A Generation Model for Surface EMG Signals

Abstract

Modeling of physical phenomena has contributed significantly in research. In fact; several investigation and results have been found basing on Modeling. In this work, we proposed a model to generate an electromyographic (EMG) signal detected on the surface of the muscle. Nowadays, surface EMG (SEMG) signal is used in many clinical applications due to its easier detection technique which is non invasive. Information carried by this signal is referred to its generation mechanism and muscle properties. In this paper, the model is based on multi-layer planar analytical model proposed in last few years by Farina which allows just the simulation of single fiber action potential (SFAP). We have generalized this model to get motor unit action potential (MUAP) which is the base of the simulated SEMG signal.