Our research projects include both basic and applied research at the intersection of health, social care, and digital technologies.
EyeQTrack - Quantitative Eye-Tracking Analytics for Adaptive XR Training & Rehabilitation in Healthcare
A self-adaptive eXtended reality environment for training and therapeutic purposes.
Endowed professorship of the province of Lower Austria to strengthen and expand the research focus on motor rehabilitation
deepForce - Pushing the limits of rapid estimation of knee joint contact force estimation in clinical gait analysis by Machine and Deep Learning
Machine learning methods to enable more clinicians to use data obtained by gait analyses for diagnosis.
Equipping devices for everyday use with voice interaction, fall detection and alerts as support in cases of emergency.
O3DGA – The Use of Machine Learning as a Supportive Measure in Clinical Three-Dimensional Gait Analysis
Optimisation of time-consuming and error-prone processes in three-dimensional gait analysis.
Promoting University of Applied Sciences as innovation and entrepreneurship centres for Digital Health
Assessing whether a sensor-equipped insole for detecting changes in gait patterns can be used for preventive therapeutic purposes.
Evaluation of the effectiveness of rehabilitation measures after reconstruction of the anterior cruciate ligament using simplified gait analysis
Evaluation of the accuracy of non-invasive hip joint centre estimation methods for clinical gait analysis in children and adolescents