VR Training System for Post-Stroke Rehabilitation based on Compensatory Analysis

Abstract

Stroke is one of the most common diseases that lead to impairment of upper limb dexterity. Nowadays, serious games are a common approach to help stroke patient’s recovery. However, the lack of compensatory movement detection, during motor rehabilitation protocols, can lead the patient to learn new and incorrect movement patterns, compromising training sessions. Thus, this project consists of a system that differentiates real upper limb functional improvements from compensatory movement patterns, through a highly customizable serious game, with adaptable levels and tasks. Interaction with the game is done through a handle of a robotic platform. In the game, the subject must control a bird of prey to hunt and to run from predators. 3D motion trackers are placed in different points of the subject paretic arm to detect compensatory movements and to lead back the patient to correctly guide the bird of prey. Therefore, we believe that the proposed method will be a useful supporting tool for helping both the patient during his training sessions and the physiotherapist for better analysis of movements and more specific stroke rehabilitation protocols.