#Motor Rehabilitation

The research area of Motor Rehabilitation at the St. Pölten UAS develops technology-assisted approaches to physical rehabilitation and promotes their widespread use in clinical practice by cooperating with industrial partners.

Projects

ELSA- Evaluation of simple gait analysis devices

Evaluation of the effectiveness of rehabilitation measures after reconstruction of the anterior cruciate ligament using simplified gait analysis

HIPstar

Evaluation of the accuracy of non-invasive hip joint centre estimation methods for clinical gait analysis in children and adolescents

Publications

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., 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/gnt2s9
Rind, A., Slijepcevic, D., Zeppelzauer, M., Unglaube, F., Kranzl, A., & Horsak, B. (2022). Trustworthy Visual Analytics in Clinical Gait Analysis: A Case Study for Patients with Cerebral Palsy. Proc. 2022 IEEE Workshop on TRust and EXpertise in Visual Analytics (TREX), 7–15. https://doi.org/10.1109/TREX57753.2022.00006
Krondorfer, P., Slijepčević, D., Unglaube, F., Kranzl, A., Breiteneder, C., Zeppelzauer, M., & Horsak, B. (2021). Deep learning-based similarity retrieval in clinical 3D gait analysis. Gait & Posture, 90, 127–128. https://doi.org/https://doi.org/10.1016/j.gaitpost.2021.09.066
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
Horsak, B., Simonlehner, M., Schöffer, L., Dumphart, B., Jalaeefar, A., & Husinsky, M. (2021). Overground walking in a fully immersive Virtual Reality: Preliminary results of a comprehensive study on the effects on walking biomechanics. Gait & Posture, 90, 100–101. https://doi.org/https://doi.org/10.3389/fbioe.2021.780314
Schwab, C., Durstberger, S., Kainz, H., Baca, A., Thajer, A., Greber-Platzer, S., Ilse, J., Horsak, B., & Kranzl, A. (2021). Accuracy of 3-dimensional freehand ultrasound to estimate anatomical landmarks in children and adolescents with obesity. Gait & Posture, 90, 232–233. https://doi.org/https://doi.org/10.1016/j.gaitpost.2021.09.120
Horst, F., Slijepcevic, D., Simak, M., & Schöllhorn, W. I. (2021). Gutenberg Gait Database, a ground reaction force database of level overground walking in healthy individuals. Scientific Data, 8(1), 232. https://doi.org/https://doi.org/10.1038/s41597-021-01014-6
Horsak, B., Schwab, C., Durstberger, S., Thajer, A., Greber-Platzer, S., Kainz, H., Jonkers, I., & Kranzl, A. (2021). 3D free-hand ultrasound to register anatomical landmarks at the pelvis and localize the hip joint center in lean and obese individuals. Scientific Reports, 11(1), 10650. https://doi.org/https://doi.org/10.1038/s41598-021-89763-7

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