimization for scaling and marker registration presumably could further improve the accuracy and should be considered in the near future for automated approaches. Effects on calculated joint and muscle loading parameters also need to be evaluated in a next step [9].}, urldate = {2023-09-21}, booktitle = {Gait \& {Posture}}, author = {Holder, Jana and Stief, Felix and van Drongelen, Stefan and Horsak, Brian}, month = sep, year = {2023}, keywords = {Center for Digital Health and Social Innovation, Institut für Gesundheitswissenschaften, SP CDHSI Motor Rehabilitation, Vortrag, Wiss. Beitrag, best, best-bhorsak, peer-reviewed}, pages = {S80--S82}, } @inproceedings{horsak_concurrent_2023, series = {{ESMAC} 2023 {Abstracts}}, title = {Concurrent assessment of a smartphone-based markerless and marker-based motion capture system in pathological gait}, volume = {106}, copyright = {Copyright}, url = {https://www.sciencedirect.com/science/article/pii/S0966636223010184}, doi = {10.1016/j.gaitpost.2023.07.098}, abstract = {Introduction Markerless motion capturing is a trending technology that is expected to revolutionize clinical settings and sports. It estimates 3D human motion using synchronized video data and deep-learning-driven pose estimation. Compared to traditional marker-based systems, markerless systems offer fast and effortless motion capturing, making them accessible to novice users without sacrificing reliability [1]. Research shows that multi-camera markerless systems have acceptable accuracy in determining joint kinematics and kinetics across several movements [2,3]. However, their need for costly and complex hardware still limits their accessibility in various healthcare settings. OpenCap is an open-source platform that aims to close this gap by using videos captured from a minimum of two smartphones to compute movement dynamics in a web-based service [4]. This study compares joint kinematics obtained simultaneously with OpenCap and a marker-based system for physiological and different pathologic gait patterns. Research question How accurate is a smartphone-based markerless motion capture system in assessing gait kinematics in various gait patterns? Methods Ten females and eight males with a mean age of 30 (SD 9yrs) and a BMI of 23 (SD 3kg/m²) were instructed by a physiotherapist to walk with four different patterns: physiological, crouch, circumduction, and equinus gait. A 16-camera motion capture system tracked the 3D trajectories of skin-mounted markers based on the Cleveland-Clinic marker set. The trajectories were then used to run OpenSim's inverse-kinematic tool with a modified 2392 model with 3 DoF in the knee joint [5,6]. The data for OpenCap were recorded simultaneously with two iOS smartphones and processed using the web application [4]. Data were synchronized using cross-correlation. The Root Mean Square Error (RMSE) was calculated between every kinematic variable obtained by both systems. Results We found an overall RMSE of 5.9 (SD 1.2 degrees), details for each gait pattern are presented in Fig. 1. A rep. measures ANOVA (p {\textless} 0.001) with post hoc tests indicated that physiological gait had the lowest (p {\textless} 0.01) and crouch and circumduction had the highest errors (p {\textless} 0.05). Fig. 1. Left: Kinematic trajectories with one standard deviation obtained with both systems. Right \& Below: Boxplots with quartiles for the averaged Root Mean Square Error (RMSE). Discussion Our data show that OpenCap’s accuracy is approximately similar to IMU-based approaches and commercial markerless multi-camera solutions [2,7]. However, errors are still above clinically desirable thresholds of approximately 2 to 5 degrees in some cases and vary depending on the variables analyzed and gait patterns presented (e.g., circumduction). This may be due to inadequate training data for certain gait patterns. Markerless motion capturing holds exciting potential to expand biomechanical research and assessment to real-world settings. We encourage the biomechanics community to make data from various activities publicly available to enable markerless solutions to further improve their deep learning algorithms.}, urldate = {2023-09-21}, booktitle = {Gait \& {Posture}}, author = {Horsak, Brian and Eichmann, Anna and Lauer-Maier, Kerstin and Prock, Kerstin and Dumphart, Bernhard}, month = sep, year = {2023}, keywords = {Center for Digital Health and Social Innovation, Institut für Gesundheitswissenschaften, SP CDHSI Motor Rehabilitation, Vortrag, Wiss. Beitrag, best, best-bhorsak, peer-reviewed}, pages = {S79--S80}, } @inproceedings{guggenberger_internal_2023, series = {{ESMAC} 2023 {Abstracts}}, title = {Internal lower limb rotation increases patella cartilage pressure in individuals with patellofemoral instability}, volume = {106}, copyright = {Copyright}, url = {https://www.sciencedirect.com/science/article/pii/S0966636223010081}, doi = {10.1016/j.gaitpost.2023.07.088}, abstract = {Introduction Femoral anteversion (FA) and tibial torsion (TT) are known factors to contribute to patellofemoral instability [1]. Studies showed increased knee joint loading in individuals with idiopathic rotational deformities [2]. Investigating the effect of FA and TT on patellofemoral joint loading and lower leg muscle forces could help to better understand their impact on patellofemoral instability. Research question How do FA and TT influence the knee joint loading and muscle force in individuals with patellofemoral instability? Methods Musculoskeletal simulations were performed based on the retrospective data set of 11 individuals diagnosed with patellofemoral instability (13 affected knees). We measured FA and TT from magnetic resonance images. The mean FA and TT were 27±11° and 31±8°, respectively. To account for the interaction of FA and TT, we calculated Lower Limb Rotation (LLR=TT-FA) [3]. The mean LLR value was 4±12°. For each individual an OpenSim model [4] was scaled for height, weight and maximum isometric muscle force [5]. We performed simulations for each participant based on a generic-scaled model and a second model with personalized FA and TT [6]. Kinematics, kinetics, muscle forces and patella cartilage pressure were estimated using the COMAK routine [7]. For muscle forces and patella cartilage loading, we calculated differences between both models for each participant and correlated them to LLR, FA and TT using Pearson correlation (α=0.05). Results LLR correlated to patella cartilage loading during different phases of stance (Fig. 1). No significant correlations were found between patella cartilage loading, FA and TT in our preliminary results. A more internally rotated LLR correlated with higher rectus femoris (r=-0.79, p=0.001) and gluteus minimus force (r=-0.77, p=0.002) as well as lower gluteus maximus (r=0.90, p{\textless}0.001) and gluteus medius force (r=0.71, p=0.007). Fig. 1 - Correlation between LLR, FA, TA and patella cartilage pressure. Bold values are statistically significant (p{\textless}0.05). Discussion Our preliminary results showed that FA and TT solely did not correlate to patella cartilage loading. In contrast LLR rotated either internally or externally, changed patella cartilage loading. An explanation could be that higher LLR and thus greater differences between FA and TT increase the rotational limb malalignment and therefore loading at the patellofemoral joint. Considering the fact that patella dislocations commonly occur to the lateral side, internal rotation of the LLR might be more relevant, as it leads to a lateralization of the patella [9]. Therefore, individuals with internally rotated LLR might increase rectus femoris force, resulting in higher patella cartilage loading to stabilize the patellofemoral joint. Decreased forces of gluteal muscles might be explained by change of abductor lever arm caused by differences in position of the greater trochanter. To conclude, beside an individual interpretation of FA and TT, additionally LLR should be considered, when examining lower limb alignment in individuals with patellofemoral instability.}, urldate = {2023-09-21}, booktitle = {Gait \& {Posture}}, author = {Guggenberger, Bernhard and Horsak, Brian and Habersack, Andreas and Smith, Colin and Svehlik, Martin and Kainz, Hans}, month = sep, year = {2023}, keywords = {Center for Digital Health and Social Innovation, Institut für Gesundheitswissenschaften, SP CDHSI Motor Rehabilitation, Vortrag, Wiss. Beitrag, best, best-bhorsak, peer-reviewed}, pages = {S71--S72}, } @article{slijepcevic_explainable_2023, title = {Explainable {Machine} {Learning} in {Human} {Gait} {Analysis}: {A} {Study} on {Children} {With} {Cerebral} {Palsy}}, volume = {11}, copyright = {CC-BY-NC-ND}, issn = {2169-3536}, shorttitle = {Explainable {Machine} {Learning} in {Human} {Gait} {Analysis}}, url = {https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10164110}, doi = {10.1109/ACCESS.2023.3289986}, abstract = {This work investigates the effectiveness of various machine learning (ML) methods in classifying human gait patterns associated with cerebral palsy (CP) and examines the clinical relevance of the learned features using explainability approaches. We trained different ML models, including convolutional neural networks, self-normalizing neural networks, random forests, and decision trees, and generated explanations for the trained models. For the deep neural networks, Grad-CAM explanations were aggregated on different levels to obtain explanations at the decision, class and model level. We investigate which subsets of 3D gait analysis data are particularly suitable for the classification of CP-related gait patterns. The results demonstrate the superiority of kinematic over ground reaction force data for this classification task and show that traditional ML approaches such as random forests and decision trees achieve better results and focus more on clinically relevant regions compared to deep neural networks. The best configuration, using sagittal knee and ankle angles with a random forest, achieved a classification accuracy of 93.4 \% over all four CP classes (crouch gait, apparent equinus, jump gait, and true equinus). Deep neural networks utilized not only clinically relevant features but also additional ones for their predictions, which may provide novel insights into the data and raise new research questions. Overall, the article provides insights into the application of ML in clinical practice and highlights the importance of explainability to promote trust and understanding of ML models.}, journal = {IEEE Access}, author = {Slijepcevic, Djordje and Zeppelzauer, Matthias and Unglaube, Fabian and Kranzl, Andreas and Breiteneder, Christian and Horsak, Brian}, year = {2023}, note = {Conference Name: IEEE Access}, keywords = {Biomechanics, Center for Artificial Intelligence, Center for Digital Health and Social Innovation, Departement Gesundheit, Department Gesundheit, Department Medien und Digitale Technologien, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Gait Analysis, Gait Classification, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Machine Learning, SP CDHSI Motor Rehabilitation, Wiss. Beitrag, best, best-bhorsak, peer-reviewed}, pages = {65906--65923}, } @article{horsak_overground_2023, title = {Overground walking while using a virtual reality head mounted display increases variability in trunk kinematics and reduces dynamic balance in young adults}, copyright = {CC-BY}, issn = {1434-9957}, url = {https://doi.org/10.1007/s10055-023-00851-7}, doi = {10.1007/s10055-023-00851-7}, abstract = {This study analyzed the effects of walking freely in virtual reality (VR) compared to walking in the real-world on dynamic balance and postural control. For this purpose, nine male and twelve female healthy participants underwent standard 3D gait analysis while walking randomly in a real laboratory and in a room-scale overground VR environment resembling the real laboratory. The VR was delivered to participants by a head-mounted-display which was operated wirelessly and calibrated to the real-world. Dynamic balance and postural control were assessed with (1) the margin of stability (MOS) in the anteroposterior (AP-MOS) and mediolateral (ML-MOS) directions at initial-contact, (2) the relationship between the mediolateral center of mass (COM) position and acceleration at mid-stance with subsequent step width, (3) and trunk kinematics during the entire gait cycle. We observed increased mediolateral (ML) trunk linear velocity variability, an increased coupling of the COM position and acceleration with subsequent step width, and a decrease in AP-MOS while walking in VR but no change in ML-MOS when walking in VR. Our findings suggest that walking in VR may result in a less reliable optical flow, indicated by increased mediolateral trunk kinematic variability, which seems to be compensated by the participants by slightly reweighing sensorimotor input and thereby consciously tightening the coupling between the COM and foot placement to avoid a loss of balance. Our results are particularly valuable for future developers who want to use VR to support gait analysis and rehabilitation.}, language = {en}, urldate = {2023-09-04}, journal = {Virtual Reality}, author = {Horsak, Brian and Simonlehner, Mark and Dumphart, Bernhard and Siragy, Tarique}, month = sep, year = {2023}, keywords = {Center for Digital Health and Social Innovation, Departement Gesundheit, Department Gesundheit, Dynamic stability, Gait analysis, Immersive virtual reality, Institut für Gesundheitswissenschaften, Motion capturing, Phaidra, Postural control, SP CDHSI Motor Rehabilitation, Wiss. Beitrag, best, best-bhorsak, peer-reviewed}, } @incollection{stamm_besonderheiten_2023, address = {Berlin}, edition = {2}, title = {Besonderheiten der {Forschung} im {Gesundheitswesen}}, isbn = {978-3-662-66500-8}, booktitle = {Wissenschaftliches {Arbeiten} und {Schreiben} - {Verstehen}, {Anwenden}, {Nutzen} für die {Praxis}}, publisher = {Springer}, author = {Stamm, Tanja and Karner, Gabriele and Kutrovatz, Jutta M. and Ritschl, Valentin and Perkhofer, Susanne and Tucek, Gerhard and Weigl, Roman}, editor = {Ritschl, Valentin and Weigl, Roman and Stamm, Tanja}, year = {2023}, keywords = {Department Gesundheit, Institut für Gesundheitswissenschaften, Publikationstyp Buch, Publikationstyp Schriftpublikation, Studiengang Diätologie, best, best-gkarner, best-lbkutrovatz}, pages = {29--53}, } @inproceedings{fischer_auditory_2016, address = {Segovia, Spain}, series = {Biosystems \& {Biorobotics}}, title = {An {Auditory} {Feedback} {System} in {Use} with {People} {Aged} +50 {Years}: {Compliance} and {Modifications} in {Gait} {Pattern}}, copyright = {©2017 Springer International Publishing AG}, isbn = {978-3-319-46668-2 978-3-319-46669-9}, shorttitle = {An {Auditory} {Feedback} {System} in {Use} with {People} {Aged} +50 {Years}}, url = {http://link.springer.com/chapter/10.1007/978-3-319-46669-9_143}, doi = {10/gnt2tg}, abstract = {Aging leads to gait impairments, which increases the risk for falls. In this study the impact of the auditory feedback system SONIGait on gait parameters in elderly persons was investigated. Twenty-one participants walked at self-selected speed with four variations of real-time auditory feedback of their plantar pressure. Repeated measures ANOVA was utilized to determine changes in time-distance parameters between walking without feedback and four feedback variations. After walking, they completed a questionnaire about their appraisal of the SONIGait system and the four different feedback modalities. There was a significant reduction in gait velocity (0.142 ± 0.04 m/s; p {\textless} 0.001) and prolongation of step time (0.02 ± 0.005 s; p {\textless} 0.001) during walking with SONIGait. No significant preference for any of the feedback variations was observed. Most participants evaluated the system SONIGait positively. Thus, real-time auditory feedback may be used in gait rehabilitation and may support an older person’s gait stability.}, language = {en}, urldate = {2016-10-19}, booktitle = {Converging {Clinical} and {Engineering} {Research} on {Neurorehabilitation} {II}}, publisher = {Springer International Publishing}, author = {Fischer, Theresa and Kiselka, Anita and Dlapka, Ronald and Doppler, Jakob and Iber, Michael and Gradl, Christian and Gorgas, Anna-Maria and Siragy, Tarique and Horsak, Brian}, editor = {Ibáñez, Jaime and González-Vargas, José and Azorín, José María and Akay, Metin and Pons, José Luis}, year = {2016}, note = {Projekt: CARMA Projekt: DHLab}, keywords = {Biofeedback, Biomechanics, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, DHLab, Departement Soziales, Department Gesundheit, Department Technologie, Forschungsgruppe Digital Technologies, Gait Analysis, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, Publikationstyp Vortrag, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, SP IGW Health Promotion \& Healthy Ageing, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, interdisziplinär, peer-reviewed, project\_carma, project\_sonigait}, pages = {881--885}, } @article{de_jesus_oliveira_auditory_2023, title = {Auditory feedback in tele-rehabilitation based on automated gait classification}, copyright = {CC-BY}, issn = {1617-4917}, url = {https://doi.org/10.1007/s00779-023-01723-2}, doi = {10.1007/s00779-023-01723-2}, abstract = {In this paper, we describe a proof-of-concept for the implementation of a wearable auditory biofeedback system based on a sensor-instrumented insole. Such a system aims to assist everyday users with static and dynamic exercises for gait rehabilitation interventions by providing auditory feedback based on plantar pressure distribution and automated classification of functional gait disorders. As ground reaction force (GRF) data are frequently used in clinical practice to quantitatively describe human motion and have been successfully used for the classification of gait patterns into clinically relevant classes, a feed-forward neural network was implemented on the firmware of the insoles to estimate the GRFs using pressure and acceleration data. The estimated GRFs approximated well the GRF measurements obtained from force plates. To distinguish between physiological gait and gait disorders, we trained and evaluated a support vector machine with labeled data from a publicly accessible dataset. The automated gait classification was then sonified for auditory feedback. The potential of the implemented auditory feedback for preventive and supportive applications in physical therapy was finally assessed with both expert and non-expert participants. A focus group revealed experts’ expectations for the proposed system, while a usability study assessed the clarity of the auditory feedback to everyday users. The evaluation shows promising results regarding the usefulness of our system in this application area.}, language = {en}, urldate = {2023-05-16}, journal = {Personal and Ubiquitous Computing}, author = {de Jesus Oliveira, Victor Adriel and Slijepčević, Djordje and Dumphart, Bernhard and Ferstl, Stefan and Reis, Joschua and Raberger, Anna-Maria and Heller, Mario and Horsak, Brian and Iber, Michael}, month = may, year = {2023}, keywords = {Biofeedback, Biomechanics, Center for Digital Health and Social Innovation, Departement Gesundheit, Departement Medien und Digitale Technologien, Department Gesundheit, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Gait Analysis, Gait Classification, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Machine Learning, Phaidra, SP CDHSI Motor Rehabilitation, Wiss. Beitrag, best, best-bhorsak, best-lbiber, peer-reviewed}, } @inproceedings{slijepcevic_towards_2023, address = {Heidelberg}, series = {{GAMMA} 2023 {Abstracts}}, title = {Towards more transparency: {The} utility of {Grad}-{CAM} in tracing back deep learning based classification decisions in children with cerebral palsy}, volume = {100}, copyright = {Copyright}, shorttitle = {Towards more transparency}, url = {https://www.sciencedirect.com/science/article/pii/S0966636222006828}, doi = {10.1016/j.gaitpost.2022.11.045}, abstract = {GAMMA Conference}, language = {en}, urldate = {2023-03-10}, booktitle = {Gait \& {Posture}}, author = {Slijepcevic, Djordje and Zeppelzauer, Matthias and Unglaube, Fabian and Kranzl, Andreas and Breiteneder, Christian and Horsak, Brian}, month = mar, year = {2023}, note = {Projekt: I3D}, keywords = {Biomechanics, Center for Artificial Intelligence, Center for Digital Health and Social Innovation, Department Gesundheit, Department Medien und Digitale Technologien, Forschungsgruppe Media Computing, Gait Analysis, Gait Classification, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Machine Learning, SP CDHSI Motor Rehabilitation, Vortrag, Wiss. Beitrag, best, peer-reviewed}, pages = {32--33}, } @article{dumphart_robust_2023, title = {Robust deep learning-based gait event detection across various pathologies}, volume = {18}, copyright = {CC-BY}, issn = {1932-6203}, url = {https://dx.plos.org/10.1371/journal.pone.0288555}, doi = {10.1371/journal.pone.0288555}, abstract = {The correct estimation of gait events is essential for the interpretation and calculation of 3D gait analysis (3DGA) data. Depending on the severity of the underlying pathology and the availability of force plates, gait events can be set either manually by trained clinicians or detected by automated event detection algorithms. The downside of manually estimated events is the tedious and time-intensive work which leads to subjective assessments. For automated event detection algorithms, the drawback is, that there is no standardized method available. Algorithms show varying robustness and accuracy on different pathologies and are often dependent on setup or pathology-specific thresholds. In this paper, we aim at closing this gap by introducing a novel deep learning-based gait event detection algorithm called IntellEvent , which shows to be accurate and robust across multiple pathologies. For this study, we utilized a retrospective clinical 3DGA dataset of 1211 patients with four different pathologies (malrotation deformities of the lower limbs, club foot, infantile cerebral palsy (ICP), and ICP with only drop foot characteristics) and 61 healthy controls. We propose a recurrent neural network architecture based on long-short term memory (LSTM) and trained it with 3D position and velocity information to predict initial contact (IC) and foot off (FO) events. We compared IntellEvent to a state-of-the-art heuristic approach and a machine learning method called DeepEvent. IntellEvent outperforms both methods and detects IC events on average within 5.4 ms and FO events within 11.3 ms with a detection rate of ≥ 99\% and ≥ 95\%, respectively. Our investigation on generalizability across laboratories suggests that models trained on data from a different laboratory need to be applied with care due to setup variations or differences in capturing frequencies.}, language = {en}, number = {8}, urldate = {2023-08-17}, journal = {PLOS ONE}, author = {Dumphart, Bernhard and Slijepcevic, Djordje and Zeppelzauer, Matthias and Kranzl, Andreas and Unglaube, Fabian and Baca, Arnold and Horsak, Brian}, editor = {Srinivasan, Kathiravan}, month = aug, year = {2023}, keywords = {Artificial intelligence, Biomechanics, Center for Artificial Intelligence, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, Department Gesundheit, Department Medien und Digitale Technologien, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Gait Analysis, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Machine learning, Phaidra, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Wiss. Beitrag, best, best-bdumphart, peer-reviewed}, pages = {e0288555}, } @inproceedings{vulpe-grigorasi_multimodal_2023, address = {Tubingen Germany}, title = {Multimodal machine learning for cognitive load based on eye tracking and biosensors}, isbn = {9798400701504}, url = {https://dl.acm.org/doi/10.1145/3588015.3589534}, doi = {10.1145/3588015.3589534}, language = {en}, urldate = {2024-01-23}, booktitle = {2023 {Symposium} on {Eye} {Tracking} {Research} and {Applications}}, publisher = {ACM}, author = {Vulpe-Grigorasi, Adrian}, year = {2023}, note = {Projekt: EyeQTrack}, keywords = {Center for Digital Health and Social Innovation, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, SP CDHSI Digital Wellbeing, Vortrag, Wiss. Beitrag, best, peer-reviewed}, pages = {1--3}, } @article{siragy_comparison_2023, title = {Comparison of over-ground and treadmill perturbations for simulation of real-world slips and trips: {A} systematic review}, volume = {100}, copyright = {CC-BY}, issn = {0966-6362}, shorttitle = {Comparison of over-ground and treadmill perturbations for simulation of real-world slips and trips}, url = {https://www.sciencedirect.com/science/article/pii/S0966636222007342}, doi = {10.1016/j.gaitpost.2022.12.015}, abstract = {Background Trips and slips increase fall risk for young and older adults. To examine recovery responses, studies utilized treadmill and/or over-ground methods to simulate real-world perturbations. However, differences in the recovery response between treadmill and over-ground perturbations remain unexamined. Research question To assess the current literature on the reactive recovery responses between over-ground- and split-belt treadmill trips and slips as well as the effect of aging on these responses. Methods PubMed, Medline, Web of Science, SCOPUS, and Cochrane databases were searched for publications examining trips and slips in healthy young, healthy older adults, and older adults who fall. Included articles were in English, full-text accessible, and biomechanically quantified the reactive recovery responses for slips and trips during either over-ground or split-belt treadmill protocols. The initial database search yielded 1075 articles and 31 articles were included after title, abstract, and full-text screening. Results For slips, 7 articles utilized lubricated surfaces while 5 articles used treadmills. Further, 3 studies examined differences between older and younger adults. For trips, 9 articles utilized obstacles and 7 used treadmills. Further, 4 articles examined differences between older and young adults and 1 article only examined older adults during over-ground trips. For both perturbations, treadmill and over-ground protocols demonstrated similar anteroposterior destabilization on the center of mass. In the mediolateral direction, over-ground slips consistently found a lateral destabilization while treadmill articles did not examine this direction. Foot placement recovery responses varied less for both perturbation directions on a treadmill compared to over-ground. Significance Although treadmill and over-ground perturbations destabilize the center of mass similarly, the recovery response to these perturbations were different on treadmills. Specifically, recovery responses were more consistent for both slips and trips on treadmills. As older adults have difficulty in perturbation recovery scaling, treadmills may be limited in their ability to investigate the variety of aging impairments on perturbation recovery responses.}, language = {en}, urldate = {2023-01-17}, journal = {Gait \& Posture}, author = {Siragy, Tarique and Russo, Yuri and Young, Will and Lamb, Sallie E.}, month = feb, year = {2023}, keywords = {Center for Digital Health and Social Innovation, Department Gesundheit, Institut für Gesundheitswissenschaften, Phaidra, Publikationstyp Schriftpublikation, SP CDHSI Motor Rehabilitation, Wiss. Beitrag, best, peer-reviewed}, pages = {201--209}, } @article{slijepcevic_explaining_2022, title = {Explaining {Machine} {Learning} {Models} for {Clinical} {Gait} {Analysis}}, volume = {3}, copyright = {CC-BY-NC-SA}, issn = {2691-1957}, url = {https://doi.org/10.1145/3474121}, doi = {10.1145/3474121}, number = {2}, journal = {ACM Transactions on Computing for Healthcare}, author = {Slijepcevic, Djordje and Horst, Fabian and Lapuschkin, Sebastian and Horsak, Brian and Raberger, Anna-Maria and Kranzl, Andreas and Samek, Wojciech and Breitender, Christian and Schöllhorn, Wolfgang and Zeppelzauer, Matthias}, year = {2022}, note = {Projekt: I3D Projekt: ReMoCapLab Projekt: DHLab}, keywords = {2020, Biomechanics, Center for Artificial Intelligence, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, DHLab, Department Gesundheit, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Gait Analysis, Gait Classification, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Machine Learning, Media Computing Group, SP CDHSI Motor Rehabilitation, Studiengang Physiotherapie, Wiss. Beitrag, best, best-mzeppelzauer, peer-reviewed}, pages = {14:1--14:27}, } @article{neubauer_artificial-intelligence-aided_2023, title = {Artificial-{Intelligence}-{Aided} {Radiographic} {Diagnostic} of {Knee} {Osteoarthritis} {Leads} to a {Higher} {Association} of {Clinical} {Findings} with {Diagnostic} {Ratings}}, volume = {12}, copyright = {CC-BY}, issn = {2077-0383}, url = {https://www.mdpi.com/2077-0383/12/3/744}, doi = {10.3390/jcm12030744}, abstract = {Background: Radiographic knee osteoarthritis (OA) severity and clinical severity are often dissociated. Artificial intelligence (AI) aid was shown to increase inter-rater reliability in radiographic OA diagnosis. Thus, AI-aided radiographic diagnoses were compared against AI-unaided diagnoses with regard to their correlations with clinical severity. Methods: Seventy-one DICOMs (m/f = 27:42, mean age: 27.86 ± 6.5) (X-ray format) were used for AI analysis (KOALA software, IB Lab GmbH). Subjects were recruited from a physiotherapy trial (MLKOA). At baseline, each subject received (i) a knee X-ray and (ii) an assessment of five main scores (Tegner Scale (TAS); Knee Injury and Osteoarthritis Outcome Score (KOOS); International Physical Activity Questionnaire; Star Excursion Balance Test; Six-Minute Walk Test). Clinical assessments were repeated three times (weeks 6, 12 and 24). Three physicians analyzed the presented X-rays both with and without AI via KL grading. Analyses of the (i) inter-rater reliability (IRR) and (ii) Spearman’s Correlation Test for the overall KL score for each individual rater with clinical score were performed. Results: We found that AI-aided diagnostic ratings had a higher association with the overall KL score and the KOOS. The amount of improvement due to AI depended on the individual rater. Conclusion: AI-guided systems can improve the ratings of knee radiographs and show a stronger association with clinical severity. These results were shown to be influenced by individual readers. Thus, AI training amongst physicians might need to be increased. KL might be insufficient as a single tool for knee OA diagnosis.}, language = {en}, number = {3}, urldate = {2023-02-08}, journal = {Journal of Clinical Medicine}, author = {Neubauer, Markus and Moser, Lukas and Neugebauer, Johannes and Raudner, Marcus and Wondrasch, Barbara and Führer, Magdalena and Emprechtinger, Robert and Dammerer, Dietmar and Ljuhar, Richard and Salzlechner, Christoph and Nehrer, Stefan}, month = jan, year = {2023}, keywords = {Department Gesundheit, Institut für Gesundheitswissenschaften, Phaidra, best, peer-reviewed}, pages = {744}, } @article{horst_modeling_2023, title = {Modeling biological individuality using machine learning: {A} study on human gait}, volume = {21}, copyright = {CC-BY-NC-ND}, issn = {2001-0370}, shorttitle = {Modeling biological individuality using machine learning}, doi = {10.1016/j.csbj.2023.06.009}, abstract = {Human gait is a complex and unique biological process that can offer valuable insights into an individual's health and well-being. In this work, we leverage a machine learning-based approach to model individual gait signatures and identify factors contributing to inter-individual variability in gait patterns. We provide a comprehensive analysis of gait individuality by (1) demonstrating the uniqueness of gait signatures in a large-scale dataset and (2) highlighting the gait characteristics that are most distinctive to each individual. We utilized the data from three publicly available datasets comprising 5368 bilateral ground reaction force recordings during level overground walking from 671 distinct healthy individuals. Our results show that individuals can be identified with a prediction accuracy of 99.3\% by using the bilateral signals of all three ground reaction force components, with only 10 out of 1342 recordings in our test data being misclassified. This indicates that the combination of bilateral ground reaction force signals with all three components provides a more comprehensive and accurate representation of an individual's gait signature. The highest accuracy was achieved by (linear) Support Vector Machines (99.3\%), followed by Random Forests (98.7\%), Convolutional Neural Networks (95.8\%), and Decision Trees (82.8\%). The proposed approach provides a powerful tool to better understand biological individuality and has potential applications in personalized healthcare, clinical diagnosis, and therapeutic interventions.}, language = {eng}, journal = {Computational and Structural Biotechnology Journal}, author = {Horst, Fabian and Slijepcevic, Djordje and Simak, Marvin and Horsak, Brian and Schöllhorn, Wolfgang Immanuel and Zeppelzauer, Matthias}, year = {2023}, pmid = {37416082}, pmcid = {PMC10319823}, keywords = {Biomechanics, Center for Artificial Intelligence, Center for Digital Health and Social Innovation, Departement Gesundheit, Departement Medien und Digitale Technologien, Department Gesundheit, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Gait Analysis, Gait Classification, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Machine Learning, Media Computing Group, Musculoskeletal Simulations, Phaidra, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Wiss. Beitrag, best, best-bhorsak, peer-reviewed}, pages = {3414--3423}, } @inproceedings{judmaier_untersuchungsmethoden_2014, address = {Berlin}, title = {Untersuchungsmethoden zur {Gendersensibilität} von {Arbeitsplätzen} im {Umfeld} sicherheitskritischer {Systeme}}, booktitle = {Gender {UseT}}, publisher = {Kompetenzzentrum Technik – Diversity – Chancengleichheit e.V.}, author = {Judmaier, Peter and Pohl, Margit and Michelberger, Frank and Bichler, Romana and Erharter, Dorothea and Fränzl, Thomas and Kunz, Angelika}, year = {2014}, keywords = {Creative Industries, Department Gesundheit, Department Technologie, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Institut für Mobilitätsforschung, Publikationstyp Schriftpublikation, SP IGW Health Promotion \& Healthy Ageing, Studiengang Physiotherapie, best, peer-reviewed, user centered design, ⛔ No DOI found}, } @misc{schweiger_pro_2016, address = {St. Pölten}, type = {Invited talk and workshop}, title = {Pro \& {Contra} {Diätologischer} {Prozess} – {Ein} {Erfahrungsaustausch} unter {Anwenderinnen} und {Anwen}-dern}, author = {Schweiger, Alexandra and Kohlmaier, Barbara and Moser, Michaela and Sommerauer, Edith}, month = apr, year = {2016}, keywords = {2016, Department Gesundheit, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, Publikationstyp Vortrag, SP IGW Clinical \& Healthcare Research, Studiengang Diätologie, best}, } @misc{kolm_kompetenzorientierte_2016, address = {St. Pölten}, type = {Invited talk and workshop}, title = {Kompetenzorientierte {Modulprüfung} am {Studiengang} {Diätologie}. {Interprofessionelles} {Prüfungsfor}-mat anhand klinischer {Fallbeispiele} in {Medizin} \& {Ernährungsstherapie}}, author = {Kolm, Alexandra and Kritz, Harald}, month = oct, year = {2016}, note = {Projekt: IMPECD}, keywords = {2016, Department Gesundheit, Einladung, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, Publikationstyp Vortrag, SP IGW Education \& Lifelong Learning for Health Professionals, Studiengang Diätologie, best}, } @misc{haupt_transfettsauren_2014, address = {Groß Gerungs}, type = {Invited talk}, title = {Transfettsäuren, {Koffein}, {Alkohol} und {Ernährung} bei {Hypertonie}}, language = {Deutsch}, author = {Haupt, Alexandra}, month = sep, year = {2014}, keywords = {2014, Department Gesundheit und Soziales, Einladung, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, Publikationstyp Vortrag, SP IGW Clinical \& Healthcare Research, Studiengang Diätologie, best}, } @misc{leitner_mens_2014, address = {Las Palmas de Gran Canaria}, type = {Posterpräsentation}, title = {Men's health - {Eating} habits, health status and health behaviour of young {Austrian} men aged 17 to 20 years in context to their lifestyles –}, language = {English}, author = {Leitner, Gabriele and Rust, Petra and Elmadfa, Ibrahim}, month = nov, year = {2014}, keywords = {2014, Bewerbungsverfahren, Department Gesundheit und Soziales, Institut für Gesundheitswissenschaften, Poster, Publikationstyp Poster, Publikationstyp Präsentation, SP IGW Health Promotion \& Healthy Ageing, Studiengang Diätologie, best}, } @misc{leitner_influence_2016, address = {Dresden}, type = {Posterpräsentation}, title = {Influence of dietary habits and lifestyle factors on health indicators of young men, aged 17-19, in {Lower} {Austria}}, author = {Leitner, Gabriele}, month = jun, year = {2016}, keywords = {2016, Bewerbungsverfahren, Department Gesundheit, Institut für Gesundheitswissenschaften, Publikationstyp Poster, Publikationstyp Präsentation, SP IGW Health Promotion \& Healthy Ageing, Studiengang Diätologie, best}, } @incollection{kolm_lessons-learned_2015, address = {St. Pölten}, title = {Lessons-{Learned} aus dem {Pilotprojekt} „{Inverted} {Classroom}“ am {Studiengang} {Diätologie}}, isbn = {978-3-200-03969-8}, url = {http://skill.fhstp.ac.at/wp-content/uploads/2014/06/Tagungsband_TagderLehre_Online_2015-31.pdf}, booktitle = {Neue {Technologien} – {Kollaboration} – {Personalisierung}, {Beiträge} zum 3. {Tag} der {Lehre} an der {FH} {St}. {Pölten} am 16. {Oktober} 2014}, publisher = {Fachhochschule St. Pölten}, author = {Kolm, Alexandra and Ramler, Heidemarie and Berger, Julia}, year = {2015}, note = {Projekt: IMPECD}, keywords = {2015, Department Gesundheit, Department Gesundheit und Soziales, Institut für Gesundheitswissenschaften, Publikationstyp Schriftpublikation, SP IGW Education \& Lifelong Learning for Health Professionals, Studiengang Diätologie, best}, pages = {16--21}, } @incollection{kolm_improvisationsmethoden_2016, address = {St. Pölten}, title = {Improvisationsmethoden in der {Umsetzung} einer nach {Kriterien} des {Inverted} {Classroom} {Modells} gestalteten {Lehrveranstaltung} zum diätologischen {Beratungsprozess}}, isbn = {978-3-99023-410-5}, booktitle = {Das {Inverted} {Classroom} {Modell}. {Begleitband} zur 5. {Konferenz} „{Inverted} {Classroom} and {Beyond}“ an der {FH} {St}. {Pölten} am 23. und 24. {Februar} 2016}, publisher = {Eigenverlag FH St. Pölten}, author = {Kolm, Alexandra and Freisleben-Teutscher, Christian F.}, editor = {Haag, Johann and Freisleben-Teutscher, Christian F.}, year = {2016}, keywords = {2016, Department Gesundheit, Institut für Gesundheitswissenschaften, Publikationstyp Buch, Publikationstyp Schriftpublikation, SP IGW Education \& Lifelong Learning for Health Professionals, Studiengang Diätologie, best}, pages = {63--70}, } @misc{kolm_ausbildung_2016, address = {Wien}, type = {Posterpräsentation}, title = {Ausbildung von {Gesundheitsfachkräften} in der {Diätetik}}, author = {Kolm, Alexandra and Werkman, Andrea and Valentini, Luzia and Vanherle, Koen and Baete, Eline and Aerts, Hanna and Le Bruyn, Bente and Hahn, Sigrid and Gast, Christina and Roemeling-Walters, Maaike and Heine-Bröring, Renate and Buchholz, Daniel and Rachman-Elbaum, Shelly and Höld, Elisabeth and Huber, Marie-Luise and Wewerka-Kreimel, Daniela and Kohlenberg-Müller, Kathrin}, month = nov, year = {2016}, note = {Projekt: IMPECD}, keywords = {2016, Bewerbungsverfahren, Center for Digital Health Innovation, Department Gesundheit, Institut für Gesundheitswissenschaften, Publikationstyp Poster, Publikationstyp Präsentation, SP IGW Education \& Lifelong Learning for Health Professionals, Studiengang Diätologie, best}, } @misc{kolm_ausbildung_2016, address = {Berlin}, type = {Posterpräsentation}, title = {Ausbildung von {Gesundheitsfachkräften} in der {Diätetik} für das 21. {Jahrhundert} am {Beispiel} {IMPECD}}, author = {Kolm, Alexandra and Kohlenberg-Müller, Kathrin and Vanherle, Koen and Werkman, Andrea and Valentini, Luzia}, month = oct, year = {2016}, note = {Projekt: IMPECD}, keywords = {2016, Bewerbungsverfahren, Department Gesundheit, Institut für Gesundheitswissenschaften, Publikationstyp Poster, Publikationstyp Präsentation, SP IGW Education \& Lifelong Learning for Health Professionals, Studiengang Diätologie, best}, } @misc{datzreiter_validierung_2016, address = {Wien}, type = {Posterpräsentation}, title = {Validierung des {Screenings} zur {Risikoerfassung} von {Essstörungen} bei adipösen {Erwachsenen} ({SREA})}, author = {Datzreiter, Martina and Mayer, Christina and Schnötzinger, Marion and Möseneder, Jutta M. and Gnauer, Sandra and Kaiser, Monika and König, Alexandra and Karner, Gabriele and Kolm, Alexandra}, month = nov, year = {2016}, keywords = {2016, Bewerbungsverfahren, Department Gesundheit, Institut für Gesundheitswissenschaften, Publikationstyp Poster, Publikationstyp Präsentation, SP IGW Clinical \& Healthcare Research, Studiengang Diätologie, best}, } @article{kolm_international_2021, title = {International {Online} {Collaboration} {Competencies} in {Higher} {Education} {Students}: {A} {Systematic} {Review}}, issn = {1028-3153}, shorttitle = {International {Online} {Collaboration} {Competencies} in {Higher} {Education} {Students}}, url = {https://doi.org/10.1177/10283153211016272}, doi = {10/gkjd8j}, abstract = {The COVID-19 pandemic has been forcing people to work remotely in virtual teams around the globe. Global virtual teamwork will continue, and people are not sufficiently prepared for this, resulting in reduced team commitment and lower performance. Higher education institutions need to equip their graduates with International Online Collaboration Competencies (IOCCs), but research into these is fragmented, lacking even a definition of these competencies. This study was systematically reviewing empirical studies on IOCCs. 516 studies were reviewed, and data from 14 full texts were analyzed. Six competence domains emerged from the literature. Most studies focused on single domains of IOCCs, and none of the studies covered all domains. Results indicate that this preliminary framework for higher education students provides a first overview of the fragmented literature on IOCCs. Methods to teach and evaluate IOCCs acquisition are underdeveloped but urgently needed to equip professionals for global virtual teamwork.}, language = {en}, urldate = {2022-01-27}, journal = {Journal of Studies in International Education}, author = {Kolm, Alexandra and de Nooijer, Jascha and Vanherle, Koen and Werkman, Andrea and Wewerka-Kreimel, Daniela and Rachman-Elbaum, Shelly and van Merriënboer, Jeroen J. G.}, month = may, year = {2021}, note = {Publisher: SAGE Publications Inc}, keywords = {Department Gesundheit, Institut für Gesundheitswissenschaften, Publiktationstyp Schriftpublikation, SP IGW Education \& Lifelong Learning for Health Professionals, Studiengang Diätologie, best, best-lbkolm, best-lbwewerka, peer-reviewed}, } @misc{haupt_lessons-learned_2014, address = {St. Pölten}, type = {Invited talk}, title = {Lessons-{Learned} aus dem {Pilotprojekt} „{Inverted} {Classroom}“ am {Studiengang} {Diätologie}}, author = {Haupt, Alexandra and Berger, Julia}, month = oct, year = {2014}, keywords = {2014, Department Gesundheit und Soziales, Einladung, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, Publikationstyp Vortrag, SP IGW Education \& Lifelong Learning for Health Professionals, Studiengang Diätologie, best}, } @inproceedings{slijepcevic_explaining_2022, series = {{ESMAC} 2022 {Abstracts}}, title = {Explaining machine learning models for age classification in human gait analysis}, volume = {97}, url = {https://www.sciencedirect.com/science/article/pii/S0966636222003538}, doi = {10.1016/j.gaitpost.2022.07.153}, language = {en}, urldate = {2022-11-11}, booktitle = {Gait \& {Posture}}, author = {Slijepcevic, D. and Horst, F. and Simak, M. and Lapuschkin, S. and Raberger, A. M. and Samek, W. and Breiteneder, C. and Schöllhorn, W. I. and Zeppelzauer, M. and Horsak, B.}, month = sep, year = {2022}, note = {Projekt: I3D}, keywords = {Biomechanics, Center for Artificial Intelligence, Center for Digital Health and Social Innovation, Department Gesundheit, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Gait Analysis, Gait Classification, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Machine Learning, Media Computing Group, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Vortrag, Wiss. Beitrag, best, peer-reviewed}, pages = {S252--S253}, } @article{wagner_kavagait_2018, title = {{KAVAGait}: {Knowledge}-{Assisted} {Visual} {Analytics} for {Clinical} {Gait} {Analysis}}, volume = {25}, url = {https://doi.org/10.1109/TVCG.2017.2785271}, doi = {10/ghppzn}, abstract = {In 2014, more than 10 million people in the US were affected by an ambulatory disability. Thus, gait rehabilitation is a crucial part of health care systems. The quantification of human locomotion enables clinicians to describe and analyze a patient’s gait performance in detail and allows them to base clinical decisions on objective data. These assessments generate a vast amount of complex data which need to be interpreted in a short time period. We conducted a design study in cooperation with gait analysis experts to develop a novel Knowledge-Assisted Visual Analytics solution for clinical Gait analysis (KAVAGait). KAVAGait allows the clinician to store and inspect complex data derived during clinical gait analysis. The system incorporates innovative and interactive visual interface concepts, which were developed based on the needs of clinicians. Additionally, an explicit knowledge store (EKS) allows externalization and storage of implicit knowledge from clinicians. It makes this information available for others, supporting the process of data inspection and clinical decision making. We validated our system by conducting expert reviews, a user study, and a case study. Results suggest that KAVAGait is able to support a clinician during clinical practice by visualizing complex gait data and providing knowledge of other clinicians.}, number = {3}, journal = {IEEE Transactions on Visualization and Computer Graphics (TVCG)}, author = {Wagner, Markus and Slijepcevic, Djordje and Horsak, Brian and Rind, Alexander and Zeppelzauer, Matthias and Aigner, Wolfgang}, year = {2018}, note = {Projekt: KAVA-Time Projekt: IntelliGait Projekt: CARMA Projekt: DHLab}, keywords = {Biomechanics, Center for Artificial Intelligence, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, DHLab, Design Study, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Digital Technologies, Forschungsgruppe Media Computing, Gait Analysis, Gait Classification, Healthcare, Human Gait Analysis, Human-Computer Interaction, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Machine Learning, Media Computing Group, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Visual analytics, Wiss. Beitrag, best, best-bhorsak, best-lbaigner, best-lbwagnerm, best-mzeppelzauer, information visualization, knowledge generation, peer-reviewed}, pages = {1528--1542}, } @article{slijepcevic_input_2020, title = {Input {Representations} and {Classification} {Strategies} for {Automated} {Human} {Gait} {Analysis}}, volume = {76}, issn = {0966-6362}, doi = {10/ghz24x}, journal = {Gait \& Posture}, author = {Slijepcevic, Djordje and Zeppelzauer, Matthias and Schwab, Caterine and Raberger, Anna-Maria and Breitender, Christian and Horsak, Brian}, year = {2020}, note = {Projekt: IntelliGait Projekt: I3D Projekt: ReMoCap-Lab Projekt: DHLab}, keywords = {2020, Biomechanics, Center for Artificial Intelligence, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, Department Gesundheit, Eintrag überprüfen, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Gait Analysis, Gait Classification, Green OA, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Machine Learning, Media Computing Group, Open Access, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, peer-reviewed}, pages = {198--203}, } @article{slijepcevic_automatic_2018, title = {Automatic {Classification} of {Functional} {Gait} {Disorders}}, volume = {5}, issn = {2168-2194}, url = {https://arxiv.org/abs/1712.06405}, doi = {10/ghz24w}, number = {22}, urldate = {2017-12-21}, journal = {IEEE Journal of Biomedical and Health Informatics}, author = {Slijepcevic, Djordje and Zeppelzauer, Matthias and Raberger, Anna-Maria and Schwab, Caterine and Schuller, Michael and Baca, Arnold and Breiteneder, Christian and Horsak, Brian}, year = {2018}, note = {Projekt: IntelliGait Projekt: CARMA Projekt: DHLab}, keywords = {Biomechanics, Center for Artificial Intelligence, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, DHLab, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Gait Analysis, Gait Classification, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Machine Learning, Media Computing Group, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, best-mzeppelzauer, peer-reviewed}, pages = {1653 -- 1661}, } @inproceedings{slijepcevic_usefulness_2019, address = {Vienna, Austria}, title = {On the usefulness of statistical parameter mapping for feature selection in automated gait classification}, booktitle = {Book of {Abstracts} of the 25th {Conference} of the {European} {Society} of {Biomechanics} ({ESB})}, author = {Slijepcevic, Djordje and Raberger, Anna-Maria and Zeppelzauer, Matthias and Dumphart, Bernhard and Breiteneder, Christian and Horsak, Brian}, year = {2019}, note = {Projekt: IntelliGait Projekt: DHLab}, keywords = {Biomechanics, Center for Artificial Intelligence, Center for Digital Health Innovation, Digital Health, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Gait Analysis, Gait Classification, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Machine Learning, Media Computing Group, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Vortrag, Wiss. Beitrag, best, best-bhorsak, peer-reviewed, ⛔ No DOI found}, pages = {1}, } @inproceedings{dumphart_automated_2021, series = {{ESMAC} 2021 {Abstracts}}, title = {An automated deep learning-based gait event detection algorithm for various pathologies}, volume = {90}, url = {https://www.sciencedirect.com/science/article/pii/S0966636221003350}, doi = {https://doi.org/10.1016/j.gaitpost.2021.09.026}, language = {en}, urldate = {2021-10-15}, booktitle = {Gait \& {Posture}}, author = {Dumphart, B. and Slijepčević, D. and Unglaube, F. and Kranzl, A. and Baca, A. and Zeppelzauer, M. and Horsak, B.}, month = oct, year = {2021}, note = {Projekt: ELSA}, keywords = {Biomechanics, Center for Artificial Intelligence, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, Department Gesundheit, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Gait Analysis, Gait Classification, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Machine Learning, SP CDHSI Motor Rehabilitation, Vortrag, Wiss. Beitrag, best, peer-reviewed}, pages = {50--51}, } @inproceedings{krondorfer_deep_2021, series = {{ESMAC} 2021 {Abstracts}}, title = {Deep learning-based similarity retrieval in clinical {3D} gait analysis}, volume = {90}, url = {https://www.sciencedirect.com/science/article/pii/S0966636221003751}, doi = {https://doi.org/10.1016/j.gaitpost.2021.09.066}, language = {en}, urldate = {2021-10-15}, booktitle = {Gait \& {Posture}}, author = {Krondorfer, P. and Slijepčević, D. and Unglaube, F. and Kranzl, A. and Breiteneder, C. and Zeppelzauer, M. and Horsak, B.}, month = oct, year = {2021}, note = {Projekt: I3D}, keywords = {Biomechanics, Center for Artificial Intelligence, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, Department Gesundheit, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Gait Analysis, Gait Classification, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Machine Learning, SP CDHSI Motor Rehabilitation, Vortrag, Wiss. Beitrag, best, peer-reviewed}, pages = {127--128}, } @inproceedings{slijepcevic_ground_2017, address = {Trondheim, Norway}, title = {Ground reaction force measurements for gait classification tasks: {Effects} of different {PCA}-based representations}, volume = {57}, url = {http://www.gaitposture.com/article/S0966-6362(17)30712-9/pdf}, doi = {10.1016/j.gaitpost.2017}, booktitle = {Gait \& {Posture} {Supplement}}, author = {Slijepcevic, Djordje and Horsak, Brian and Schwab, Caterine and Raberger, Anna-Maria and Schüller, Michael and Baca, Arnold and Breitender, Christian and Zeppelzauer, Matthias}, year = {2017}, note = {Projekt: IntelliGait Projekt: DHLab}, keywords = {2017, Biofeedback, Biomechanics, Center for Artificial Intelligence, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, Creative Industries, DHLab, Department Technologie, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Gait Analysis, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Machine Learning, Media Computing Group, Pattern recognition, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, peer-reviewed, project\_carma, project\_intelligait, ⚠️ Invalid DOI}, pages = {4--5}, } @article{horsak_gaitrec_2020, title = {{GaitRec}, a large-scale ground reaction force dataset of healthy and impaired gait}, volume = {7:143}, copyright = {CC BY}, url = {https://www.nature.com/articles/s41597-020-0481-z}, doi = {10/gh372d}, number = {1}, journal = {Scientific Data}, author = {Horsak, Brian and Slijepcevic, Djordje and Raberger, Anna-Maria and Schwab, Caterine and Worisch, Marianne and Zeppelzauer, Matthias}, year = {2020}, note = {Projekt: I3D Projekt: IntelliGait Projekt: DHLab}, keywords = {2019, Biomechanics, Center for Artificial Intelligence, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, DHLab, Eintrag überprüfen, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Gait Analysis, Gait Classification, Green OA, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Machine Learning, Media Computing Group, Open Access, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, best-mzeppelzauer, peer-reviewed, submitted}, pages = {1--8}, } @inproceedings{schwab_intelligait_2018, address = {Hamburg, Deutschland}, title = {{IntelliGait}: {Automatische} {Gangmusteranalyse} für die robuste {Erkennung} von {Gangstörungen}}, booktitle = {Tagungsband des 2ten {GAMMA} {Kongress} ({Gesellschaft} für die {Analyse} {Menschlicher} {Motorik} in ihrer klinischen {Anwendung})}, author = {Schwab, Caterine and Slijepcevic, Djordje and Zeppelzauer, Matthias and Raberger, Anna-Maria and Dumphart, Bernhard and Baca, Arnold and Breitender, Christian and Horsak, Brian}, year = {2018}, note = {Projekt: IntelliGait Projekt: CARMA Projekt: DHLab}, keywords = {Biomechanics, Center for Artificial Intelligence, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, Creative Industries, DHLab, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Gait Analysis, Gait Classification, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Machine Learning, Media Computing Group, Pattern recognition, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, peer-reviewed, ⛔ No DOI found}, } @inproceedings{horsak_explainable_2020, address = {München, Deutschland}, title = {Explainable {Artificial} {Intelligence} ({XAI}) und ihre {Anwendung} auf {Klassifikationsprobleme} in der {Ganganalyse}}, booktitle = {Abstractband des 3. {GAMMA} {Kongress}}, author = {Horsak, Brian and Dumphart, Bernhard and Slijepcevic, Djordje and Zeppelzauer, Matthias}, year = {2020}, note = {Projekt: ReMoCap-Lab Projekt: DHLab Projekt: I3D}, keywords = {Biomechanics, Center for Artificial Intelligence, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, Department Gesundheit, Eintrag überprüfen, Forschungsgruppe Media Computing, Gait Analysis, Gait Classification, Green OA, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Machine Learning, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Vortrag, Wiss. Beitrag, best, best-bhorsak, peer-reviewed, ⛔ No DOI found}, } @article{horst_explaining_2020, title = {Explaining automated gender classification of human gait}, volume = {81, supplement 1}, url = {http://www.sciencedirect.com/science/article/pii/S0966636220303568}, doi = {10/ghr9k6}, language = {en}, urldate = {2020-09-14}, journal = {Gait \& Posture}, author = {Horst, F. and Slijepcevic, D. and Zeppelzauer, M. and Raberger, A. M. and Lapuschkin, S. and Samek, W. and Schöllhorn, W. I. and Breiteneder, C. and Horsak, B.}, year = {2020}, note = {Projekt: ReMoCap-Lab Projekt: I3D}, keywords = {2020, Biomechanics, Center for Artificial Intelligence, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, DHLab, Department Gesundheit, Digital Health, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Gait Analysis, Gait Classification, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Institutional Access, Machine Learning, Media Computing Group, Poster, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Vortrag, Wiss. Beitrag, best, best-bhorsak, peer-reviewed}, pages = {159--160}, } @inproceedings{slijepcevic_towards_2018, address = {Prague, Czech Republic}, title = {Towards an optimal combination of input signals and derived representations for gait classification based on ground reaction force measurements.}, volume = {65}, doi = {10/gh38wn}, booktitle = {Gait \& {Posture} {Supplement}}, author = {Slijepcevic, Djordje and Zeppelzauer, Matthias and Schwab, Caterine and Raberger, Anna-Maria and Dumphart, B and Baca, Arnold and Breiteneder, Christian and Horsak, Brian}, year = {2018}, note = {Projekt: IntelliGait Projekt: CARMA Projekt: DHLab}, keywords = {Biomechanics, Center for Artificial Intelligence, Center for Digital Health and Social Innovation, Classification, DHLab, FH SP Data Analytics \& Visual Computing, Feature Representations, Forschungsgruppe Media Computing, Gait Analysis, Gait Classification, Gait Recognition, Human Gait Analysis, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Machine Learning, Media Computing Group, PCA, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, SVM, Wiss. Beitrag, best, best-bhorsak, pattern recognition, peer-reviewed}, } @inproceedings{slijepcevic_usefullness_2019, address = {Vienna, Austria}, title = {On the usefullness of statistical parameter mapping for feature selection in automated gait classification}, booktitle = {Book of {Abstracts} of the 25th {Conference} of the {European} {Society} of {Biomechanics} ({ESB})}, author = {Slijepcevic, Djordje and Raberger, Anna-Maria and Zeppelzauer, Matthias and Dumphart, Bernhard and Breiteneder, Christian and Horsak, Brian}, year = {2019}, note = {Projekt: IntelliGait Projekt: DHLab}, keywords = {Biomechanics, Center for Artificial Intelligence, Center for Digital Health and Social Innovation, DHLab, Digital Health, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Gait Analysis, Gait Classification, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Machine Learning, Media Computing Group, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Vortrag, Wiss. Beitrag, best, peer-reviewed, ⛔ No DOI found}, pages = {1}, } @inproceedings{horsak_klinische_2022, address = {Krems, Austria}, title = {Die klinische {Ganganalyse}: ein „{Werkzeugkasten}“ zur objektiven {Analyse} der menschlichen {Bewegung} ({Invited} {Talk})}, author = {Horsak, Brian}, year = {2022}, keywords = {Biofeedback, Biomechanics, Center for Digital Health and Social Innovation, Department Gesundheit, Gait Analysis, Gait Classification, Institut für Gesundheitswissenschaften, Machine Learning, Musculoskeletal Simulations, SP CDHSI Motor Rehabilitation, Virtual Reality, Vortrag, Wiss. Beitrag, best, ⛔ No DOI found}, } @article{horsak_overground_2021, title = {Overground {Walking} in a {Fully} {Immersive} {Virtual} {Reality}: {A} {Comprehensive} {Study} on the {Effects} on {Full}-{Body} {Walking} {Biomechanics}}, volume = {9}, copyright = {CC-BY}, issn = {2296-4185}, shorttitle = {Overground {Walking} in a {Fully} {Immersive} {Virtual} {Reality}}, url = {https://www.frontiersin.org/article/10.3389/fbioe.2021.780314}, doi = {https://doi.org/10.3389/fbioe.2021.780314}, abstract = {Virtual reality (VR) is an emerging technology offering tremendous opportunities to aid gait rehabilitation. To this date, real walking with users immersed in virtual environments with head-mounted displays (HMDs) is either possible with treadmills or room-scale (overground) VR setups. Especially for the latter, there is a growing interest in applications for interactive gait training as they could allow for more self-paced and natural walking. This study investigated if walking in an overground VR environment has relevant effects on 3D gait biomechanics. A convenience sample of 21 healthy individuals underwent standard 3D gait analysis during four randomly assigned walking conditions: the real laboratory (RLab), a virtual laboratory resembling the real world (VRLab), a small version of the VRlab (VRLab−), and a version which is twice as long as the VRlab (VRLab+). To immerse the participants in the virtual environment we used a VR-HMD, which was operated wireless and calibrated in a way that the virtual labs would match the real-world. Walking speed and a single measure of gait kinematic variability (GaitSD) served as primary outcomes next to standard spatio-temporal parameters, their coefficients of variant (CV\%), kinematics, and kinetics. Briefly described, participants demonstrated a slower walking pattern (−0.09 ± 0.06 m/s) and small accompanying kinematic and kinetic changes. Participants also showed a markedly increased gait variability in lower extremity gait kinematics and spatio-temporal parameters. No differences were found between walking in VRLab+ vs. VRLab−. Most of the kinematic and kinetic differences were too small to be regarded as relevant, but increased kinematic variability (+57\%) along with increased percent double support time (+4\%), and increased step width variability (+38\%) indicate gait adaptions toward a more conservative or cautious gait due to instability induced by the VR environment. We suggest considering these effects in the design of VR-based overground training devices. Our study lays the foundation for upcoming developments in the field of VR-assisted gait rehabilitation as it describes how VR in overground walking scenarios impacts our gait pattern. This information is of high relevance when one wants to develop purposeful rehabilitation tools.}, urldate = {2021-12-03}, journal = {Frontiers in Bioengineering and Biotechnology}, author = {Horsak, Brian and Simonlehner, Mark and Schöffer, Lucas and Dumphart, Bernhard and Jalaeefar, Arian and Husinsky, Matthias}, year = {2021}, keywords = {Biofeedback, Biomechanics, Center for Digital Health and Social Innovation, Department Gesundheit, Forschungsgruppe Digital Technologies, Forschungsgruppe Media Computing, Gait Analysis, Institut für Gesundheitswissenschaften, SP CDHSI Motor Rehabilitation, Virtual Reality, Wiss. Beitrag, best, peer-reviewed}, pages = {1236}, } @inproceedings{iber_mind_2021, title = {Mind the {Steps}: {Towards} {Auditory} {Feedback} in {Tele}-{Rehabilitation} {Based} on {Automated} {Gait} {Classification}}, doi = {10/gnt2tc}, abstract = {We describe a proof-of-concept for the implementation of a mobile auditory biofeedback system based on automated classification of functional gait disorders. The classification is embedded in a sensor-instrumented insole and is based on ground reaction forces (GRFs). GRF data have been successfully used for the classification of gait patterns into clinically relevant classes and are frequently used in clinical practice to quantitatively describe human motion. A feed-forward neural network that was implemented on the firmware of the insole is used to estimate the GRFs using pressure and accelerator data. Compared to GRF measurements obtained from force plates, the estimated GRFs performed highly accurately. To distinguish between physiological gait and gait disorders, we trained and evaluated a support vector machine with labeled data from a publicly accessible database. The automated gait classification was sonified for auditory feedback. The high potential of the implemented auditory feedback for preventive and supportive applications in physical therapy, such as supervised therapy settings and tele-rehabilitation, was highlighted by a semi- structured interview with two experts.}, booktitle = {In {Proceedings} of the 16th {International} {Audio} {Mostly} {Conference} ({AM}’21)}, publisher = {ACM}, author = {Iber, Michael and Dumphart, Bernhard and Oliveira, Victor A. de. J. and Ferstl, Stefan and Reis, Joschua and Slijepcevic, Djordje and Heller, Mario and Raberger, Anna-Maria and Horsak, Brian}, year = {2021}, note = {Projekt: Sonigait II}, keywords = {Artificial Intelligence, Biofeedback, Biomechanics, CDHI, Digital Health, Forschungsgruppe Media Computing, Gait Analysis, Human-computer interaction, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Motor rehabilitation, Vortrag, Wiss. Beitrag, best, best-lbiber, peer-reviewed}, } @article{horsak_effects_2019, title = {Effects of a lower extremity exercise program on gait biomechanics and clinical outcomes in children and adolescents with obesity: {A} randomized controlled trial}, volume = {70}, issn = {0966-6362}, shorttitle = {Effects of a lower extremity exercise program on gait biomechanics and clinical outcomes in children and adolescents with obesity}, url = {http://www.sciencedirect.com/science/article/pii/S0966636218313341}, doi = {10/gh38bj}, number = {122-129}, urldate = {2019-03-04}, journal = {Gait \& Posture}, author = {Horsak, Brian and Schwab, Caterine and Baca, Arnold and Greber-Platzer, Susanne and Kreissl, Alexandra and Nehrer, Stefan and Keilani, Mohammad and Crevenna, Richard and Kranzl, Andreas and Wondrasch, Barbara}, year = {2019}, note = {Projekt: Childrens KNEEs Study}, keywords = {Biofeedback, Biomechanics, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, DHLab, Gait Analysis, Institut für Gesundheitswissenschaften, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, peer-reviewed}, } @inproceedings{zulkarnain_development_2022, address = {Budapest, Hungary}, title = {Development of a social inclusive immersive virtual reality exergame to promote physical activity}, url = {http://www.foodconf.hu/poster/P4000/68.pdf}, booktitle = {Book of {Proceedings} {FOODCONF}}, publisher = {MATE, Buda Campus}, author = {Zulkarnain, Abdul Hannan Bin and Totorean, Alin and Gere, Attila and Cruz, Eduardo and Horsak, Brian and Lancere, Linda and Schöffer, Lucas and Simonlehner, Mark and Crișan-Vida, Mihaela and Fernandes, Rita and Sterckx, Yasmine}, year = {2022}, keywords = {Biofeedback, Biomechanics, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, Department Gesundheit, Gait Analysis, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Publikationstyp Poster, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Virtual Reality, Vortrag, Wiss. Beitrag, best, peer-reviewed, ⛔ No DOI found}, } @inproceedings{guggenberger_influence_2022, series = {{ESMAC} 2022 {Abstracts}}, title = {The influence of different walking strategies on patellofemoral and tibiofemoral contact forces in individuals with patellofemoral instability}, volume = {97}, url = {https://www.sciencedirect.com/science/article/pii/S0966636222002508}, doi = {10.1016/j.gaitpost.2022.07.052}, language = {en}, urldate = {2022-10-04}, booktitle = {Gait \& {Posture}}, author = {Guggenberger, B. and Horsak, B. and Habersack, A. and Smith, C. and Svehlik, M. and Kainz, H.}, month = sep, year = {2022}, keywords = {Biofeedback, Biomechanics, Center for Digital Health and Social Innovation, Department Gesundheit, Gait Analysis, Institut für Gesundheitswissenschaften, Musculoskeletal Simulations, SP CDHSI Motor Rehabilitation, Vortrag, Wiss. Beitrag, best, best-bhorsak, peer-reviewed}, pages = {S68--S69}, } @inproceedings{dumphart_validity_2021, address = {Virtual Meeting}, title = {Validity and reliability of a mobile insole to measure vertical ground reaction force during walking}, author = {Dumphart, Bernhard and Schimakno, Markus and Nöstlinger, Stefan and Iber, Michael and Horsak, Brian and Heller, Mario}, year = {2021}, note = {Projekt: DHLab Project: SONIGAIT II}, keywords = {Biofeedback, Biomechanics, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, Department Gesundheit, Gait Analysis, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Vortrag, Wiss. Beitrag, best, peer-reviewed, ⛔ No DOI found}, } @inproceedings{horsak_walking_2022, address = {Taipei, Taiwan}, title = {Walking overground in a room-scale {Virtual} {Reality} {Environment}: a motor control perspective}, author = {Horsak, Brian and Simonlehner, Mark and Schöffer, Lucas and Dumphart, Bernhard and Jalaeefar, Arian and Husinsky, Matthias and Siragy, Tarique}, year = {2022}, keywords = {Biofeedback, Biomechanics, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, Department Gesundheit, Gait Analysis, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Virtual Reality, Vortrag, Wiss. Beitrag, best, peer-reviewed, ⛔ No DOI found}, } @inproceedings{horsak_clinical_2022, address = {Berlin, Germany}, title = {Clinical {Gait} {Analysis}: {A} {Toolbox} to study {Dynamic} {Joint} {Loading} ({Invited} {Talk})}, author = {Horsak, Brian}, year = {2022}, keywords = {3D Free Hand Ultrasound, Biofeedback, Biomechanics, Center for Digital Health and Social Innovation, Department Gesundheit, Gait Analysis, Gait Classification, Institut für Gesundheitswissenschaften, Machine Learning, Musculoskeletal Simulations, SP CDHSI Motor Rehabilitation, Virtual Reality, Vortrag, Wiss. Beitrag, best, ⛔ No DOI found}, } @article{horsak_3d_2021, title = {{3D} free-hand ultrasound to register anatomical landmarks at the pelvis and localize the hip joint center in lean and obese individuals}, volume = {11}, copyright = {Open Access}, issn = {2045-2322}, url = {https://www.nature.com/articles/s41598-021-89763-7}, doi = {https://doi.org/10.1038/s41598-021-89763-7}, abstract = {3D free-hand ultrasound (3DFUS) is becoming increasingly popular to assist clinical gait analysis because it is cost- and time-efficient and does not expose participants to radiation. The aim of this study was to evaluate its reliability in localizing the anterior superior iliac spine (ASIS) at the pelvis and the hip joint centers (HJC). Additionally, we evaluated its accuracy to get a rough estimation of the potential to use of 3DFUS to segment bony surface. This could offer potential to register medical images to motion capture data in future. To evaluate reliability, a test–retest study was conducted in 16 lean and 19 obese individuals. The locations of the ASIS were determined by manual marker placement (MMP), an instrumented pointer technique (IPT), and with 3DFUS. The HJC location was also determined with 3DFUS. To quantify reliability, intraclass correlation coefficients (ICCs), the standard error of measurement (SEm), among other statistical parameters, were calculated for the identified locations between the test and retest. To assess accuracy, the surface of a human plastic pelvic phantom was segmented with 3DFUS in a distilled water bath in 27 trials and compared to a 3D laser scan of the pelvis. Regarding reliability, the MMP, but especially the IPT showed high reliability in lean (SEm: 2–3 mm) and reduced reliability in obese individuals (SEm: 6–15 mm). Compared to MMP and IPT, 3DFUS presented lower reliability in the lean group (SEm: 2–4 mm vs. 2–8 mm, respectively) but slightly better values in the obese group (SEm: 7–11 mm vs. 6–16 mm, respectively). Correlations between test–retest reliability and torso body fat mass (\% of body mass) indicated a moderate to strong relationship for MMP and IPT but only a weak correlation for the 3DFUS approach. The water-bath experiments indicated an acceptable level of 3.5 (1.7) mm of accuracy for 3DFUS in segmenting bone surface. Despite some difficulties with single trials, our data give further rise to the idea that 3DFUS could serve as a promising tool in future to inform marker placement and hip joint center location, especially in groups with higher amount of body fat.}, language = {en}, number = {1}, urldate = {2021-05-20}, journal = {Scientific Reports}, author = {Horsak, Brian and Schwab, Caterine and Durstberger, Sebastian and Thajer, Alexandra and Greber-Platzer, Susanne and Kainz, Hans and Jonkers, Ilse and Kranzl, Andreas}, year = {2021}, note = {Projekt: HIPstar}, keywords = {3D Free Hand Ultrasound, Biomechanics, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, DHLab, Department Gesundheit, Gait Analysis, Institut für Gesundheitswissenschaften, Open Access, SP CDHSI Motor Rehabilitation, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, peer-reviewed}, pages = {10650}, } @inproceedings{gorgas_short-term_2016, address = {Segovia, Spain}, series = {Biosystems \& {Biorobotics}}, title = {Short-{Term} {Effects} of {Real}-{Time} {Auditory} {Display} ({Sonification}) on {Gait} {Parameters} in {People} with {Parkinsons}’ {Disease}—{A} {Pilot} {Study}}, copyright = {©2017 Springer International Publishing AG}, isbn = {978-3-319-46668-2 978-3-319-46669-9}, url = {http://link.springer.com/chapter/10.1007/978-3-319-46669-9_139}, doi = {10/gnt2th}, abstract = {Parkinson’s disease PD patients frequently experience gait impairments. Auditory input has been shown to be an effective measure to benefit critical gait aspects related to the timing and initiation of movement. An instrumented shoe insole device for real-time sonification of gait has been developed for rehabilitation purposes (SONIGait). The objective of the present pilot study was to gain insight about possible effects of SONIGait on gait parameters in PD patients. Five PD patients participated in this pilot study and completed three series of trials with and without sonification. Spatio-temporal gait parameters were recorded during these trials. The outcomes revealed an increase in walking velocity and cadence along with other gait parameters between pre- and posttest. These data indicate that sonification affects gait parameters and fosters (short-term) learning effects in PD patients. Thus, SONIGait may be a suitable measure to promote gait rehabilitation in PD in the future.}, language = {en}, urldate = {2016-10-19}, booktitle = {Converging {Clinical} and {Engineering} {Research} on {Neurorehabilitation} {II}}, publisher = {Springer International Publishing}, author = {Gorgas, Anna-Maria and Schön, Lena and Dlapka, Ronald and Doppler, Jakob and Iber, Michael and Gradl, Christian and Kiselka, Anita and Siragy, Tarique and Horsak, Brian}, editor = {Ibáñez, Jaime and González-Vargas, José and Azorín, José María and Akay, Metin and Pons, José Luis}, year = {2016}, note = {Projekt: CARMA Projekt: DHLab}, keywords = {Biofeedback, Biomechanics, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, DHLab, Department Gesundheit, Department Technologie, Forschungsgruppe Digital Technologies, Gait Analysis, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, Publikationstyp Vortrag, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, interdisziplinär, peer-reviewed, project\_carma, project\_sonigait}, pages = {855--859}, } @misc{fischer_auditory_2016, address = {Segovia, Spain}, title = {An {Auditory} {Feedback} {System} in {Use} with {People} {Aged} +50 {Years}: {Compliance} and {Modifications} in {Gait} {Pattern}}, abstract = {Aging leads to gait impairments, which increases the risk for falls. In this study the impact of the auditory feedback system SONIGait on gait parameters in elderly persons was investigated. Twenty-one participants walked at self-selected speed with four variations of real-time auditory feedback of their plantar pressure. Repeated measures ANOVA was utilized to determine changes in time-distance parameters between walking without feedback and four feedback variations. After walking, they completed a questionnaire about their appraisal of the SONIGait system and the four different feedback modalities. There was a significant reduction in gait velocity (0.142 ± 0.04 m/s; p {\textless} 0.001) and prolongation of step time (0.02 ± 0.005 s; p {\textless} 0.001) during walking with SONIGait. No significant preference for any of the feedback variations was observed. Most participants evaluated the system SONIGait positively. Thus, real-time auditory feedback may be used in gait rehabilitation and may support an older person’s gait stability.}, author = {Fischer, Theresa and Kiselka, Anita}, collaborator = {Dlapka, Ronald and Doppler, Jakob and Iber, Michael and Gradl, Christian and Gorgas, Anna-Maria and Siragy, Tarique and Horsak, Brian}, year = {2016}, note = {Projekt: CARMA Projekt: DHLab}, keywords = {Biofeedback, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, DHLab, Forschungsgruppe Digital Technologies, Gait Analysis, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, peer-reviewed}, } @article{horsak_sonigait_2016, title = {{SONIGait}: a wireless instrumented insole device for real-time sonification of gait}, volume = {10}, issn = {1783-7677, 1783-8738}, shorttitle = {{SONIGait}}, url = {http://link.springer.com/10.1007/s12193-016-0216-9}, doi = {10/gh38bg}, language = {en}, number = {3}, urldate = {2016-04-26}, journal = {Journal on Multimodal User Interfaces}, author = {Horsak, Brian and Dlapka, Ronald and Iber, Michael and Gorgas, Anna-Maria and Kiselka, Anita and Gradl, Christian and Siragy, Tarique and Doppler, Jakob}, year = {2016}, note = {Projekt: CARMA Projekt: SoniGait Projekt: DHLab}, keywords = {Biofeedback, Biomechanics, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, DHLab, Forschungsgruppe Digital Technologies, Gait Analysis, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, peer-reviewed}, pages = {195--206}, } @inproceedings{schwab_anwendung_2020, address = {München, Deutschland}, title = {Die {Anwendung} von {3D}-{Freihand}-{Ultraschall} für die digitale {Rekonstruktion} von anatomischen {Strukturen} in der {3D} {Ganganalyse}: erste {Ergebnisse} eines laufenden {Projekts}}, booktitle = {Abstractband des 3. {GAMMA} {Kongress}}, author = {Schwab, Caterine and Durstberger, Sebastian and Kranzl, Andreas and Horsak, Brian}, year = {2020}, note = {Projekt: HIPstar Projekt: DHLab}, keywords = {3D Free Hand Ultrasound, Biomechanics, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, Department Gesundheit, Gait Analysis, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Vortrag, Wiss. Beitrag, best, best-bhorsak, peer-reviewed, ⛔ No DOI found}, } @inproceedings{durstberger_evaluating_2020, address = {Virtual Meeting}, title = {Evaluating {3D} free-hand ultrasound as an alternative approach to register anatomical landmarks: {A} test-retest study in lean and overweight participants}, shorttitle = {Evaluating {3D} free-hand ultrasound as an alternative approach to register anatomical landmarks}, doi = {10/gnt2tf}, language = {en}, urldate = {2020-09-14}, booktitle = {Gait \& {Posture}}, author = {Durstberger, S. and Schwab, C. and Simonlehner, M. and Kainz, H. and Kranzl, A. and Horsak, B.}, year = {2020}, note = {Projekt: HIPstar}, keywords = {3D Free Hand Ultrasound, Biomechanics, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, DHLab, Department Gesundheit, Digital Health, Eintrag überprüfen, Gait Analysis, Green OA, Institut für Gesundheitswissenschaften, Institutional Access, Poster, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, peer-reviewed}, } @inproceedings{siragy_framework_2016, address = {Wien, Österreich}, title = {Framework for {Real}-time {Auditory} {Display} of {Plantar} {Pressure} during {Walking}}, booktitle = {Tagungsband des 10. {Forschungsforum} der Österreichischen {Fachhochschulen}}, author = {Siragy, Tarique and Doppler, Jakob and Gorgas, Anna-Maria and Dlapka, Ronald and Iber, Michael and Kiselka, Anita and Gradl, Christian and Horsak, Brian}, year = {2016}, note = {Projekt: CARMA Projekt: DHLab}, keywords = {Biofeedback, Biomechanics, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, DHLab, Department Gesundheit und Soziales, Department Medien und Digitale Technologien, Department Technologie, Forschungsgruppe Digital Technologies, Gait Analysis, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, Publikationstyp Vortrag, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, interdisziplinär, peer-reviewed, project\_carma, project\_sonigait, ⛔ No DOI found}, } @inproceedings{schwab_evaluating_2020, address = {Virtual Meeting}, title = {Evaluating the accuracy of a {3D} free-hand ultrasound technique for bone segmentation in clinical gait analysis}, url = {http://www.sciencedirect.com/science/article/pii/S0966636220304513}, doi = {10.1016/j.gaitpost.2020.08.064}, language = {en}, urldate = {2020-09-14}, booktitle = {Gait \& {Posture}}, author = {Schwab, C. and Durstberger, S. and Kranzl, A. and Simonlehner, M. and Kainz, H. and Horsak, B.}, year = {2020}, note = {Projekt: HIPstar}, keywords = {3D Free Hand Ultrasound, Biomechanics, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, DHLab, Department Gesundheit, Digital Health, Eintrag überprüfen, Gait Analysis, Institut für Gesundheitswissenschaften, Poster, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, peer-reviewed}, } @inproceedings{schwab_accuracy_2021, series = {{ESMAC} 2021 {Abstracts}}, title = {Accuracy of 3-dimensional freehand ultrasound to estimate anatomical landmarks in children and adolescents with obesity}, volume = {90}, url = {https://www.sciencedirect.com/science/article/pii/S096663622100429X}, doi = {https://doi.org/10.1016/j.gaitpost.2021.09.120}, language = {en}, urldate = {2021-10-15}, booktitle = {Gait \& {Posture}}, author = {Schwab, C. and Durstberger, S. and Kainz, H. and Baca, A. and Thajer, A. and Greber-Platzer, S. and Ilse, J. and Horsak, B. and Kranzl, A.}, month = oct, year = {2021}, note = {Projekt: HIPstar}, keywords = {3D Free Hand Ultrasound, Biomechanics, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, Department Gesundheit, Gait Analysis, Institut für Gesundheitswissenschaften, SP CDHSI Motor Rehabilitation, Wiss. Beitrag, best, peer-reviewed}, pages = {232--233}, } @inproceedings{horsak_applicability_2020, address = {Virtual Meeting}, title = {Applicability and usability of an immersive virtual reality-based balance control exergame for prosthetic users: {A} pilot study with healthy individuals}, shorttitle = {Applicability and usability of an immersive virtual reality-based balance control exergame for prosthetic users}, url = {http://www.sciencedirect.com/science/article/pii/S0966636220303556}, doi = {10/gnkdht}, language = {en}, urldate = {2020-09-14}, booktitle = {Gait \& {Posture}}, author = {Horsak, B. and Simonlehner, M. and Schöffer, L. and Maureder, J. and Schwab, C. and Raberger, A. M. and Zeller, M. and Husinsky, M.}, year = {2020}, note = {Projekt: ReMoCap-Lab Projekt: AVATAR}, keywords = {Biomechanics, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, DHLab, Department Gesundheit, Digital Health, Gait Analysis, Immersive Media (AR, VR, 360°), Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Institutional Access, Poster, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Virtual Reality, Wiss. Beitrag, best, best-bhorsak, peer-reviewed}, } @article{horsak_overground_2021, series = {{ESMAC} 2021 {Abstracts}}, title = {Overground walking in a fully immersive {Virtual} {Reality}: {Preliminary} results of a comprehensive study on the effects on walking biomechanics}, volume = {90}, copyright = {Open Access}, issn = {0966-6362}, shorttitle = {Overground walking in a fully immersive {Virtual} {Reality}}, url = {https://www.sciencedirect.com/science/article/pii/S096663622100360X}, doi = {https://doi.org/10.3389/fbioe.2021.780314}, language = {en}, urldate = {2021-10-15}, journal = {Gait \& Posture}, author = {Horsak, B. and Simonlehner, M. and Schöffer, L. and Dumphart, B. and Jalaeefar, A. and Husinsky, M.}, month = oct, year = {2021}, note = {Projekt: ReMoCap-Lab}, keywords = {Biomechanics, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, Department Gesundheit, Gait Analysis, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, SP CDHSI Motor Rehabilitation, Virtual Reality, Wiss. Beitrag, best, peer-reviewed}, pages = {100--101}, } @article{thajer_comparison_2021, title = {Comparison of {Bioelectrical} {Impedance}-{Based} {Methods} on {Body} {Composition} in {Young} {Patients} with {Obesity}}, volume = {8}, copyright = {CC-BY}, url = {https://www.mdpi.com/2227-9067/8/4/295}, doi = {https://doi.org/10.3390/children8040295}, language = {en}, number = {4}, urldate = {2021-04-12}, journal = {Children}, author = {Thajer, Alexandra and Skacel, Gabriele and Truschner, Katharina and Jorda, Anselm and Vasek, Martin and Horsak, Brian and Strempfl, Johanna and Kautzky-Willer, Alexandra and Kainberger, Franz and Greber-Platzer, Susanne}, month = apr, year = {2021}, note = {Projekt: Childrens KNEEs Study}, keywords = {Biomechanics, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, DHLab, Department Gesundheit, Gait Analysis, Institut für Gesundheitswissenschaften, Open Access, SP CDHSI Motor Rehabilitation, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, peer-reviewed}, pages = {295}, } @inproceedings{horsak_patella-femoral_2022, series = {{ESMAC} 2022 {Abstracts}}, title = {Patella-femoral joint loading during the modified {Star} {Excursion} {Balance} {Test}: {Preliminary} results of an extensive simulation study}, volume = {97}, shorttitle = {Patella-femoral joint loading during the modified {Star} {Excursion} {Balance} {Test}}, url = {https://www.sciencedirect.com/science/article/pii/S0966636222002119}, doi = {10.1016/j.gaitpost.2022.07.013}, language = {en}, urldate = {2022-10-04}, booktitle = {Gait \& {Posture}}, author = {Horsak, B. and Simonlehner, M. and Dumphart, B. and Kainz, H. and Killen, B. and Jonkers, I.}, month = sep, year = {2022}, keywords = {Biomechanics, Center for Digital Health and Social Innovation, Department Gesundheit, Gait Analysis, Institut für Gesundheitswissenschaften, Musculoskeletal Simulations, SP CDHSI Motor Rehabilitation, Vortrag, Wiss. Beitrag, best, best-bhorsak, peer-reviewed}, pages = {S5--S6}, } @inproceedings{horsak_machine_2022, address = {Dortmund, Germany}, title = {From machine learning to virtual reality: application examples of emerging digital trends in (clinical) gait analysis and rehabilitation ({Invited} {Talk})}, author = {Horsak, Brian}, year = {2022}, keywords = {Biomechanics, Center for Digital Health and Social Innovation, Department Gesundheit, Gait Analysis, Gait Classification, Institut für Gesundheitswissenschaften, Machine Learning, SP CDHSI Motor Rehabilitation, Virtual Reality, Vortrag, Wiss. Beitrag, best, ⛔ No DOI found}, } @article{horsak_effects_2015, title = {The effects of a strength and neuromuscular exercise programme for the lower extremity on knee load, pain and function in obese children and adolescents: study protocol for a randomised controlled trial}, volume = {16}, issn = {1745-6215}, shorttitle = {The effects of a strength and neuromuscular exercise programme for the lower extremity on knee load, pain and function in obese children and adolescents}, doi = {10/ghf82d}, abstract = {BACKGROUND: Childhood obesity is one of the most critical and accelerating health challenges throughout the world. It is a major risk factor for developing varus/valgus misalignments of the knee joint. The combination of misalignment at the knee and excess body mass may result in increased joint stresses and damage to articular cartilage. A training programme, which aims at developing a more neutral alignment of the trunk and lower limbs during movement tasks may be able to reduce knee loading during locomotion. Despite the large number of guidelines for muscle strength training and neuromuscular exercises that exist, most are not specifically designed to target the obese children and adolescent demographic. Therefore, the aim of this study is to evaluate a training programme which combines strength and neuromuscular exercises specifically designed to the needs and limitations of obese children and adolescents and analyse the effects of the training programme from a biomechanical and clinical point of view. METHODS/DESIGN: A single assessor-blinded, pre-test and post-test randomised controlled trial, with one control and one intervention group will be conducted with 48 boys and girls aged between 10 and 18 years. Intervention group participants will receive a 12-week neuromuscular and quadriceps/hip strength training programme. Three-dimensional (3D) gait analyses during level walking and stair climbing will be performed at baseline and follow-up sessions. The primary outcome parameters for this study will be the overall peak external frontal knee moment and impulse during walking. Secondary outcomes include the subscales of the Knee injury and Osteoarthritis Outcome Score (KOOS), frontal and sagittal kinematics and kinetics for the lower extremities during walking and stair climbing, ratings of change in knee-related well-being, pain and function and adherence to the training programme. In addition, the training programme will be evaulated from a clinical and health status perspective by including the following analyses: cardiopulmonary testing to quantify aerobic fitness effects, anthropometric measures, nutritional status and psychological status to characterise the study sample. DISCUSSION: The findings will help to determine whether a neuromuscular and strength training exercise programme for the obese children population can reduce joint loading during locomotion, and thereby decrease the possible risk of developing degenerative joint diseases later in adulthood. TRIAL REGISTRATION: ClinicalTrials NCT02545764 , Date of registration: 24 September 2015.}, language = {eng}, journal = {Trials}, author = {Horsak, Brian and Artner, David and Baca, Arnold and Pobatschnig, Barbara and Greber-Platzer, Susanne and Nehrer, Stefan and Wondrasch, Barbara}, year = {2015}, note = {Projekt: Childrens KNEEs Study Projekt: DHLab}, keywords = {Biomechanics, Center for Digital Health Innovation, DHLab, Department Gesundheit und Soziales, Gait Analysis, Institut für Gesundheitswissenschaften, Publikationstyp Schriftpublikation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, peer-reviewed, project\_childrensknees}, pages = {586}, } @inproceedings{iber_pilotstudie_2015, address = {FH St. Pölten}, title = {Pilotstudie zur sonifikationsgestützten {Ganganalyse}}, isbn = {987-3-86488-090-2}, abstract = {Verletzungs- oder krankheitsbedingte Beeinträchtigungen des Ganges stellen die physiotherapeutische Behandlung vor große Herausforderungen. Aktuelle Technologien erlauben heute die Entwicklung preiswerter tragbarer Ganganalysesysteme, die den gewohnten Bewegungsablauf nicht einschränken und auch außerhalb eines Labors verwendet werden können. Über eine diagnostische Anwendung hinaus können sie auch den motorischen Lernprozess in der physiotherapeutischen Behandlung unterstützen. Eine akustische Darstellung des Abrollverhaltens erlaubt PatientInnen mögliche Abweichungen wahrzunehmen und ermöglicht folglich Eigenkontrolle und Eigenständigkeit beim Üben. Auf Grundlage dieser Rahmenbedingungen wurde ein Hardware-Prototyp bestehend aus einem Paar mit Sensoren ausgestatteter Schuhsohlen und einem Mikroprozessor mit BluetoothLE entwickelt, der Bewegungsdaten in Echtzeit an ein handelsübliches mobiles Endgerät schickt. Auf diesem werden die parametrisierten Daten in Echtzeit sonifiziert, d.h. als Klänge synthetisiert, und über Kopfhörer der PatientIn zugespielt. Dadurch erhält die PatientIn eine zusätzliche Rückmeldung zu seinem Gangmuster. In einer Pilotstudie wurden Sonifikationsvarianten entwickelt und nach einer Vorauswahl durch PhysiotherapeutInnen durch eine Gruppe gesunder ProbandInnen evaluiert. Darüber hinaus wurde der objektive Einfluss der Sonifikationen auf das Gangmuster anhand von Bewegungsdaten, die mit Druckmessplatten erhobenen wurden, verglichen.}, booktitle = {Forum {Medientechnik} - {Next} {Generation}, {New} {Ideas}}, publisher = {Verlag Werner Hülsbusch, Fachverlag für Medientechnik und -wirtschaft}, author = {Iber, Michael and Horsak, Brian and Bauer, Karin and Kiselka, Anita and Gorgas, Anna-Maria and Dlapka, Ronald and Doppler, Jakob}, year = {2015}, note = {Projekt: CARMA Projekt: DHLab}, keywords = {2015, Biomechanics, Center for Digital Health Innovation, DHLab, Department Gesundheit und Soziales, Department Medien und Digitale Technologien, Forschungsgruppe Digital Technologies, Forschungsgruppe Media Computing, Gait Analysis, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, Publikationstyp Vortrag, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, peer-reviewed, project\_carma, project\_sonigait}, pages = {51--68}, } @article{horsak_muscle_2015, title = {Muscle co-contraction around the knee when walking with unstable shoes}, issn = {1873-5711}, doi = {10/f6xvzs}, abstract = {Walking with unstable shoes has been discussed to decrease joint loading. Typical estimates of joint loading using an inverse dynamic approach only account for net joint moments, not considering the potential role of muscular co-contraction. Therefore, the purpose of this study was to compare muscular co-contraction levels when walking with two different unstable shoe constructions (rocker-bottom and toning shoes) compared to walking with regular shoes. For each shoe condition, 12 healthy subjects walked with both, a regular shoe and with an unstable shoe at self-selected walking speed at a 10-m walkway. Surface EMG data of selected muscles were recorded and time normalized for calculating co-contraction indices (CCI) for opposing muscle groups. Results showed an increase of co-contraction primarily for vastii and gastrocnemius muscles for the first and second half of stance when walking with an unstable shoe construction. Therefore, when using an inverse dynamic approach to analyze joint loading differences between regular shoes and unstable shoes, one should be cautious in interpreting the data, as these methods base their estimates of joint moments upon the net joint torque.}, language = {ENG}, number = {25}, journal = {Journal of Electromyography and Kinesiology: Official Journal of the International Society of Electrophysiological Kinesiology}, author = {Horsak, Brian and Heller, Mario and Baca, Arnold}, year = {2015}, pmid = {25156445}, note = {Projekt: DHLab}, keywords = {Biomechanics, Center for Digital Health Innovation, DHLab, Department Gesundheit und Soziales, Forschungsgruppe Digital Technologies, Gait Analysis, Institut für Gesundheitswissenschaften, Publikationstyp Schriftpublikation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, best-lbheller, peer-reviewed}, pages = {175--181}, } @article{horsak_reliability_2020, title = {Reliability of walking and stair climbing kinematics in a young obese population using a standard kinematic and the {CGM2} model}, volume = {83}, issn = {0966-6362}, url = {http://www.sciencedirect.com/science/article/pii/S096663622030597X}, doi = {10/gnt2tj}, language = {en}, number = {96-99}, urldate = {2020-10-21}, journal = {Gait \& Posture}, author = {Horsak, Brian and Schwab, Caterine and Leboeuf, Fabien and Kranzl, Andreas}, year = {2020}, note = {Projekt: ReMoCap-Lab}, keywords = {Biomechanics, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, Department Gesundheit, Eintrag überprüfen, Gait Analysis, Green OA, Institut für Gesundheitswissenschaften, Open Access, Publikationstyp Schriftpublikation, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, peer-reviewed}, } @inproceedings{horsak_wireless_2015, address = {Graz, Austria}, title = {A wireless instrumented insole device for real-time sonification of gait}, isbn = {978-3-902949-01-1}, booktitle = {Proceedings of the 21st {International} {Conference} on {Auditory} {Display}}, author = {Horsak, Brian and Iber, Michael and Bauer, Karin and Kiselka, Anita and Gorgas, Anna-Maria and Dlapka, Ronald and Doppler, Jakob}, year = {2015}, note = {Projekt: CARMA Projekt: DHLab}, keywords = {Biomechanics, Center for Digital Health Innovation, DHLab, Department Gesundheit und Soziales, Department Medien und Digitale Technologien, Department Technologie, Forschungsgruppe Digital Technologies, Gait Analysis, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, Publikationstyp Vortrag, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, interdisziplinär, peer-reviewed, project\_carma, project\_sonigait}, pages = {94--101}, } @inproceedings{lampel_development_2015, address = {Istanbul, Turkey}, title = {Development of an educational software for observational gait analysis in physical therapy}, booktitle = {International {Neurology} and {Rehabilitation} {Meeting} - {Abstract} {Book}}, author = {Lampel, Kerstin and Horsak, Brian and Brauneis, Werner and Doppler, Jakob}, year = {2015}, note = {Projekt: GAIT SCORE Projekt: DHLab}, keywords = {Biomechanics, Center for Digital Health Innovation, DHC, DHLab, Department Gesundheit und Soziales, Department Technologie, Forschungsgruppe Digital Technologies, Gait Analysis, HCI, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, Publikationstyp Vortrag, SP IGW Clinical \& Healthcare Research, SP IGW Education \& Lifelong Learning for Health Professionals, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, interdisziplinär, peer-reviewed, user centered design, ⛔ No DOI found}, } @inproceedings{kiselka_demands_2015, address = {Hagenberg, Österreich}, title = {Demands on a mobile auditory feedback system for gait rehabilitation}, booktitle = {Tagungsband des 9. {Forschungsforum} der Österreichischen {Fachhochschulen}}, author = {Kiselka, Anita and Gorgas, A.-M. and Bauer, Karin and Dlapka, Ronald and Gusenbauer, Markus and Doppler, Jakob and Horsak, Brian}, year = {2015}, note = {Projekt: CARMA Projekt: DHLab}, keywords = {Biomechanics, Center for Digital Health Innovation, DHLab, Department Gesundheit und Soziales, Department Medien und Digitale Technologien, Department Technologie, Forschungsgruppe Digital Technologies, Gait Analysis, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, Publikationstyp Vortrag, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, interdisziplinär, peer-reviewed, project\_carma, project\_sonigait, ⛔ No DOI found}, } @article{horsak_trunk_2017, title = {Trunk muscle activation levels during eight stabilization exercises used in the functional kinetics concept: {A} controlled laboratory study}, volume = {30}, issn = {1878-6324}, shorttitle = {Trunk muscle activation levels during eight stabilization exercises used in the functional kinetics concept}, doi = {10/gh38bd}, abstract = {BACKGROUND: To ensure accurate implementation of stabilization exercises in rehabilitation, physical therapists need to understand the muscle activation patterns of prescribed exercise. OBJECTIVE: Compare muscle activity during eight trunk and lumbar spine stabilization exercises of the Functional Kinetics concept by Klein-Vogelbach. METHODS: A controlled laboratory study with a single-group repeated-measures design was utilized to analyze surface electromyographic intensities of 14 female and 6 male young healthy participants performing eight exercises. Data were captured from the rectus abdominis, external/internal oblique and lumbar paraspinalis. The normalized muscle activation levels (maximum voluntary isometric contraction, MVIC) for three repetitions during each exercise and muscle were analyzed. RESULTS: Side bridging (28 ± 20\%MVIC) and advanced planking (29 ± 20\%MVIC) reached the highest activity in the rectus abdominis. For external and internal oblique muscles, side bridging also showed the greatest activity of 99 ± 36\%MVIC and 52 ± 25\%MVIC, respectively. Apart from side bridging (52 ± 14\%MVIC), the supine roll-out (31 ± 12\%MVIC) and prone roll-out (31 ± 9\%MVIC) showed the greatest activity for the paraspinalis. The advanced quadruped, seated back extension and flexion on chair/Swiss Ball, prone roll-out and advanced one-leg back bridging only yielded negligible muscle activities for the rectus abdominis ({\textless} 5\%MVIC). CONCLUSION: Based on the data obtained, recommendations for selective trunk muscle activation during eight stabilization exercises were established, which will guide physical therapists in the development of exercises tailored to the needs of their patients.}, language = {eng}, number = {3}, journal = {Journal of Back and Musculoskeletal Rehabilitation}, author = {Horsak, Brian and Wunsch, Rüdiger and Bernhart, Philipp and Gorgas, Anna-Maria and Bichler, Romana and Lampel, Kerstin}, year = {2017}, note = {Projekt: DHLab}, keywords = {Biomechanics, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, DHLab, Department Gesundheit, Gait Analysis, Institut für Gesundheitswissenschaften, Publikationstyp Schriftpublikation, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, peer-reviewed}, pages = {497--508}, } @article{horsak_serratus_2017, title = {Serratus anterior and trapezius muscle activity during knee push-up plus and knee-plus exercises performed on a stable, an unstable surface and during sling-suspension}, volume = {0}, issn = {1466-853X, 1873-1600}, url = {https://www.sciencedirect.com/science/article/abs/pii/S1466853X16300700}, doi = {10/gh38bf}, abstract = {Push-up plus variations are commonly prescribed to clients during shoulder rehabilitation. The purpose of this study was to compare electromyographic (EMG) activities of the serratus anterior (SA), upper (UT), and lower trapezius (LT) during a knee push-up plus and knee-plus exercise performed on various surfaces.}, language = {English}, number = {26}, urldate = {2016-10-03}, journal = {Physical Therapy in Sport}, author = {Horsak, Brian and Kiener, Marion and Pötzelsberger, Andreas and Siragy, Tarique}, year = {2017}, note = {Projekt: DHLab}, keywords = {Biomechanics, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, DHLab, Department Gesundheit, Gait Analysis, Institut für Gesundheitswissenschaften, Publikationstyp Schriftpublikation, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, peer-reviewed}, pages = {86--92}, } @article{thajer_strength_2020, title = {A strength and neuromuscular exercise program did not improve body composition, nutrition and psychological status in children with obesity}, volume = {epub ahead of print}, copyright = {This article is protected by copyright. All rights reserved.}, issn = {1651-2227}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/apa.15498}, doi = {10/gh379v}, language = {en}, urldate = {2020-08-03}, journal = {Acta Paediatrica}, author = {Thajer, Alexandra and Truschner, Katharina and Jorda, Anselm and Skacel, Gabriele and Horsak, Brian and Greber‐Platzer, Susanne}, year = {2020}, note = {Projekt: Childrens KNEEs Study}, keywords = {Biomechanics, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, DHLab, Department Gesundheit, Gait Analysis, Green OA, Institut für Gesundheitswissenschaften, Open Access, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, peer-reviewed}, } @article{horsak_is_2018, title = {Is the reliability of {3D} kinematics of young obese participants dependent on the hip joint center localization method used?}, issn = {0966-6362, 1879-2219}, url = {http://www.gaitposture.com/article/S0966-6362(17)30934-7/fulltext}, doi = {10/gh38bh}, language = {English}, number = {59}, urldate = {2017-10-02}, journal = {Gait \& Posture}, author = {Horsak, Brian and Schwab, Caterine and Clemens, Christoph and Baca, Arnold and Greber-Platzer, Susanne and Kreissl, Alexandra and Kranzl, Andreas}, year = {2018}, note = {Projekt: Childrens KNEEs Study Projekt: DHLab}, keywords = {2018, Biomechanics, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, DHLab, Department Gesundheit, Gait Analysis, Institut für Gesundheitswissenschaften, Publikationstyp Schriftpublikation, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, peer-reviewed, project\_carma, project\_childrensknees}, pages = {65--70}, } @article{horsak_within-assessor_2017, title = {Within-assessor reliability and minimal detectable change of gait kinematics in a young obese demographic}, volume = {54}, issn = {0966-6362}, url = {http://www.sciencedirect.com/science/article/pii/S0966636217300711}, doi = {10/gh38bc}, urldate = {2017-03-06}, journal = {Gait \& Posture}, author = {Horsak, Brian and Pobatschnig, Barbara and Baca, Arnold and Greber-Platzer, Susanne and Kreissl, Alexandra and Nehrer, Stefan and Wondrasch, Barbara and Crevenna, Richard and Keilani, Mohammad and Kranzl, Andreas}, year = {2017}, note = {Projekt: Childrens KNEEs Study Projekt: DHLab}, keywords = {Biomechanics, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, DHLab, Department Gesundheit, Department Gesundheit und Soziales, Gait Analysis, Institut für Gesundheitswissenschaften, Publikationstyp Schriftpublikation, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, peer-reviewed, project\_carma, project\_childrensknees}, } @article{horsak_reliability_2018, title = {Reliability of joint kinematic calculations based on direct kinematic and inverse kinematic models in obese children}, volume = {66}, issn = {0966-6362, 1879-2219}, url = {https://www.gaitposture.com/article/S0966-6362(18)30270-4/fulltext}, doi = {10/gf4v7g}, language = {English}, number = {201-207}, urldate = {2018-09-03}, journal = {Gait \& Posture}, author = {Horsak, Brian and Pobatschnig, Barbara and Schwab, Caterine and Baca, Arnold and Kranzl, Andreas and Kainz, Hans}, year = {2018}, note = {Projekt: Childrens KNEEs Study Projekt: DHLab}, keywords = {2018, Biomechanics, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, DHLab, Department Gesundheit, Gait Analysis, Institut für Gesundheitswissenschaften, Publikationstyp Schriftpublikation, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, peer-reviewed, project\_carma, project\_childrensknees}, } @inproceedings{horsak_reliability_2019, address = {Berlin}, title = {Reliability of a mobile device to track the sagittal lumbar spine posture during activities of daily living}, author = {Horsak, Brian and Matousek, Elias and Schwärzler, Elisabeth and Schwab, Caterine}, year = {2019}, keywords = {Biomechanics, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, DHLab, Gait Analysis, Institut für Gesundheitswissenschaften, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, peer-reviewed}, } @inproceedings{horsak_intra-tester_2016, address = {Seville, Spain}, title = {Intra-tester reliability of three-dimensional kinematics in obese children and adolescents}, volume = {49}, url = {https://www.sciencedirect.com/science/article/abs/pii/S0966636216302934}, doi = {10.1016/j.gaitpost.2016.07.155}, language = {English}, urldate = {2016-09-27}, booktitle = {Gait \& {Posture}}, author = {Horsak, Brian and Pobatschnig, Barbara and Artner, David and Kranzl, Andreas and Baca, Arnold and Greber-Platzer, Susanne and Kreissl, Alexandra and Crevenna, Richard and Keilani, Mohammad and Wondrasch, Barbara}, year = {2016}, note = {Projekt: Childrens KNEEs Study Projekt: DHLab}, keywords = {Biomechanics, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, DHLab, Department Gesundheit, Gait Analysis, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, peer-reviewed, project\_carma, project\_childrensknees}, pages = {99}, } @misc{clemens_hip_2017, address = {Hannover, Germany}, type = {Poster}, title = {Hip joint center estimation methods do not affect test-retest reliability of kinematic measurements in young obese participants}, author = {Clemens, Christoph and Schwab, Caterine and Kranzl, Andreas and Wondrasch, Barbara and Baca, Arnold and Greber-Platzer, Susanne and Crevenna, Richard and Kreissl, Alexandra and Keilani, Mohammad and Horsak, Brian}, year = {2017}, note = {Projekt: Childrens KNEEs Study Projekt: DHLab}, keywords = {Center for Digital Health Innovation, Center for Digital Health and Social Innovation, DHLab, Department Gesundheit, Gait Analysis, Institut für Gesundheitswissenschaften, Publikationstyp Schriftpublikation, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, peer-reviewed, project\_carma, project\_childrensknees}, } @misc{horsak_reliabilitat_2019, address = {Berlin}, type = {Invited talk}, title = {Reliabilität von {Messergebnissen} in der {Gang}- und {Bewegungsanalyse} – {Erfahrungsbericht} zu gängigen {Maßzahlen}}, author = {Horsak, Brian}, year = {2019}, note = {Projekt: ReMoCap-Lab}, keywords = {Center for Digital Health Innovation, Center for Digital Health and Social Innovation, Gait Analysis, Institut für Gesundheitswissenschaften, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak}, } @misc{horsak_reliability_2019, address = {Amsterdam, Netherlands}, type = {Poster}, title = {Reliability of stair walking kinematics in young overweight and obese individuals}, author = {Horsak, Brian and Schwab, Caterine and Kranzl, Andreas}, year = {2019}, note = {Projekt: ReMoCap-Lab}, keywords = {Center for Digital Health Innovation, Center for Digital Health and Social Innovation, DHLab, Digital Health, Gait Analysis, Institut für Gesundheitswissenschaften, Poster, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, peer-reviewed}, } @article{kolm_diatetik-ausbildung_2016, title = {Diätetik-{Ausbildung} für das 21. {Jahrhundert} – {Beispiel} {IMPECD}: {Herausforderungen} für das {Gesundheits}-system in {Europa}: {Demographischer} {Wandel} und gesellschaftliche {Veränderungen}}, volume = {18}, number = {2}, journal = {Journal für Ernährungsmedizin}, author = {Kolm, Alexandra and Kohlenberg-Müller, Kathrin and Werkman, Andrea and Valentini, Luzia and Vanherle, Koen}, year = {2016}, note = {Projekt: IMPECD}, keywords = {2016, Department Gesundheit, Institut für Gesundheitswissenschaften, Publikationstyp Schriftpublikation, Studiengang Diätologie, best, ⛔ No DOI found}, pages = {28--29}, } @article{hartl_diatetische_2015, title = {Diätetische {Vorbereitung} für eine {Koloskopie} - {Diätetische} und medikamentöse {Aspekte} zur {Erlangung} der notwendigen {Reinheit} des {Colons}}, volume = {16}, number = {3}, journal = {Journal für Ernährungsmedizin}, author = {Hartl, Magdalena and Lassnig, Theresa and Sommerauer, Edith and Wewerka-Kreimel, Daniela and Möseneder, Jutta M. and Karner, Gabriele}, year = {2015}, keywords = {2015, Department Gesundheit, Institut für Gesundheitswissenschaften, Publikationstyp Schriftpublikation, SP IGW Clinical \& Healthcare Research, Studiengang Diätologie, best, ⛔ No DOI found}, pages = {30--31}, } @inproceedings{kiselka_perception_2014, address = {Basel}, title = {Perception of muscular effort in multiple sclerosis during dynamic elbow extension muscle activity}, booktitle = {Congress {Program}}, publisher = {CongressMed}, author = {Kiselka, Anita and Retz, Irene and Greisenberger, Andrea and Heller, Mario}, year = {2014}, keywords = {Department Gesundheit und Soziales, Forschungsgruppe Digital Technologies, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, Publikationstyp Vortrag, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, best, peer-reviewed, ⛔ No DOI found}, } @article{leitner_trendige_2018, title = {Trendige {Superfoods} – {Placebo} oder {Wundermittel}?}, volume = {33}, doi = {10/gnt2tr}, number = {2}, journal = {Ernährung und Medizin}, author = {Leitner, Gabriele}, year = {2018}, keywords = {2018, Department Gesundheit, Institut für Gesundheitswissenschaften, Publiktationstyp Schriftpublikation, SP IGW Clinical \& Healthcare Research, Studiengang Diätologie, best}, pages = {55--88}, } @article{wewerka-kreimel_elektronischer_2014, title = {Elektronischer {Diabetescoach} – {Einkaufsberater} für {Senioren} und {Seniorinnen} mit {Diabetes} mellitus {Typ} 2}, issn = {2312-2323}, language = {Deutsch}, number = {4}, journal = {Ernährung aktuell}, author = {Wewerka-Kreimel, Daniela and Pflegerl, Johannes and Karner, Gabriele}, year = {2014}, note = {Projekt: FORSCH30}, keywords = {2014, Department Gesundheit und Soziales, Institut für Gesundheitswissenschaften, Publikationstyp Schriftpublikation, SP IGW Health Promotion \& Healthy Ageing, Studiengang Diätologie, best, ⛔ No DOI found}, pages = {16--18}, } @article{pruckler_ernahrungstherapie_2013, title = {Ernährungstherapie und {Essverhalten} bei {Polyzystischem} {Ovarialsyndrom} ({PCOS}) im {Rahmen} einer {Kinderwunschbehandlung}}, volume = {7}, language = {Deutsch}, number = {3}, journal = {Journal für Gynäkologische Endokrinologie}, author = {Prückler, Judith and Leitner, Gabriele and Klein, Matthias and Gruber, I}, year = {2013}, keywords = {2013, Department Gesundheit und Soziales, Institut für Gesundheitswissenschaften, Publikationstyp Schriftpublikation, SP IGW Clinical \& Healthcare Research, Studiengang Diätologie, best, ⛔ No DOI found}, pages = {14--17}, } @article{pruckler_fh_2013, title = {{FH} {Diätologie} aktuell: {Polyzystisches} {Ovarialsyndrom} \& {Essverhalten}}, volume = {15}, number = {2}, journal = {Journal für Ernährungsmedizin}, author = {Prückler, Judith and Leitner, Gabriele and Möseneder, Jutta M. and Karner, Gabriele}, year = {2013}, keywords = {2013, Department Gesundheit und Soziales, Institut für Gesundheitswissenschaften, Publikationstyp Schriftpublikation, SP IGW Clinical \& Healthcare Research, Studiengang Diätologie, best, ⛔ No DOI found}, pages = {30--31}, } @article{vanherle_proposed_2018, title = {Proposed standard model and consistent terminology for {Monitoring} and {Outcome} {Evaluation} in different {Dietetic} {Care} settings: {Results} from the {EU}-sponsored {IMPECD} project}, volume = {37}, doi = {10/gh3727}, number = {6}, journal = {Clinical Nutrition}, author = {Vanherle, Koen and Werkman, Andrea and Baete, Eline and Barkmeijer, Alyanne and Kolm, Alexandra and Gast, Christina and Ramminger, Sara and Höld, Elisabeth and Kohlenberg-Müller, Kathrin and Ohlrich-Hahn, Sabine and Roemeling-Walters, Maaike and Wewerka-Kreimel, Daniela and Adam, Marleen and Valentini, Luzia}, year = {2018}, keywords = {2018, Department Gesundheit, Institut für Gesundheitswissenschaften, Publikationstyp Schriftpublikation, SP IGW Education \& Lifelong Learning for Health Professionals, Studiengang Diätologie, best, peer-reviewed}, pages = {2206--2216}, } @article{buchholz_prozessmodelle_2018, title = {Prozessmodelle in der {Diätetik} - {Ein} europäischer {Vergleich}}, volume = {65}, doi = {10/gh373b}, number = {9}, journal = {Ernährungs Umschau}, author = {Buchholz, Daniel and Kolm, Alexandra and Vanherle, Koen and Adam, Marleen and Baete, Eline and Gast, Christina and Heine-Bröring, Renate and Höld, Elisabeth and Kohlenberg-Müller, Kathrin and Lange, Karoline and Ohlrich-Hahn, Sabine and Rachman-Elbaum, Shelly and Roemeling-Walters, Maaike and Wewerka-Kreimel, Daniela and Werkman, Andrea}, year = {2018}, keywords = {2018, Department Gesundheit, Institut für Gesundheitswissenschaften, Publikationstyp Schriftpublikation, SP IGW Education \& Lifelong Learning for Health Professionals, Studiengang Diätologie, best, peer-reviewed}, pages = {M494--503}, } @incollection{hold_game_2015, address = {Brunn am Gebirge}, title = {Game {Based} {Learning}: {Ernährungswissen} kindgerecht vermitteln}, isbn = {978-3-99023-411-2}, booktitle = {Game {Based} {Lerning} – {Dialogorientierung} \& spielerisches {Lernen} digital und analog - {Beiträge} zum 4. {Tag} der {Lehre} an der {FH} {St}. {Pölten} am 15.10.2015}, publisher = {ikon VerlagsGesmbH}, author = {Höld, Elisabeth and Möseneder, Jutta M.}, editor = {Haag, Johann and Weißenböck, Josef and Gruber, Wolfgang and Freisleben-Teutscher, Christian F.}, year = {2015}, note = {Projekt: FORSCH42}, keywords = {2016, Center for Digital Health Innovation, Department Gesundheit, Institut für Gesundheitswissenschaften, Publikationstyp Buch, Publikationstyp Schriftpublikation, SP IGW Health Promotion \& Healthy Ageing, Studiengang Diätologie, best, best-lbkutrovatz}, pages = {101--106}, } @incollection{moseneder_evaluierung/praktische_2016, address = {Wien}, edition = {1. Aufl.}, title = {Evaluierung/praktische {Beurteilung} der durchgeführten {Ernährungstherapie}: {Wie} könnte eine praxis-bezogene {Vorgehensweise} aussehen?}, booktitle = {Qualitätsentwicklung in der {Ernährungstherapie}}, publisher = {Facultas Verlags- und Buchhandels AG}, author = {Möseneder, Jutta M.}, editor = {Schmid, Barbara}, year = {2016}, keywords = {2016, Department Gesundheit, Institut für Gesundheitswissenschaften, Publikationstyp Buch, Publikationstyp Schriftpublikation, SP IGW Clinical \& Healthcare Research, Studiengang Diätologie, best, best-lbkutrovatz}, } @article{kolm_aktuelles_2016, title = {Aktuelles aus der {Forschung}: {Ausbildung} von {Gesundheitsfachkräften} in der {Diätetik} am {Beispiel} {IMPECD}}, volume = {63}, number = {5}, journal = {Ernährungs Umschau}, author = {Kolm, Alexandra and Vanherle, Koen and Werkman, Andrea and Kohlenberg-Müller, Kathrin and Valentini, Luzia}, year = {2016}, note = {Projekt: IMPECD}, keywords = {2016, Department Gesundheit, Institut für Gesundheitswissenschaften, Publikationstyp Schriftpublikation, SP IGW Education \& Lifelong Learning for Health Professionals, Studiengang Diätologie, best, ⛔ No DOI found}, pages = {M259}, } @article{kiselka_perception_2013, title = {Perception of muscular effort in multiple sclerosis.}, volume = {32}, doi = {10/gh377b}, abstract = {BACKGROUND: Resistance exercise is effective in improving muscle strength and preventing muscle weakness in multiple sclerosis (MS) patients. Control of resistance training intensity based on perceived muscular effort is applicable to healthy individuals, yet there is no evidence of its utility for MS patients. OBJECTIVE: To compare perception of muscular effort in MS patients to healthy controls. METHODS: Based on their perception of muscular effort, twenty-five MS patients and twenty-eight controls adjusted static elbow extension tasks according to five levels on the OMNI-Resistance Exercise Scale. Elbow extension strength and muscle activity were measured via load cell dynamometer and surface electromyography (EMG) and related to each participant's maximal voluntary contraction (MVC) strength and muscle activity. Two-way analysis of variance was used to evaluate statistical significance. RESULTS: There were no statistically significant differences between MS patients and healthy controls, they produced similar relative torque values (F1 = 0.196; p {\textgreater} 0.05) and extensor muscle activities (F(2,617) = 1.556; p {\textgreater} 0.05) across all effort levels. CONCLUSION: No differences were found in the perception of muscular effort in MS patients and the age-matched control group. Future studies should explore, whether rating of perceived exertion is an effective instrument to control resistance training intensity in MS patients}, number = {2}, journal = {NeuroRehabilitation}, author = {Kiselka, Anita and Greisberger, Andrea and Heller, Mario}, year = {2013}, keywords = {Forschungsgruppe Digital Technologies, Institut für Gesundheitswissenschaften, Publikationstyp Schriftpublikation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, best, best-lbheller, peer-reviewed}, pages = {415--423}, } @article{hold_determinants_2016, title = {Determinants of complementary feeding behaviour. {Part} 2: {Influence} of migration background and socio-economic status on complementary feeding behaviour of women in {Lower} {Austria}}, volume = {63}, doi = {10/gh3764}, number = {7}, journal = {Ernährungs Umschau}, author = {Höld, Elisabeth and Hitthaler, Ariane and Ruso, Petra and Kolm, Alexandra}, year = {2016}, keywords = {2016, Department Gesundheit, Institut für Gesundheitswissenschaften, Publikationstyp Schriftpublikation, SP IGW Health Promotion \& Healthy Ageing, Studiengang Diätologie, best, peer-reviewed}, pages = {140--147}, } @article{wewerka-kreimel_elektronischer_2014, title = {Elektronischer {Berater} für den {Lebensmitteleinkauf} von {Senioren} mit {Diabetes} mellitus {Typ} 2}, doi = {10/gh3766}, number = {29}, journal = {Ernährung \& Medizin}, author = {Wewerka-Kreimel, Daniela and Lienbacher, Michael and Möseneder, Jutta M.}, year = {2014}, note = {Projekt: FORSCH30}, keywords = {2014, Department Gesundheit und Soziales, Institut für Gesundheitswissenschaften, Publikationstyp Schriftpublikation, SP IGW Clinical \& Healthcare Research, Studiengang Diätologie, best}, pages = {21--24}, } @article{wendt_zusammenhang_2013, title = {Der {Zusammenhang} von {Schlafdauer} und {Body} {Mass} {Index} bei 10-{14Jährigen} in Österreich}, volume = {60}, doi = {10/gh3763}, number = {8}, journal = {ErnaehrungsUmschau international}, author = {Wendt, Eva Maria and Pernerstorfer, Elisabeth and Möseneder, Jutta M. and Karner, Gabriele}, year = {2013}, keywords = {2013, Department Gesundheit und Soziales, Institut für Gesundheitswissenschaften, Publikationstyp Schriftpublikation, SP IGW Clinical \& Healthcare Research, Studiengang Diätologie, best, peer-reviewed}, pages = {140--144}, } @article{kolm_determinants_2016, title = {Determinants of complementary feeding behaviour. {Part} 1: {Review} of {European} literature}, volume = {63}, doi = {10/gh3762}, number = {6}, journal = {Ernährungs Umschau}, author = {Kolm, Alexandra and Hitthaler, Ariane and Ruso, Petra and Höld, Elisabeth}, year = {2016}, keywords = {2016, Center for Digital Health Innovation, Department Gesundheit, Institut für Gesundheitswissenschaften, Publikationstyp Schriftpublikation, SP IGW Health Promotion \& Healthy Ageing, Studiengang Diätologie, best, peer-reviewed}, pages = {120--126}, } @article{kolm_beeinflussung_2016, title = {Beeinflussung der arteriellen {Hypertonie} durch {Ernährung}}, volume = {41}, doi = {10/gh376x}, number = {3}, journal = {Aktuelle Ernährungsmedizin}, author = {Kolm, Alexandra and Höld, Elisabeth and Ramler, Heidemarie and Möseneder, Jutta M.}, year = {2016}, keywords = {2016, Center for Digital Health Innovation, Department Gesundheit, Institut für Gesundheitswissenschaften, Publikationstyp Schriftpublikation, SP IGW Health Promotion \& Healthy Ageing, Studiengang Diätologie, best, peer-reviewed}, pages = {196--201}, } @article{gimplinger_korperwahrnehmung_2012, title = {Körperwahrnehmung und {Diätverhalten} von {Jugendlichen}: {Realität}, {Wahrnehmung} und {Verhalten} häufig in {Widerspruch}}, volume = {14}, number = {4}, journal = {Journal für Ernährungsmedizin}, author = {Gimplinger, Silvia and Wewerka-Kreimel, Daniela and Möseneder, Jutta M. and Karner, Gabriele}, year = {2012}, keywords = {2012, Department Gesundheit und Soziales, Institut für Gesundheitswissenschaften, Publikationstyp Schriftpublikation, SP IGW Health Promotion \& Healthy Ageing, Studiengang Diätologie, best, ⛔ No DOI found}, pages = {28--29}, } @article{baumgartner_einfluss_2014, title = {Einfluss der {Ernährung} auf die {Entstehung} einer {Divertikulitis}. {Eine} retrospektive {Erhebung} der {Ernährungsweise} vor einer {Divertikulitis} bei {KrankenhauspatientInnen}}, volume = {15}, language = {Deutsch}, number = {2}, journal = {Journal für Ernährungsmedizin}, author = {Baumgartner, Maria and Wewerka-Kreimel, Daniela and Möseneder, Jutta M. and Karner, Gabriele}, year = {2014}, keywords = {2014, Department Gesundheit und Soziales, Institut für Gesundheitswissenschaften, Publikationstyp Schriftpublikation, SP IGW Clinical \& Healthcare Research, Studiengang Diätologie, best, ⛔ No DOI found}, pages = {16--18}, } @article{wewerka-kreimel_leichte_2014, title = {Leichte {Vollkost}-{Studie} 2013 - {Erhebung} der {Verträglichkeit} ausgewählter {Lebensmittel} bei unselektierten {KrankenhauspatientInnen} in Österreich}, volume = {15}, number = {1}, journal = {Journal für Ernährungsmedizin}, author = {Wewerka-Kreimel, Daniela and Höld, Elisabeth and Möseneder, Jutta M. and Karner, Gabriele}, year = {2014}, keywords = {2014, Department Gesundheit und Soziales, Institut für Gesundheitswissenschaften, Publikationstyp Schriftpublikation, SP IGW Clinical \& Healthcare Research, Studiengang Diätologie, best, ⛔ No DOI found}, pages = {14--18}, } @article{kolm_aus_2016, title = {Aus den {FHs}: {Trainieren} an virtuellen {PatientInnen} in der {Diätologie}. {Das} {EU}-{Projekt} {IMPECD}}, number = {2}, journal = {Diaetologen Journal für Ernährungsmanagement und –therapie}, author = {Kolm, Alexandra and Kohlenberg-Müller, Kathrin and Valentini, Luzia and Werkman, Andrea and Vanherle, Koen}, year = {2016}, note = {Projekt: IMPECD}, keywords = {2016, Department Gesundheit, Institut für Gesundheitswissenschaften, Publikationstyp Schriftpublikation, SP IGW Education \& Lifelong Learning for Health Professionals, Studiengang Diätologie, best, ⛔ No DOI found}, pages = {30--31}, } @article{kohlenberg-muller_nutrition_2019, title = {Nutrition assessment in process-driven, personalized dietetic intervention - {The} potential im-portance of assessing behaviour components to improve behavioural change: {Results} of the {EU}-funded {IMPECD} project}, volume = {32}, doi = {10/gh378d}, number = {8}, journal = {Clinical Nutrition ESPEN}, author = {Kohlenberg-Müller, Kathrin and Ramminger, Sara and Kolm, Alexandra and Barkmeijer, Alyanne and Gast, Christina and Adam, Marleen and Le Bruyn, Bente and Heine-Bröring, Renate and Rachman-Elbaum, Shelly and Werkman, Andrea and Vanherle, Koen and Höld, Elisabeth and Wewerka-Kreimel, Daniela and Valentini, Luzia}, year = {2019}, note = {Projekt: IMPECD}, keywords = {2019, Department Gesundheit, Institut für Gesundheitswissenschaften, SP IGW Clinical \& Healthcare Research, SP IGW Education \& Lifelong Learning for Health Professionals, SP IGW Health Promotion \& Healthy Ageing, Studiengang Diätologie, best, peer-reviewed}, pages = {125--134}, } @misc{schedlberger_diatologische_2016, address = {St. Pölten}, type = {Invited talk and workshop}, title = {Diätologische {Befundung} bei {StoffwechselpatientInnen}: {Vorstellung} des {PESR}-{Models} anhand einer {Bachelorarbeit}}, author = {Schedlberger, Lisa and Kolm, Alexandra}, month = apr, year = {2016}, keywords = {2016, Department Gesundheit, Einladung, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, Publikationstyp Vortrag, SP IGW Education \& Lifelong Learning for Health Professionals, Studiengang Diätologie, best}, } @inproceedings{judmaier_untersuchungsmethoden_2014, address = {Berlin}, title = {Untersuchungsmethoden zur {Gendersensibilität} von {Arbeitsplätzen} im {Umfeld} sicherheitskritischer {Systeme}}, booktitle = {Gender {UseT}}, publisher = {Kompetenzzentrum Technik – Diversity – Chancengleichheit e.V.}, author = {Judmaier, Peter and Pohl, Margit and Michelberger, Frank and Bichler, Romana and Erharter, Dorothea and Fränzl, Thomas and Kunz, Angelika}, year = {2014}, note = {Projekt: GenSiSys}, keywords = {Center for Sustainable Mobility, Creative Industries, Department Gesundheit, Department Technologie, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Institut für Mobilitätsforschung, Publikationstyp Schriftpublikation, SP IGW Health Promotion \& Healthy Ageing, Studiengang Physiotherapie, best, peer-reviewed, user centered design, ⛔ No DOI found}, } @article{leitner_multiple_2015, title = {Multiple {Tipps} – ein {Innoscheckprojekt} in {Kooperation} mit der {FH}-{St}.{Pölten}}, number = {44}, journal = {MS Aktuell - Das Informations-Magazin der Multiple Sklerose Gesellschaft Wien}, author = {Leitner, Gabriele and Leichum, Tanja and Simhandl, Sandra and Datzreiter, Martina and Wilfing, Nadine and Karl, Veronika and Mitterer, Christa}, month = dec, year = {2015}, keywords = {2016, Department Gesundheit, Institut für Gesundheitswissenschaften, Publikationstyp Schriftpublikation, SP IGW Clinical \& Healthcare Research, Studiengang Diätologie, best, ⛔ No DOI found}, }