Abstract—In this work, an attempt has been made to analyze surface electromyography (sEMG) signals in dynamic contraction using multifractal detrending moving average algorithm (MFDMA). The signals are recorded from biceps brachii muscles of twenty two healthy participants using a standard experimental protocol. The recorded sEMG signals are pre-processed and normalized by dividing the time axis into six equal segments. The first segment and sixth segment are considered as nonfatigue and fatigue conditions for analysis. The signals are subjected to MFDMA and verified to test multifractal properties of biceps brachii muscles using scaling exponent, generalized Hurst exponent and multifractal spectrum in both nonfatigue and fatigue conditions. Each multifractal spectrum is characterized by calculating three features namely peak exponent (PEV), degree of multifractality (DOM) and mean multifractal spectral exponent (MSE). The variation of multifractal spectral features in fatigue conditions are analyzed using ANOVA and Tukey test. The results of scaling exponent function and generalized Hurst exponent function indicated multifractal characteristics for sEMG signals in dynamic contractions. DOM increased from 0.56 to 0.96 and MSE increased from 0.54 to 0.75 in nonfatigue and fatigue conditions respectively. It appears that this method is useful in analyzing fatigue and nonfatigue conditions associated with muscle mechanics using non-invasive sEMG recordings. This study can be useful in field of clinical studies, rehabilitation, prosthetics control and sports medicine.
 

Index Terms—surface EMG, biceps brachii, multifractal, detrending moving average algorithm, muscle fatigue, dynamic contractions

Cite: K. Marri and R. Swaminathan, "Analysis of Biceps Brachii Muscles in Dynamic Contraction Using sEMG Signals and Multifractal DMA Algorithm," International Journal of Signal Processing Systems, Vol. 4, No. 1, pp. 79-85, February 2016. doi: 10.12720/ijsps.4.1.79-85