The Effect of Signal-to-Noise Ratio on Muscle Synergy Extraction

Abstract

The modular organization of the central nervous system (CNS) during motor tasks was widely assessed by means of muscle synergies. The aim of this work was to assess the impact of the Signal-to-Noise Ratio (SNR) on muscle synergies extracted from synthetic surface electromyographic (sEMG) signals that simulate the muscle activity of the lower limb during walking. To evaluate the effect of the SNR, the similarity between the weights vectors and the activation coefficients extracted from real sEMG signals and from simulated sEMG signals at different values of SNR was computed. Results reveal that muscle synergy extraction is strongly dependent upon the quality of the sEMG signals simulated.