The influence of digital filter type, amplitude normalisation method, and co-contraction algorithm on clinically relevant surface electromyography data during clinical movement assessments.

Autor: Devaprakash D; M408, School of Sport Science, Exercise and Health, The University of Western Australia, Crawley, Perth, Western Australia 6009, Australia., Weir GJ; M408, School of Sport Science, Exercise and Health, The University of Western Australia, Crawley, Perth, Western Australia 6009, Australia., Dunne JJ; 318 Campus Drive, Department of Bioengineering, Stanford University, Stanford, CA 94305, USA., Alderson JA; M408, School of Sport Science, Exercise and Health, The University of Western Australia, Crawley, Perth, Western Australia 6009, Australia., Donnelly CJ; M408, School of Sport Science, Exercise and Health, The University of Western Australia, Crawley, Perth, Western Australia 6009, Australia. Electronic address: cyril.donnelly@uwa.edu.au.
Jazyk: angličtina
Zdroj: Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology [J Electromyogr Kinesiol] 2016 Dec; Vol. 31, pp. 126-135. Date of Electronic Publication: 2016 Oct 13.
DOI: 10.1016/j.jelekin.2016.10.001
Abstrakt: There is a large and growing body of surface electromyography (sEMG) research using laboratory-specific signal processing procedures (i.e., digital filter type and amplitude normalisation protocols) and data analyses methods (i.e., co-contraction algorithms) to acquire practically meaningful information from these data. As a result, the ability to compare sEMG results between studies is, and continues to be challenging. The aim of this study was to determine if digital filter type, amplitude normalisation method, and co-contraction algorithm could influence the practical or clinical interpretation of processed sEMG data. Sixteen elite female athletes were recruited. During data collection, sEMG data was recorded from nine lower limb muscles while completing a series of calibration and clinical movement assessment trials (running and sidestepping). Three analyses were conducted: (1) signal processing with two different digital filter types (Butterworth or critically damped), (2) three amplitude normalisation methods, and (3) three co-contraction ratio algorithms. Results showed the choice of digital filter did not influence the clinical interpretation of sEMG; however, choice of amplitude normalisation method and co-contraction algorithm did influence the clinical interpretation of the running and sidestepping task. Care is recommended when choosing amplitude normalisation method and co-contraction algorithms if researchers/clinicians are interested in comparing sEMG data between studies.
(Copyright © 2016 Elsevier Ltd. All rights reserved.)
Databáze: MEDLINE
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