The Influence of Force Level and Motor Unit Coherence on Nonlinear Surface EMG Features Examined Using Model Simulation

DC FieldValueLanguage
dc.contributor.authorMcManus, Lara M.-
dc.contributor.authorBotelho, Diego Pereira-
dc.contributor.authorFlood, Matthew W.-
dc.contributor.authorLowery, Madeleine M.-
dc.date.accessioned2020-02-13T13:09:00Z-
dc.date.available2020-02-13T13:09:00Z-
dc.date.copyright2019 IEEEen_US
dc.date.issued2019-07-27-
dc.identifier.isbn978-1-5386-1311-5/19-
dc.identifier.urihttp://hdl.handle.net/10197/11283-
dc.descriptionThe 41st International Engineering in Medicine and Biology Conference, Berlin, Germany, 23-27 July 2019en_US
dc.description.abstractNonlinear features extracted from surface EMG signals have been previously used to infer information on coherent or synchronous activity in the underlying motor unit discharges. However, it has not yet been assessed how these features are affected by the density of the surface EMG signal, and whether changes in the level of muscle activation can influence the effective detection of correlated motor unit firing. To examine this, a motoneuron pool model receiving a beta-band modulated cortical input was used to generate correlated motor unit firing trains. These firing trains were convolved with motor unit action potentials generated from an anatomically accurate electrophysiological model of the first dorsal interosseous muscle. The sample entropy (SampEn) and percentage determinism (%DET) of recurrence quantification analysis were calculated from the composite surface EMG signals, for signals comprised of both correlated and uncorrelated motor unit firing trains. The results show that although both SampEn and %DET are influenced by motor unit coherence, they are differentially affected by muscle activation and motor unit distribution. The results also suggest that sample entropy may provide a more accurate assessment of the underlying motor unit coherence than percentage determinism, as it is less sensitive to factors unrelated to motor unit synchrony.en_US
dc.description.sponsorshipEuropean Research Councilen_US
dc.description.sponsorshipScience Foundation Irelanden_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartof2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)en_US
dc.rights© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en_US
dc.subjectNormal biological development and functioningen_US
dc.subjectElectromyographyen_US
dc.subjectSynchronous motorsen_US
dc.subjectMusclesen_US
dc.subjectForceen_US
dc.subjectCoherenceen_US
dc.subjectFiringen_US
dc.subjectAction potentialsen_US
dc.titleThe Influence of Force Level and Motor Unit Coherence on Nonlinear Surface EMG Features Examined Using Model Simulationen_US
dc.typeConference Publicationen_US
dc.internal.authorcontactotheraoife.ogorman@ucd.ieen_US
dc.statusPeer revieweden_US
dc.identifier.doi10.1109/embc.2019.8857299-
dc.neeo.contributorMcManus|Lara M.|aut|-
dc.neeo.contributorBotelho|Diego Pereira|aut|-
dc.neeo.contributorFlood|Matthew W.|aut|-
dc.neeo.contributorLowery|Madeleine M.|aut|-
dc.description.othersponsorshipInsight Research Centreen_US
dc.description.admin2020-02-13 JG: docx replaced with INSIGHT submitted PDFen_US
dc.date.updated2019-12-12T10:30:31Z-
dc.identifier.grantid646923-
dc.identifier.grantidERC-2014- CoG-646923_DBSModel-
item.grantfulltextopen-
item.fulltextWith Fulltext-
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