Possibilities of Using Motion-Capture Technology and Electromyography Measurements for the Analysis of Upper Extremity Motion

Due to medical staff shortages (Korneta and Chmiel in Int J Environ Res Public Health 19:14827, 2022) and an ageing society, there is a need for the development of technologies to provide care for multiple patients simultaneously by a single specialist—rehabilitation robots, among others. The ideal solution would be a therapy conducted remotely, with minimal supervision of a physiotherapist, which would save time and increase the number of patients treated at the same time, when it is convenient for them and the therapist. For this purpose, there is a need to create a device equipped with systems that allow detection of hazardous events resulting from the performed physiotherapeutic activities. This paper proposes a methodology for collecting data usable in the future for modelling predictive controlling systems for exoskeletons for home kinesiotherapy. It consists of simultaneous electromyography (EMG) tracking and upper extremity position measurements registered with the motion capture. The experimental trials of these were conducted on three volunteers. EMG measurements were obtained with a 12-bit resolution. The obtained kinematic data, i.e. angles of shoulder and elbow joints is intended for use as a training data set for neural networks in future research. This network’s purpose is to predict rotation angles in joints of the upper extremity based on electromyography data. To obtain information about the angles of upper extremity joints, a multibody model of the upper extremity with five degrees of freedom was proposed, and inverse kinematics calculations using motion-capture markers were conducted.