Patient-centered and dynamically adapting motor rehabilitation using Virtual Reality

Abstract

The number of deaths and impairments due to neurological diseases, and especially due to stroke and Parkinson’s disease, is increasing on a global scale [33], and challenges for current and future health care systems could arise from this increasing number of patients who require motor neurorehabilitation. VR applications have the potential to counter steer these challenges by making an interactive and adaptive rehabilitation setup in an at home environment feasable. Nonetheless, even though such a VR-based rehabilitation in an at home setting could reduce the work load of health care workers and can adapt to patients’ needs, it requires patient-centered setup to assure safe interaction. The scope of this thesis is to study how perceived cognitive load of older users di!ers between static guidance complexity and dynamic complexity adjustment of visual guidance in VR motor rehabilitation. In order to be able to answer the research question with respect to dynamic cue adjustment in context of VR motor rehabilitation, a prototype running on an HMD was designed for older users, implemented and evaluated in a user study with healthy subjects. The evaluation of the VR motor rehabilitation prototype showed that dynamic complexity adjustment of visual guidance does not di!er from static guidance complexity with respect to perceived mental demand and work load. The di!erence was not statistically significant. The conclusion was, that dynamic complexity adjustment of visual guidance does not overwhelm or support users mentally di!erently than static cues. The findings of this thesis extend the understanding of dynamic cue adjustment in VR motor rehabilitation. Future work is recommended to focus on improvement of dynamic complexity adjustment of visual guidance by enhancing it with machine learning algorithms. Extending cues and task di"culty is recommended, to better support users during interaction. Feedback from patients su!ering from stroke or Parkinson’s disease is recommended to be considered to gain deeper insights into required improvements of the VR motor rehabilitation applications.

Date of Award	2025
Original language	English
Supervisor	Christoph Anthes (Supervisor)