Quality of Life Technologies

Asim Smailagic and Dan Siewiorek, Human Computer Interaction Institute

Our study objective is to develop an in-process, automated physical therapy trainer that assists manual wheelchair users to learn proper wheelchair use technique. Our hypothesis is that it is possible to identify and train good wheelchair use technique. The system will record wheelchair sensor data on stroke and usage patterns and use machine learning-based data analysis software to extract underlying patterns. Using a database of proper wheelchair stroke techniques, our system will be able to determine how well the user is operating the wheelchair and provide notification and guidance when the user’s technique is not correct. Monitoring the stroke patterns of wheelchair users will aid clinicians in tracking and training proper stroke technique to reduce the incidence of repetitive stress injuries caused by improper wheelchair use technique. The project involves developing appropriate sensors data analysis techniques, digital data logging, wireless data transmission, and visualization of the data. The UPMC Center for Assistive Technology will be our clients.