論文

査読有り
2015年2月

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

JOURNAL OF ELECTROMYOGRAPHY AND KINESIOLOGY
  • Mark A. Robinson
  • ,
  • Jos Vanrenterghem
  • ,
  • Todd C. Pataky

25
1
開始ページ
14
終了ページ
19
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1016/j.jelekin.2014.10.018
出版者・発行元
ELSEVIER SCI LTD

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. (C) 2014 Elsevier Ltd. All rights reserved.

リンク情報
DOI
https://doi.org/10.1016/j.jelekin.2014.10.018
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000348289200003&DestApp=WOS_CPL
ID情報
  • DOI : 10.1016/j.jelekin.2014.10.018
  • ISSN : 1050-6411
  • eISSN : 1873-5711
  • Web of Science ID : WOS:000348289200003

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