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Statistical Parametric Mapping (SPM) for alpha-based statistical analyses of multi-muscle EMG time-series.

Robinson, MA, Vanrenterghem, J and Pataky, TC (2015) Statistical Parametric Mapping (SPM) for alpha-based statistical analyses of multi-muscle EMG time-series. Journal of Electromyography and Kinesiology, 25 (1). pp. 14-19. ISSN 10506411

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Abstract

Multi-muscle EMG time-series are highly correlated and time dependent yet traditional statistical analysis of scalars from an EMG time-series fails to account for such dependencies. This paper promotes the use of SPM vector-field analysis for the generalised analysis of EMG time-series. We reanalysed a publicly available dataset of Young versus Adult EMG gait data to contrast scalar and SPM vector-field analysis. Independent scalar analyses of EMG data between 35% and 45% stance phase showed no statistical differences between the Young and Adult groups. SPM vector-field analysis did however identify statistical differences within this time period. As scalar analysis failed to consider the multi-muscle and time dependence of the EMG time-series it exhibited Type II error. SPM vector-field analysis on the other hand accounts for both dependencies whilst tightly controlling for Type I and Type II error making it highly applicable to EMG data analysis. Additionally SPM vector-field analysis is generalizable to linear and non-linear parametric and non-parametric statistical models, allowing its use under constraints that are common to electromyography and kinesiology.

Item Type: Article
Additional Information: NOTICE: this is the author’s version of a work that was accepted for publication in Journal of Electromyography and Kinesiology. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Electromyography and Kinesiology, 25(1), Febrary 2015 DOI:10.1016/j.jelekin.2014.10.018
Uncontrolled Keywords: 1106 Human Movement And Sports Science
Subjects: Q Science > Q Science (General)
Divisions: Sport & Exercise Sciences
Publisher: Elsevier
Related URLs:
Date Deposited: 23 Jan 2015 15:43
Last Modified: 04 Sep 2021 14:44
DOI or ID number: 10.1016/j.jelekin.2014.10.018
URI: https://researchonline.ljmu.ac.uk/id/eprint/333
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