Computational architecture of robot coach for physical exercises in kinaesthetic rehabilitation

The rising number of the elderly incurs growing concern about healthcare, and in particular rehabilitation healthcare. Assistive technology and and assistive robotics in particular may help to improve this process. We develop a robot coach capable of demonstrating rehabilitation exercises to patients, watch a patient carry out the exercises and give him feedback so as to improve his performance and encourage him. We propose a general software architecture for our robot coach, which is based on imitation learning techniques using Gaussian Mixture Models. Our system is thus easily programmable by medical experts without specific robotics knowledge, as well as capable of personalised audio feedback to patients indicating useful information to improve on their physical rehabilitation exercise.

Low back pain is a leading cause disabling people. It particularly affects the elderly, whose proportion in European societies keeps rising, incurring growing concern about healthcare. Assistive technology in general and assistive robotics in particular may help to address the increasing need for healthcare. In particular, it can help people with musculoskeletal conditions that need keeping mobility of joints and increase of muscle force and coordination. In this context, we propose to develop a robot coach for rehabilitation exercises. The goal is to increase the time patients spend exercising, by alleviating the lack of time a physiotherapist can spend monitoring a patient. With this perspective, our project will develop a robot coach capable of demonstrating rehabilitation exercises to patients, watch a patient carry out the exercise and give him feedback so as to improve his performance and encourage him.