Quantification of ankle muscle co-contraction during early stance by wavelet-based analysis of surface electromyographic signals

Abstract

The present study involves Continuous Wavelet Transform (CWT) for the analysis of surface electromyographic (sEM G) signals, with the aim of assessing muscle co-contraction during early stance of healthy-subj ect walking. CWT approach allows computing the coscalogram function, a localized statistical assessment of cross-energy density between two signals. In this study, CWT coscalogram function between two sEMG signals from antagonist muscles is used to quantify muscular co-contraction activity. Daubechies of order 4 (factorization in 6 levels) is adopted as mother wavelet. Noise reduction in the sEMG signals is performed applying CWT denoising. Co-contractions between gastrocnemius lateralis and tibialis anterior are assessed on a set of experimental sEM G signals acquired in 15 able-bodied subjects during walking. Results show as the present CWT approach can provide a reliable assessment of co-contraction in early-stance phase of walking, highlighting that this co-contraction is short (< 1 0 ms) and very frequent. A large variability in the occurrence of the co-contraction is also detected, suggesting that each subject adopts her/his own modality of co-contraction. However, the same physiological purpose is maintained for all subj ects, i.e., to control shock absorption and improve weight-bearing stability during the first phase of human walking. Physiological reliability of experimental results suggests the appropriateness of the present method in clinical applications.