Measurement system to study the relationship between forearm EMG signals and wrist position at varied hand grip force

Abstract

Hand grip force, wrist flexion and wrist extension are the result of forearm muscle activity. In certain applications such as controlling the movements of a robotic prosthetic hand, information relating wrist joint angles to forearm muscle activity is useful to be used as part of the control algorithm. In this paper, we study the relationship between the muscular activity of forearm muscles and wrist joint angles/position while hand grip force is varied. In order to do that, an electronic circuit was constructed to amplify and filter the electromyogram (EMG) signals measured from the Flexor Carpi Radialis (FCR), Flexor Digitorum Superficialis (FDS) and Extensor Digitorum Communis (EDC). Neural networks were used to model the relationship between EMG signals and wrist joint angle data at different hand grip strength levels. The performances of the networks were indicated by the corresponding Mean Absolute Error values