A Smart Telerehabilitation Mirror for Stroke Patients

Cerebrovascular accident is the leading cause of long-term disabilities in adult populations worldwide with the number of cases increasing continuously. Current options for therapy following stroke are expensive and time-consuming for both the patient and the therapist. While the growing concern has

Project Title

A Smart Telerehabilitation Mirror for Stroke Patients

Project Area of Specialization

Biomedical Engineering

Project Summary

Cerebrovascular accident is the leading cause of long-term disabilities in adult populations worldwide with the number of cases increasing continuously. Current options for therapy following stroke are expensive and time-consuming for both the patient and the therapist. While the growing concern has led to the advent of various technologies to ease the rehabilitation process of stroke patients, telerehabilitation systems have not been widely implemented in developed or underdeveloped countries. Consequently, we propose a novel system which would allow patients to perform action observation therapy, for improving upper limb functioning, at home with the therapist remotely monitoring the patient’s progress. A smart mirror is to be used for viewing and recording videos and for sharing patient data with the therapist. EMG sensors in combination with a goniometer will monitor the patient’s muscle activity and joint angles providing the therapist with better insight to improvements in motor skills. This system is a cost-effective, viable alternative to the traditional methods of treating stroke patients in rehabilitation centers and hospitals.

Project Objectives

The goal of this project is to design and develop a cost effective, easy-to-use tele-rehabilitation device which allows therapists to conduct action observation therapy sessions and monitor patient progress remotely. The design consists of a smart mirror and EMG and goniometer sensors which will be provided to the stroke patient on discharge from the hospital. When it is time for the scheduled session, the smart mirror will self-activate and prompt the patient to begin the physiotherapy session for that day. A video will be played for the patient to view and a live video recording will start in which the patient will perform the exercise demonstrated by the video. During the session, the data obtained by the EMG and goniometer sensors will be sent to the smart mirror from where it will be viewable by the physiotherapist. The proposed solution described above differs from other designs since it allows physiotherapists to monitor at-home patients from remote locations while also freeing them from the dependency of individual perception for progress measurement scales.

Project Implementation Method

The overall architecture of the proposed telerehabilitation system will have a user-friendly design. The at-home patient will attach the EMG and goniometer sensors which will be designed and developed for this system specifically to his/her arm. The smart mirror will then display the video for patient viewing and the patient will attempt to perform the same task with the camera recording. The data obtained from both sensors will be processed in the Raspberry Pi; more specifically, signal processing of the EMG signal will be encoded in the Pi and data from the goniometer sensor unit will be converted to an angle measurement for easy interpretation by the physiotherapist. A program for the Raspberry Pi module will be developed for time and/or frequency domain analysis of the EMG signal. Furthermore, the Raspberry Pi will be sending patient data to and retrieving videos for patient viewing from the Thingspeak cloud server. The smart mirror will further be programmed to prompt the patient for the therapy sessions at the scheduled time and days. The physiotherapist will have remote access to all patient data available on Thingspeak from a PC.

Benefits of the Project

This project is specifically designed for the elderly population of Pakistan since commuting to hospitals for physiotherapy sessions is a hassle for most. Moreover, traditional methods of measuring patient progress are dependent on the physiotherapist’s perception which varies with experience and the degree which he/she pay attention to detail. The use of this system will eliminate the need for patients commuting to hospitals on a daily basis while also easing the workload of physiotherapists by providing them with quantitative data (EMG data and goniometer readings) to asses patient recovery.

Technical Details of Final Deliverable

Raspberry pi will be the main device used for acquiring, processing, and transferring data. Data will be transferred via Wi-Fi which is why Raspberry pi 3 and Raspberry pi 4 will be considered. For preparing a smart mirror, a display screen alongside a two-way mirror will be used. Use of gyroscopes will enable angle measurement of the joints. A wearable low-cost EMG sensor will be designed to measure muscle activity of the patients.  

Final Deliverable of the Project

HW/SW integrated system

Core Industry

Medical

Other Industries

Health

Core Technology

Wearables and Implantables

Other Technologies

Augmented & Virtual Reality

Sustainable Development Goals

Good Health and Well-Being for People

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com