Iterative Assessment of Statistically-Oriented and Standard Algorithms for Determining Muscle Onset with Intramuscular Electromyography.

The onset of muscle activity, as measured by electromyography (EMG), is a commonly applied metric in biomechanics. Intramuscular EMG is often used to examine deep musculature and there are currently no studies examining the effectiveness of algorithms for intramuscular EMG onset. The present study e...

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Publicado en:Journal of Applied Biomechanics Vol. 33; no. 6; pp. 464 - 469
Autores principales: Tenan, Matthew S., Tweedell, Andrew J., Haynes, Courtney A.
Formato: research tables/charts Journal Article
Publicado: Human Kinetics Publishers, Inc. Dec2017
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Dec2017
      vid: 33
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      pub: Human Kinetics Publishers, Inc.
      place: Champaign, Illinois
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        10.1123/jab.2016-0313
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        atl: Iterative Assessment of Statistically-Oriented and Standard Algorithms for Determining Muscle Onset with Intramuscular Electromyography.
      aug:
        au:
          Tenan, Matthew S.
          Tweedell, Andrew J.
          Haynes, Courtney A.
        affil: United States Army Research Laboratory
      sug:
        subj:
          Electromyography Methods
          Data Analysis, Statistical Methods
          Algorithms Evaluation
          Human
          Female
          Male
          Young Adult
          Adult
          Variance Analysis
          Parametric Statistics
          Nonparametric Statistics
          Linear Regression
          Double-Blind Studies
          Adult: 19-44 years
          Female
          Male
      ab: The onset of muscle activity, as measured by electromyography (EMG), is a commonly applied metric in biomechanics. Intramuscular EMG is often used to examine deep musculature and there are currently no studies examining the effectiveness of algorithms for intramuscular EMG onset. The present study examines standard surface EMG onset algorithms (linear envelope, Teager-Kaiser Energy Operator, and sample entropy) and novel algorithms (time series mean-variance analysis, sequential/batch processing with parametric and nonparametric methods, and Bayesian changepoint analysis). Thirteen male and 5 female subjects had intramuscular EMG collected during isolated biceps brachii and vastus lateralis contractions, resulting in 103 trials. EMG onset was visually determined twice by 3 blinded reviewers. Since the reliability of visual onset was high (ICC(1,1): 0.92), the mean of the 6 visual assessments was contrasted with the algorithmic approaches. Poorly performing algorithms were stepwise eliminated via (1) root mean square error analysis, (2) algorithm failure to identify onset/premature onset, (3) linear regression analysis, and (4) Bland-Altman plots. The top performing algorithms were all based on Bayesian changepoint analysis of rectified EMG and were statistically indistinguishable from visual analysis. Bayesian changepoint analysis has the potential to produce more reliable, accurate, and objective intramuscular EMG onset results than standard methodologies.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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