Evaluation of Capacitive EMG Sensor Geometries by Simulation and Measurement

Abstract

Myoelectric prostheses use electromyography (EMG) signals to control the movements of the prosthesis. EMG-signals are electric potentials on the skin which originate from voluntarily contracted muscles within a person’s residual limb. Thus prostheses of this type utilize the residual neuro-muscular system of the human body to control the functions of an electrically powered prosthesis. Standard measurements are done using conductive electrodes on the skin surface. For technical reasons a capacitive coupling of the EMG to the prosthesis control would be preferable. To design optimal settings of the sensors, a detailed knowledge of the temporal electric potential distribution is vital. Here we show the simulation of the EMG using finite elements employing COMSOL based on MRI data. Then a node-based approach in MATLAB was derived and the comparison with the FE-results show that this approach yields excellent results and offers the advantage of high speed computation which allows for optimization of the sensor geometry. The simulation results were verified using measurements on volunteers showing that indeed our model assumptions and simplifications made are valid. The developed nodal analysis model enables fast and simple determination of the optimal prostheses-sensor geometry for the individual amputee.