Improvement of a Portable Assistive Device Concept for Hand Rehabilitation

As the number of patients with stroke and Parkinson's Disease (PD) increases, it is essential to obtain treatment progress data efficiently for the home rehabilitation. For the therapy of hand disabilities, a system is required to collect data, process and control hand motions during rehabilitation. Current rehabilitation devices that are available in the market are costly and not portable. Existing hand training devices use contact-based sensing approaches that are expensive and inaccurate. As capturing hand motion data using the free joint interaction for rehabilitation and self-exercises still remains a challenge, we propose a low-cost portable system to measure joint motions quantitatively. It uses an electromagnetic driven hand exoskeleton to help patients follow treatment guidelines, which is integrated to a developed module for assessment of the recovery performance to record, analyze and visualize rehabilitation processes in real time.

Hamid Reza Fazeli
Faculty Supervisor: 
Qingjin Peng
Partner University: