Targeted Muscle Training with a Hybrid Body-Machine Interface

Studies have shown that motor recovery after neurological injuries is dependent on functional reorganization. In particular, engaging muscles in skilled activities triggers a process of remodeling that could lead to improving functional outcomes. Here, we propose a novel approach for engaging targeted muscles into skilled activities while operating assistive interfaces based on wearable sensors. To enforce contribution of specific muscles to the control output of a movement-based assistive interface, we introduced a signal dependent on muscle activation as replacement of a highly correlated signal dependent on limb kinematics, as measured by a set of inertial sensors. The latter were weighted against the EMG contribution and sent as input to a linear map projecting kinematic signals onto a 2D screen. Modulation of the weighting factor allows switching from a kinematic only (assistive) to a hybrid (rehabilitative) mode by increasing or decreasing EMG contribution to the operation of the interface.