Fusion of M-IMU and EMG signals for the control of trans-humeral prostheses

The commercially available myoelectric control strategies with surface electrodes used to drive upper limb prostheses, e.g. conventional amplitude-based control, do not allow the control of simultaneous movements in multi-Dof devices, i.e. the prostheses for trans-humeral amputees or with shoulder disarticulation. Pattern recognition applied to ElectroMyoGraphic (EMG) signals represents a valid solution to this problem although it could be efficiently applied only to high level upper limb amputees who undergo a Targeted Muscle Reinnervation surgery (TMR). This paper introduces a novel control strategy for trans-humeral prostheses that, based on the coupled use of myoelectric and magneto-inertial sensors, allows managing simultaneous movements and more physiological reaching tasks. With the proposed approach the user could operate the elbow flexion-extension, wrist prono-supination and hand opening-closing exploiting the residual stump motions combined to the myoelectric activity of two target muscles, i.e. biceps and triceps. A comparative experimental analysis has been carried out in order to compare the performance of the proposed control with the traditional myoelectric control. Eight able-bodied individuals have been recruited and were asked to perform four different tasks in a Virtual Environment (VE), using both control strategies. Control performance was assessed by means of three quantitative indices, i.e. completion time, average rotational speed and success rate. The obtained results show that the proposed control strategy can achieve higher performance than the traditional control for each task.