Phasor represented EMG feature extraction against varying contraction level of prosthetic control

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dc.authorid0000-0003-4236-3646en_US
dc.contributor.authorOnay, Fatih
dc.contributor.authorMert, Ahmet
dc.date.accessioned2021-03-20T20:09:29Z
dc.date.available2021-03-20T20:09:29Z
dc.date.issued2020
dc.departmentBTÜ, Mühendislik ve Doğa Bilimleri Fakültesi, Mekatronik Mühendisliği Bölümüen_US
dc.descriptionMert, Ahmet/0000-0003-4236-3646en_US
dc.description.abstractThis paper introduces phasor representation of electromyography (EMG) feature extraction (PRE). The well-known EMG signal analysis methods, namely root mean square (RMS), and waveform length (WL) are adopted into phasor form depending electrode placement. The values of these methods are computed from 8-channel EMG signals, and their magnitudes with respect to origin are used to construct phasor represented features in this study. The class separability of the PRE is strengthened by adding difference EMG and Euclidean distanced phasor in order to obtain improved feature set against force and electrode variations. The simulations (three schemes) are performed on publicly available EMG dataset on transradial amputees, and the results are presented in terms of accuracy and processing time considering the control strategies of a prosthetic hand. Linear (LDA), and quadratic (QDA) discriminant analysis, and knearest neighbor (k-NN) classifiers are trained, and tested by the PRE features. Our method outperforms previous accuracy rates in some cases, and reaches to accuracy results of the first study using this dataset without using any reduction method. In our simulations, accuracy rates up to 71.17% (PRE with QDA) for six classes hand movements with three force levels are obtained decreasing processing time by 81.83%. (C) 2020 Elsevier Ltd. All rights reserved.en_US
dc.identifier.doi10.1016/j.bspc.2020.101881en_US
dc.identifier.issn1746-8094
dc.identifier.issn1746-8108
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttp://doi.org/10.1016/j.bspc.2020.101881
dc.identifier.urihttps://hdl.handle.net/20.500.12885/438
dc.identifier.volume59en_US
dc.identifier.wosWOS:000528276200006en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorMert, Ahmet
dc.language.isoenen_US
dc.publisherElsevier Sci Ltden_US
dc.relation.ispartofBiomedical Signal Processing And Controlen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectElectromyographyen_US
dc.subjectPattern recognitionen_US
dc.subjectProsthetic hand controlen_US
dc.subjectMyoelectric controlen_US
dc.subjectTransradial amputeesen_US
dc.titlePhasor represented EMG feature extraction against varying contraction level of prosthetic controlen_US
dc.typeArticleen_US

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