Use of inertial sensors as devices for upper limb motor monitoring exercises for motor rehabilitation
This paper presents the development of a system that uses inertial sensors, wireless transceivers and virtual models to monitor the exercises of motor rehabilitation of the upper limbs based on Kabats method. This method involves performing rehabilitation complex exercises that cannot be easily reproduced by the patient, requiring permanent assistance of a qualified professional. However, it is very expensive to have a professional expert assisting the patient throughout the treatment. Therefore, the development of technologies to monitor this type of exercise is necessary. The Kabats method has several applications, e.g. in motor rehabilitation of stroke patients. Stroke is considered the second most common cardiovascular disorder and affects about 9.6 million people in Europe alone, and an estimated 6 million people worldwide die from this disorder. Also, the natural aging process increases the number of strokes, and the demand for healthcare and motor rehabilitation services. To minimize this problem, we propose an experimental system consisting of inertial sensors, wireless transceivers and virtual models according to the models of Denavit & Hartenberg and Euler Angles & Tait Bryan. Through inertial sensors, this system can characterize the movement performed by the patient, compare it with a predefined motion and then indicate if the motor system performed the correct movement. The patients monitor their own movements and the movement pattern (correct movement). All movements are stored in a database allowing continuous checking by a qualified professional. Several experimental tests have shown that the average system error was 0.97, which is suitable to the proposed system.
inertial sensors kabats method models of denavit & hartenberg euler angles & tait bryan motion analysis