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

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 informa...

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Publicado en:Journal of Electromyography & Kinesiology Vol. 31; pp. 126 - 136
Autores principales: Devaprakash, Daniel, Weir, Gillian J., Dunne, James J., Alderson, Jacqueline A., Donnelly, Cyril J.
Formato: Journal Article
Publicado: Elsevier B.V. Dec2016
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Dec2016
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      pub: Elsevier B.V.
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        10.1016/j.jelekin.2016.10.001
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        atl: The influence of digital filter type, amplitude normalisation method, and co-contraction algorithm on clinically relevant surface electromyography data during clinical movement assessments.
      aug:
        au:
          Devaprakash, Daniel
          Weir, Gillian J.
          Dunne, James J.
          Alderson, Jacqueline A.
          Donnelly, Cyril J.
        affil: M408, School of Sport Science, Exercise and Health, The University of Western Australia, Crawley, Perth, Western Australia 6009, Australia
      sug:
        subj:
          Movement
          Muscle, Skeletal Physiology
          Electromyography Methods
          Electromyography Equipment and Supplies
          Electromyography Standards
          Young Adult
          Calibration
          Female
          Algorithms
          Signal Processing, Computer Assisted
          Adolescence
          Scales
          Adolescent: 13-18 years
          Female
      ab: 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.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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