Refining Upper Body Muscles’ EMG Signals from ECG Contamination by Nonlinear Filter

Electromyogram signals are key factors for analyzing physiological activities of the muscles. One of the problems that we face in analyzing EMG signals of torso muscles, is removal the electrocardiogram artifact from EMG signals. In this paper nonlinear filtering method is used for removing ECG contamination from EMG signals. This technique is the result of nonlinear dynamical systems theory that developed for reducing noise in deterministically chaotic signals. In this study a clean EMG signal recorded from the rectus femoris muscle of the left leg and ECG signal is taken from MIT-BIH database and to simulate contaminated signal, based on signal-to-noise ratio, ECG and EMG signals are linearly combined. Simulation results is evaluated with signal to noise ratio, relative error and correlation coefficient criteria. The results indicate the suitability of nonlinear filtering method for removing ECG contamination from EMG signals.

کلیدواژه ها:

chaotic signal ، electrocardiogram contamination ، electromyogram ، noise removal ، nonlinear filter