Smart Muscle Strength Assessment Glove for Rehabilitation Purposes

Muscle strength assessment is the first and most important step in the evaluation of injured people. This test is usually performed by experienced therapeutic personals. Yet, the assessment is being performed by manual methods, where only the therapeutic experience is used in this process. This involves many errors and misunderstanding of the exact muscle behavior of the injured person. Hence, there is a critical need for a low cost, easy to use, and portable muscle strength assessment device that can help physiotherapists' during their patient's evaluation process. This work presents a smart wearable glove device that can measure muscles functionality and injury classification with high accuracy in real time. The hardware is designed using force resistive sensors fixed on the tip of glove fingers, and a load cell on the palm in order to take force measurements with high accuracy. Artificial Neural Network algorithm is implemented by using backpropagation method for the classification of the injury level with high accuracy. Real data were gathered from Altkaful Health Center located in AL-Ramtha/Jordan, with sample size equals to 300 patients at different strength levels. Based on the measured data a neural network was trained to classify such data into a standard six levels classification. The newly designed system is successfully trained by the measured data and the neural classifier shows (98.7%) testing accuracy, the hardware after implementation was successfully used by a physiotherapist in the patients' evaluation process.