Reconstitution of Electromyographic Signals from Pen-Tip Velocity

Abstract

This study deals with a new identification approach, based on Recursive Least Squares algorithm (RLS) to reconstruct the electromyographic signals (EMG) of the forearm muscle. The present study uses the relationship between EMG signals and the velocities profiles of the pen-tip moving on (x, y) plane during the human handwriting motion. An experimental approach has been carried out to measure the forearm EMG signals and the pen-tip displacements on a digital writing tablet. These measurements are used to predict the electrotromyographic signals of the most active forearm signals during the human handwriting motion. In this research, a new third order, linear model is proposed to identify these muscular activities. Good qualitative and quantitative agreement was found between the proposed model response and the recorded experimental data. Quantitative agreement was found between traces and trajectories calculated with identified system.