Publikationen: Institut für Gesundheitswissenschaften – FHSTP

Slijepcevic, D., Horst, F., Simak, M. L., Schöllhorn, W. I., Horsak, B., & Zeppelzauer, M. (2024). Decoding Gait Signatures: Exploring Individual Patterns in Pathological Gait using Explainable AI. IEEE Access, 1–1. https://doi.org/10.1109/ACCESS.2024.3513893

Teufl, G., Simonlehner, M., Prock, K., & Horsak, B. (2024). Comparing Jump Height Estimated From A Virtual Reality Head-Mounted-Display and Force plate. ISBS Proceedings Archive, 42, 922. https://commons.nmu.edu/isbs/vol42/iss1/213/

Totorean, A., Lancere, L., Horsak, B., Simonlehner, M., Stoia, D. I., Crisan-Vida, M., Moco, D., Fernandes, R., Gere, A., Sterckx, Y., Zulkarnain, A., Gal-Nadasan, N., & Stoia, A. (2024). Heart Rate and Surface Electromyography Analysis to Assess Physical Activity Using a Virtual-Reality Exergame. In N. Herisanu & V. Marinca (Eds.), Acoustics and Vibration of Mechanical Structures—AVMS-2023 (pp. 139–146). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-48087-4_15

Bibtex

Vulpe-Grigorasi, A., Gollan, B., & Leung, V. (2024). Assessing Cognitive Load in Distraction and Task Switching: Implications for Developing Realistic Clinical XR Training. 41st Computer Graphics International Conference, CGI 2024, Geneva, Switzerland, July 1–5, 2024, Proceedings, Part II. CGI Computer Graphics International 2024, Geneva Switzerland. https://link.springer.com/book/9783031820205

Vulpe-Grigorasi, A., Kren, Z., Slijepčević, D., Schmied, R., & Leung, V. (2024). Attention performance classification based on eye tracking and machine learning. Informatics 2024 Proceedings. IEEE International Scientific Conference on Informatics, Poprad Slovakia.

Bibtex

de Jesus Oliveira, V. A., Slijepčević, D., Dumphart, B., Ferstl, S., Reis, J., Raberger, A.-M., Heller, M., Horsak, B., & Iber, M. (2023). Auditory feedback in tele-rehabilitation based on automated gait classification. Personal and Ubiquitous Computing. https://doi.org/10.1007/s00779-023-01723-2

Dumphart, B., Slijepcevic, D., Zeppelzauer, M., Kranzl, A., Unglaube, F., Baca, A., & Horsak, B. (2023). Robust deep learning-based gait event detection across various pathologies. PLOS ONE, 18(8), e0288555. https://doi.org/10.1371/journal.pone.0288555

Dumphart, B., Slijepcevic, D., Kranz, A., Zeppelzauer, M., & Horsak, B. (2023). Is it time to re-think the appropriateness of autocorrelation for gait event detection? Preliminary results of an ongoing study. Gait & Posture, 106, S50–S51. https://doi.org/10.1016/j.gaitpost.2023.07.064

Durstberger, S., Kranzl, A., & Horsak, B. (2023). 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. Gait & Posture, 100, 42–43. https://doi.org/10.1016/j.gaitpost.2022.11.056

Guggenberger, B., Horsak, B., Habersack, A., Smith, C. R., Kainz, H., & Svehlik, M. (2023). Different walking strategies impact patella cartilage pressure in individuals with patellofemoral instability. Gait & Posture, 100, 9–10. https://doi.org/10.1016/j.gaitpost.2022.11.025

Guggenberger, B., Horsak, B., Habersack, A., Smith, C., Svehlik, M., & Kainz, H. (2023). Internal lower limb rotation increases patella cartilage pressure in individuals with patellofemoral instability. Gait & Posture, 106, S71–S72. https://doi.org/10.1016/j.gaitpost.2023.07.088

Holder, J., Stief, F., van Drongelen, S., & Horsak, B. (2023). A comparative analysis of kinematic simulation results obtained by manually and automated scaled OpenSim models during walking – preliminary findings. Gait & Posture, 106, S80–S82. https://doi.org/10.1016/j.gaitpost.2023.07.099

Horsak, B., Eichmann, A., Lauer, K., Prock, K., Krondorfer, P., Siragy, T., & Dumphart, B. (2023). Concurrent validity of smartphone-based markerless motion capturing to quantify lower-limb joint kinematics in healthy and pathological gait. Journal of Biomechanics, 159, 111801. https://doi.org/10.1016/j.jbiomech.2023.111801

Horsak, B., Simonlehner, M., Dumphart, B., & Siragy, T. (2023). Overground walking while using a virtual reality head mounted display increases variability in trunk kinematics and reduces dynamic balance in young adults. Virtual Reality. https://doi.org/10.1007/s10055-023-00851-7

Horsak, B., Eichmann, A., Lauer-Maier, K., Prock, K., & Dumphart, B. (2023). Concurrent assessment of a smartphone-based markerless and marker-based motion capture system in pathological gait. Gait & Posture, 106, S79–S80. https://doi.org/10.1016/j.gaitpost.2023.07.098

Horst, F., Slijepcevic, D., Simak, M., Horsak, B., Schöllhorn, W. I., & Zeppelzauer, M. (2023). Modeling biological individuality using machine learning: A study on human gait. Computational and Structural Biotechnology Journal, 21, 3414–3423. https://doi.org/10.1016/j.csbj.2023.06.009

Bibtex

Neubauer, M., Moser, L., Neugebauer, J., Raudner, M., Wondrasch, B., Führer, M., Emprechtinger, R., Dammerer, D., Ljuhar, R., Salzlechner, C., & Nehrer, S. (2023). Artificial-Intelligence-Aided Radiographic Diagnostic of Knee Osteoarthritis Leads to a Higher Association of Clinical Findings with Diagnostic Ratings. Journal of Clinical Medicine, 12(3), 744. https://doi.org/10.3390/jcm12030744

Siragy, T., Russo, Y., Young, W., & Lamb, S. E. (2023). Comparison of over-ground and treadmill perturbations for simulation of real-world slips and trips: A systematic review. Gait & Posture, 100, 201–209. https://doi.org/10.1016/j.gaitpost.2022.12.015

Slijepcevic, D., Zeppelzauer, M., Unglaube, F., Kranzl, A., Breiteneder, C., & Horsak, B. (2023). Explainable Machine Learning in Human Gait Analysis: A Study on Children With Cerebral Palsy. IEEE Access, 11, 65906–65923. https://doi.org/10.1109/ACCESS.2023.3289986

Slijepcevic, D., Zeppelzauer, M., Unglaube, F., Kranzl, A., Breiteneder, C., & Horsak, B. (2023). Towards more transparency: The utility of Grad-CAM in tracing back deep learning based classification decisions in children with cerebral palsy. Gait & Posture, 100, 32–33. https://doi.org/10.1016/j.gaitpost.2022.11.045