Vision Based Rehabilitation and Information System for Patients

Abstract

The system is an action verification system for rehabilitation of patients with limited mobility. In this regard, a Kinect depth sensor is used to capture the image-sequences of patients for identification of different actions in real time during rehabilitation exercisers at home. The system is trained to make decisions whether the person is performing the rehabilitation exercises correctly or not, each exercise contain some passing parameters, and this is to ensure that all the exercises are done in a complete and perfect manner. A desktop based application is designed for user’s interaction. This application contains a list of exercises available, the user will have an option to choose any of them according to the need. Physiotherapists using this system at their clinics will be hugely benefitted with this, it will act as their personal application based assistant for mobility exercises. Especially, the report generation feature will help them in tracking the patient’s progress. The report can be generated at any given time while doing an exercise that will brief the user about the angles and distances between the joints and what is the ideal one. The main ambition behind making this rehabilitation system is to recover pre-injury stages in all phases of physical fitness. The equipment required by the system are economical ones to help those patients who genuinely need this system which everyone can set up at their own places. This would allow patients to perform the rehabilitation exercises in sitting position at their relaxing place while preventing patients from falling down during training. The proposed system is 100% real-time (gives results on run time), effective to vision-based action identification, and demands low-cost system requirement (hardware and software), which is affordable for almost everyone.