title: Use of muscle synergies and wavelet transforms to identify fatigue during squatting.
abstract: The objective of this study was to supplement continuous wavelet transforms with muscle synergies in a fatigue analysis to better describe the combination of decreased firing frequency and altered activation profiles during dynamic muscle contractions. Nine healthy young individuals completed the dynamic tasks before and after they squatted with a standard Olympic bar until complete exhaustion. Electromyography (EMG) profiles were analyzed with a novel concatenated non-negative matrix factorization method that decomposed EMG signals into muscle synergies. Muscle synergy analysis provides the activation pattern of the muscles while continuous wavelet transforms output the temporal frequency content of the EMG signals. Synergy analysis revealed subtle changes in two-legged squatting after fatigue while differences in one-legged squatting were more pronounced and included the shift from a general co-activation of muscles in the pre-fatigue state to a knee extensor dominant weighting post-fatigue. Continuous wavelet transforms showed major frequency content decreases in two-legged squatting after fatigue while very few frequency changes occurred in one-legged squatting. It was observed that the combination of methods is an effective way of describing muscle fatigue and that muscle activation patterns play a very important role in maintaining the overall joint kinetics after fatigue.
authors.affiliation: Faculty of Health Sciences, University of Ottawa, Ottawa, Canada.
authors.forename: Kenneth B
authors.initials: KB
authors.lastname: Smale
authors.affiliation: Faculty of Health Sciences, University of Ottawa, Ottawa, Canada; Faculty of Engineering, University of Ottawa, Ottawa, Canada.
authors.forename: Mohammad S
authors.initials: MS
authors.lastname: Shourijeh
authors.affiliation: Faculty of Health Sciences, University of Ottawa, Ottawa, Canada; Faculty of Engineering, University of Ottawa, Ottawa, Canada. Electronic address: dbenoit@uottawa.ca.
authors.forename: Daniel L
authors.initials: DL
authors.lastname: Benoit
mesh_terms: D000328:Adult; D004576:Electromyography / Q000379:methods*; D005260:Female; D006801:Humans; D007719:Knee Joint / Q000502:physiology; D008297:Male; D009119:Muscle Contraction; D018763:Muscle Fatigue; D018482:Muscle, Skeletal / Q000502:physiology*; D011187:Posture; D058067:Wavelet Analysis
keywords: Mean frequency; Muscle activation; Non-negative matrix factorization; Root mean square