This project aims to develop a real-time system that guides stroke patients during upper extremity rehabilitation. The system automatically modifies exercise parameters to account for the specific needs and abilities of different individuals. The system uses a partially observable Markov decision (POMDP) model of a rehabilitation exercise that can capture this form of customization.
This project is in collaboration with the Intelligent Assistive Technology and Systems Lab, the University of Toronto and Quanser, inc.
Read more details about this project from Quanser and IATSL.
Paper
More details can be found by reading the following paper, presented at AAAI 2008 Fall Symposium on AI in Eldercare, 2008:Patricia Kan, Jesse Hoey and Alex Mihailidis Automated upper extremity rehabilitation for stroke patients using a partially observable Markov decision process. AAAI 2008 Fall Symposium on AI in Eldercare, 2008