The aim of this study is to analyze the origin of multifractality of surface electromyography (sEMG) signals during dynamic contraction in nonfatigue and fatigue conditions. sEMG signals are recorded from triceps brachii muscles of 22 healthy subjects. The signals are divided into six equal segments on time scale for normalization. The first and sixth segments are considered as the nonfatigue and fatigue conditions, respectively. The source of multifractality can be due to correlation and probability distribution. The original sEMG series are transformed into shuffled and surrogate series. These three series namely, original, shuffled, and surrogate series in the nonfatigue and fatigue conditions are subjected to multifractal detrended fluctuation analysis (MFDFA) and features are extracted. The results indicate that sEMG signals exhibit multifractal behavior. Further investigation revealed that origin of multifractality is primarily due to correlation. The origin of multifractality due to correlation is quantified as 80% in nonfatigue and 86% in fatigue conditions. This method of multifractal analysis may be useful for analyzing the progressive changes in muscle contraction in varied neuromuscular studies.
Issue Section:
Fractal Engineering and Biomedicine
Keywords:
Biomedical
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