2015年2月
Statistical Parametric Mapping (SPM) for alpha-based statistical analyses of multi-muscle EMG time-series
JOURNAL OF ELECTROMYOGRAPHY AND KINESIOLOGY
- ,
- ,
- 巻
- 25
- 号
- 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
- ID情報
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- DOI : 10.1016/j.jelekin.2014.10.018
- ISSN : 1050-6411
- eISSN : 1873-5711
- Web of Science ID : WOS:000348289200003