Extraction and analysis of multiple time window features associated with muscle fatigue conditions using sEMG signals
作者：
Highlights：
• Applicability of MTW features in muscle fatigue analysis is studied.
• sEMG signals under fatigue and non-fatigue conditions are recorded and are found to be distinguishable.
• The features represent non-stationary and time-dependant energy variations of sEMG signals associated with fatigue.
• Feature values are distinct in both the conditions.
• MTW features provides better classification accuracy than currently employed time and frequency domain features.
摘要
•Applicability of MTW features in muscle fatigue analysis is studied.•sEMG signals under fatigue and non-fatigue conditions are recorded and are found to be distinguishable.•The features represent non-stationary and time-dependant energy variations of sEMG signals associated with fatigue.•Feature values are distinct in both the conditions.•MTW features provides better classification accuracy than currently employed time and frequency domain features.
论文关键词：Muscle fatigue analysis,Feature extraction,Feature selection,Surface electromyography,Multiple time windows
论文评审过程：Available online 14 November 2013.
论文官网地址：https://doi.org/10.1016/j.eswa.2013.11.009
