title: 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 long-term 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.
authors.affiliation: Université de technologie de Troyes, France. jacques.duchene@univ-troyes.fr
authors.forename: J
authors.initials: J
authors.lastname: Duchêne
authors.forename: T
authors.initials: T
authors.lastname: Lamotte
mesh_terms: D000465:Algorithms; D001334:Automobile Driving; D004576:Electromyography / Q000379:methods*; D006804:Ergonomics; D005260:Female; D006801:Humans; D008297:Male; D008962:Models, Theoretical; D018763:Muscle Fatigue / Q000502:physiology*; D011187:Posture / Q000502:physiology*; D013997:Time Factors