@article{ref1,
title="Surface electromyography analysis in long-term recordings: application to head rest comfort in cars",
journal="Ergonomics",
year="2001",
author="Duchene, J. and Lamotte, T.",
volume="44",
number="3",
pages="313-327",
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.<p /> <p>Language: en</p>",
language="en",
issn="0014-0139",
doi="",
url="http://dx.doi.org/"
}