sEMG feature evaluation for identification of elbow angle resolution in graded arm movement

Página do item simplificado
dc.contributor.authorCastro M.C.F.
dc.contributor.authorColombini E.L.
dc.contributor.authorJunior P.T.A.
dc.contributor.authorArjunan S.P.
dc.contributor.authorKumar D.K.
dc.date.accessioned2019-08-19T23:45:15Z
dc.date.available2019-08-19T23:45:15Z
dc.date.issued2014
dc.description.abstract© 2014 Castro et al.Automatic and accurate identification of elbow angle from surface electromyogram (sEMG) is essential for myoelectric controlled upper limb exoskeleton systems. This requires appropriate selection of sEMG features, and identifying the limitations of such a system. This study has demonstrated that it is possible to identify three discrete positions of the elbow; full extension, right angle, and mid-way point, with window size of only 200 milliseconds. It was seen that while most features were suitable for this purpose, Power Spectral Density Averages (PSD-Av) performed best. The system correctly classified the sEMG against the elbow angle for 100% cases when only two discrete positions (full extension and elbow at right angle) were considered, while correct classification was 89% when there were three discrete positions. However, sEMG was unable to accurately determine the elbow position when five discrete angles were considered. It was also observed that there was no difference for extension or flexion phases.
dc.description.firstpage155
dc.description.issuenumber1
dc.description.volume13
dc.identifier.citationCASTRO, MARIA CLAUDIA; COLOMBINI, ESTHER L; JUNIOR, PLINIO T; ARJUNAN, SRIDHAR P; KUMAR, DINESH K. sEMG feature evaluation for identification of elbow angle resolution in graded arm movement. Biomedical Engineering Online (Online), v. 13, n. 1, p. 155, 2014.
dc.identifier.doi10.1186/1475-925X-13-155
dc.identifier.issn1475-925X
dc.identifier.urihttps://repositorio.fei.edu.br/handle/FEI/1159
dc.relation.ispartofBioMedical Engineering Online
dc.rightsAcesso Aberto
dc.subject.otherlanguageAngular position
dc.subject.otherlanguageArm flexion/extension
dc.subject.otherlanguageEMG signal
dc.subject.otherlanguageFeature extraction
dc.subject.otherlanguagePattern recognition
dc.titlesEMG feature evaluation for identification of elbow angle resolution in graded arm movement
dc.typeArtigo
fei.scopus.citations7
fei.scopus.eid2-s2.0-84924418234
fei.scopus.subjectAngle resolution
fei.scopus.subjectAngular positions
fei.scopus.subjectArm flexion/extension
fei.scopus.subjectArm movements
fei.scopus.subjectEMG signal
fei.scopus.subjectExoskeleton systems
fei.scopus.subjectFeature evaluation
fei.scopus.subjectSurface electromyogram
fei.scopus.subjectAdult
fei.scopus.subjectArm
fei.scopus.subjectBraces
fei.scopus.subjectElbow
fei.scopus.subjectElbow Joint
fei.scopus.subjectElectromyography
fei.scopus.subjectEquipment Design
fei.scopus.subjectFemale
fei.scopus.subjectHumans
fei.scopus.subjectMale
fei.scopus.subjectMuscle, Skeletal
fei.scopus.subjectMuscles
fei.scopus.subjectPattern Recognition, Automated
fei.scopus.subjectRange of Motion, Articular
fei.scopus.subjectReproducibility of Results
fei.scopus.subjectSoftware
fei.scopus.updated2023-02-01
fei.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84924418234&origin=inward
Arquivos
Coleções
Artigos