Developing a Low-cost, smart, handheld electromyography biofeedback system for telerehabilitation with Clinical Evaluation

Existing telerehabilitation systems require highly experienced personnel to interpret a patient’s muscle activity in a specialized lab, limiting the biofeedback available at the patient’s home. In addition, there is no contact between physiotherapists and patients remotely. This study designed and i...

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Bibliographic Details
Main Authors: Mazen M. Yassin, Abubakr M. Saber, Mohamed N. Saad, Ashraf M. Said, Ayman M. Khalifa
Format: Article
Language:English
Published: Elsevier 2021-06-01
Series:Medicine in Novel Technology and Devices
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2590093520300308
Description
Summary:Existing telerehabilitation systems require highly experienced personnel to interpret a patient’s muscle activity in a specialized lab, limiting the biofeedback available at the patient’s home. In addition, there is no contact between physiotherapists and patients remotely. This study designed and implemented an interactive tele-electromyography (EMG) biofeedback device for facilitating patients’ rehabilitation and giving the physiotherapist the ability to develop and monitor personalized treatment for each patient precisely and remotely. The device comprised a device that acquires EMG signals during muscular activity and two cell phone applications, one for the patient and the other for the physiotherapist; traced muscle activity; and enabled the physiotherapist to monitor and control the patients’ sessions through a Google Firebase database. EMG signals were acquired from five subjects, and results were compared to a certified device. The evaluation process involved two metrics, correlation coefficient and root mean square value (RMSV). The proposed EMG biofeedback device is an integrated solution with numerous features, such as low cost, handheld size, patient-friendly interface, contributions to rapid healing, and secure communication. In addition, it provides raw EMG signals for applied research applications.
ISSN:2590-0935