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

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.