Publikationen: Institut für Gesundheitswissenschaften – FHSTP

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). 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

Slijepcevic, D., Horst, F., Simak, M., Schöllhorn, W. I., Zeppelzauer, M., & Horsak, B. (2023). Towards personalized gait rehabilitation: How robustly can we identify personal gait signatures with machine learning? Gait & Posture, 106, S192–S193. https://doi.org/10.1016/j.gaitpost.2023.07.232

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

Stamm, T., Karner, G., Kutrovatz, J. M., Ritschl, V., Perkhofer, S., Tucek, G., & Weigl, R. (2023). Besonderheiten der Forschung im Gesundheitswesen. In V. Ritschl, R. Weigl, & T. Stamm (Eds.), Wissenschaftliches Arbeiten und Schreiben - Verstehen, Anwenden, Nutzen für die Praxis (2nd ed., pp. 29–53). Springer.

Bibtex

Vulpe-Grigorasi, A. (2023). Cognitive load assessment based on VR eye-tracking and biosensors. Proceedings of the 22nd International Conference on Mobile and Ubiquitous Multimedia, 589–591. https://doi.org/10.1145/3626705.3632618

Vulpe-Grigorasi, A. (2023). Multimodal machine learning for cognitive load based on eye tracking and biosensors. 2023 Symposium on Eye Tracking Research and Applications, 1–3. https://doi.org/10.1145/3588015.3589534

Guggenberger, B., Horsak, B., Habersack, A., Smith, C., Svehlik, M., & Kainz, H. (2022). The influence of different walking strategies on patellofemoral and tibiofemoral contact forces in individuals with patellofemoral instability. Gait & Posture, 97, S68–S69. https://doi.org/10.1016/j.gaitpost.2022.07.052

Horsak, B., Simonlehner, M., Dumphart, B., Kainz, H., Killen, B., & Jonkers, I. (2022). Patella-femoral joint loading during the modified Star Excursion Balance Test: Preliminary results of an extensive simulation study. Gait & Posture, 97, S5–S6. https://doi.org/10.1016/j.gaitpost.2022.07.013

Horsak, B. (2022). From machine learning to virtual reality: application examples of emerging digital trends in (clinical) gait analysis and rehabilitation (Invited Talk). 2022 Motion Capture Days, Dortmund, Germany.

Bibtex

Horsak, B., Simonlehner, M., Schöffer, L., Dumphart, B., Jalaeefar, A., Husinsky, M., & Siragy, T. (2022). Walking overground in a room-scale Virtual Reality Environment: a motor control perspective. 9th World Congress of Biomechanics, Taipei, Taiwan.

Bibtex

Horsak, B. (2022). Die klinische Ganganalyse: ein „Werkzeugkasten“ zur objektiven Analyse der menschlichen Bewegung (Invited Talk). Jahrestagung der Österreichischen Gesellschaft für Physikalische Medizin und Rehabilitation (ÖGPMR), Krems, Austria.

Bibtex

Horsak, B. (2022). Clinical Gait Analysis: A Toolbox to study Dynamic Joint Loading (Invited Talk). 16th World Conference of the International Cartilage Regeneration & Joint Repair Society, Berlin, Germany.

Bibtex

Slijepcevic, D., Horst, F., Simak, M., Lapuschkin, S., Raberger, A. M., Samek, W., Breiteneder, C., Schöllhorn, W. I., Zeppelzauer, M., & Horsak, B. (2022). Explaining machine learning models for age classification in human gait analysis. Gait & Posture, 97, S252–S253. https://doi.org/10.1016/j.gaitpost.2022.07.153

Slijepcevic, D., Horst, F., Lapuschkin, S., Horsak, B., Raberger, A.-M., Kranzl, A., Samek, W., Breitender, C., Schöllhorn, W., & Zeppelzauer, M. (2022). Explaining Machine Learning Models for Clinical Gait Analysis. ACM Transactions on Computing for Healthcare, 3(2), 14:1-14:27. https://doi.org/10.1145/3474121

Zulkarnain, A. H. B., Totorean, A., Gere, A., Cruz, E., Horsak, B., Lancere, L., Schöffer, L., Simonlehner, M., Crișan-Vida, M., Fernandes, R., & Sterckx, Y. (2022). Development of a social inclusive immersive virtual reality exergame to promote physical activity. Book of Proceedings FOODCONF. Fourth International Conference on Food Science and Technology, Budapest, Hungary. http://www.foodconf.hu/poster/P4000/68.pdf

Dumphart, B., Slijepčević, D., Unglaube, F., Kranzl, A., Baca, A., Zeppelzauer, M., & Horsak, B. (2021). An automated deep learning-based gait event detection algorithm for various pathologies. Gait & Posture, 90, 50–51. https://doi.org/https://doi.org/10.1016/j.gaitpost.2021.09.026

Dumphart, B., Schimanko, M., Nöstlinger, S., Iber, M., Horsak, B., & Heller, M. (2021). Validity and reliability of a mobile insole to measure vertical ground reaction force during walking. 823. http://media.isb2021.com/2021/12/ISB2021_ProgrammeAbstracts.pdf