Mechanomyogram signal detection and decomposition: Conceptualisation and research design

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dc.AffiliationOctober University for modern sciences and Arts (MSA)
dc.contributor.authorDaoud H.G.
dc.contributor.authorRagai H.F.
dc.contributor.otherDepartment of Electrical Communications and Electronics Systems
dc.contributor.otherFaculty of Engineering
dc.contributor.otherMSA University
dc.contributor.otherCairo
dc.contributor.other41511
dc.contributor.otherEgypt; Department of Electrical Communications and Electronics
dc.contributor.otherFaculty of Engineering
dc.contributor.otherAin Shams University
dc.contributor.otherCairo
dc.contributor.other11517
dc.contributor.otherEgypt
dc.date.accessioned2020-01-25T19:58:27Z
dc.date.available2020-01-25T19:58:27Z
dc.date.issued2012
dc.descriptionScopus
dc.description.abstractThe primary purpose of the present study is to construct behavioural modelling of the detection and analysis of the Mechanomyogram (MMG) signal for different muscles using virtual muscle model. Mechanomyography is the superficial recording of low frequency vibrations detected over contracting muscles. In this study, a MEMS based accelerometer model is used. Three decomposition techniques which are Discrete Wavelet Transform, Principle Component Analysis and empirical mode decomposition are applied on the MMG for the purpose of feature extraction which could be used for the diagnosis process. A comparison between results of the different techniques as well as hybrid techniques is studied to reach the best one. Copyright � 2012 Inderscience Enterprises Ltd.en_US
dc.description.urihttps://www.scimagojr.com/journalsearch.php?q=23688&tip=sid&clean=0
dc.identifier.doihttps://doi.org/10.1504/IJHTM.2012.048971
dc.identifier.issn13682156
dc.identifier.otherhttps://doi.org/10.1504/IJHTM.2012.048971
dc.identifier.urihttps://www.inderscience.com/info/inarticle.php?artid=48972
dc.language.isoEnglishen_US
dc.relation.ispartofseriesInternational Journal of Healthcare Technology and Management
dc.relation.ispartofseries13
dc.subjectAccelerometeren_US
dc.subjectMechanomyogramen_US
dc.subjectMMGen_US
dc.subjectSignal decompositionen_US
dc.subjectaccelerometeren_US
dc.subjectarticleen_US
dc.subjectbehavioren_US
dc.subjectdecompositionen_US
dc.subjectdiagnostic procedureen_US
dc.subjectextractionen_US
dc.subjectintermethod comparisonen_US
dc.subjectmechanomyographyen_US
dc.subjectmethodologyen_US
dc.subjectmicroelectromechanical systemen_US
dc.subjectmodelen_US
dc.subjectmuscleen_US
dc.subjectmuscle contractilityen_US
dc.subjectmyographyen_US
dc.subjectprincipal component analysisen_US
dc.subjectsignal detectionen_US
dc.subjectvibrationen_US
dc.subjectvirtual realityen_US
dc.titleMechanomyogram signal detection and decomposition: Conceptualisation and research designen_US
dc.typeArticleen_US
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