Intention recognition for FES in a grasp-and-release task using volitional EMG and inertial sensors

Abstract

Functional Electrical Stimulation (FES) facilitates the motor recovery of the hand function after stroke. The integration of biofeedback and other strategies to actively involve a patient in the therapy is important for the rehabilitation progress. We introduce a combined control approach for a FES-driven neuroprosthesis using volitional electromyo-graphy (vEMG) and motion capturing via a novel inertial sensor network for patients that still possess a residual activity in the paralyzed muscles. A real-time vEMG measurement and signal processing in between stimulation pulses has been realized during active FES. Experiments showed that our system allows for quick adaption to individual users.

Co-activation and eEMG-feedback for Restoring Hand-Functions

“…In [8] an approach for detecting the user-intention based on EMG and the wrist joint-angle is presented. The detector triggers FES to open the hand or to realize a grasp.…”

“…Now, this becomes u = G * u * = (1 + (G * − 1))u * = u * + u c , wherein u c = G * − 1 is an additional portion present in the actuation signal that is responsible for the compensation of the dynamics. The influence of u c shall be spread across both muscles while the effect of the compensation remains 8. When α does not change by more than 1 • within 0.5s, the movement is considered to have stopped.…”