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Surface electromyography analysis in long-term recordings: application to head rest comfort in cars

Abstract : Analysis of long-term surface electromyographic (SEMG) signals has many applications in ergonomics when related to muscle fatigue. The present work proposes a set of processing methods reporting SEMG modifications during longterm driving tests in various situations (with or without head rest). A segmentation/classification algorithm allows signal splitting into homogeneous parts (postural activity and EMG bursts) and an efficient artefact suppression. Postural activity modifications are evaluated from time-varying amplitude probability density function (TAPDF) parameters. EMG burst analysis is achieved taking into account the relationships of these bursts with accelerometric events. This segmentation/classification procedure improves repeatability but does not significantly modify the overall results obtained before segmentation, as far as the analysis of head rest influence is concerned.
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https://hal-utt.archives-ouvertes.fr/hal-02362969
Contributor : Jean-Baptiste Vu Van <>
Submitted on : Thursday, November 14, 2019 - 10:39:22 AM
Last modification on : Monday, December 9, 2019 - 4:42:05 PM

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Jacques Duchene, Thibault Lamotte. Surface electromyography analysis in long-term recordings: application to head rest comfort in cars. Ergonomics, Taylor & Francis, 2010, 44 (3), pp.313-327. ⟨10.1080/00140130118427⟩. ⟨hal-02362969⟩

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