A multivariate statistical analysis of muscular biopotencial for human arm movement characterization

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dc.contributor.authorSILVA, G. A. DA
dc.contributor.authorCastro, M.C.F.
dc.contributor.authorCarlos E. Thomaz
dc.contributor.authorOrcidhttps://orcid.org/0000-0002-2751-0014
dc.contributor.authorOrcidhttps://orcid.org/0000-0001-5566-1963
dc.date.accessioned2023-08-26T23:50:07Z
dc.date.available2023-08-26T23:50:07Z
dc.date.issued2009-01-14
dc.description.abstractPattern recognition of electromyographic signals consists of a hard task due to the high dimensionality of the data and noise presence on the acquired signals. This work intends to study the data set as a multivariate pattern recognition problem by applying linear transformations to reduce the data dimensionality. Five volunteers contributed in a previous experiment that acquired the myoelectrical signals using surface electrodes. Attempts to analyse the groups of acquired data by means of descriptive statistics have shown to be inconclusive. This works shows that the use of multivariate statistical techniques such as Principal Components Analysis (PCA) and Maximum uncertainty Linear Discriminant Analysis (MLDA) to characterize the: acquired set of signals through low dimensional scatter plots provides a new understanding of the data spread, making easier its analysis. Considering the arm horizontal movement and the acquired set of data used in this research, a multivariate linear separation between the patterns of interest quantified by the distance of Bhattacharyya suggests that it's possible not only to characterize the angular joint position, but also to confirm that different movements recruit similar amounts of energy to be executed.
dc.description.firstpage227
dc.description.lastpage232
dc.identifier.citationSILVA, G. A. DA; CASTRO, M.C.F.; THOMAZ, C. E. A multivariate statistical analysis of muscular biopotencial for human arm movement characterization. BIOSIGNALS 2009 - Proceedings of the 2nd International Conference on Bio-Inspired Systems and Signal Processing, p. 227-232, jan. 2009.
dc.identifier.urihttps://repositorio.fei.edu.br/handle/FEI/5016
dc.relation.ispartofBIOSIGNALS 2009 - Proceedings of the 2nd International Conference on Bio-Inspired Systems and Signal Processing
dc.rightsAcesso Restrito
dc.subject.otherlanguageBhattacharyya Distance
dc.subject.otherlanguageBiceps
dc.subject.otherlanguageElectromyography
dc.subject.otherlanguageLinear Transformation
dc.subject.otherlanguageMLDA
dc.subject.otherlanguagePCA
dc.subject.otherlanguageTriceps
dc.titleA multivariate statistical analysis of muscular biopotencial for human arm movement characterization
dc.typeArtigo de evento
fei.scopus.citations0
fei.scopus.eid2-s2.0-67650538297
fei.scopus.subjectBhattacharyya Distance
fei.scopus.subjectBiceps
fei.scopus.subjectLinear Transformation
fei.scopus.subjectMLDA
fei.scopus.subjectPCA
fei.scopus.subjectTriceps
fei.scopus.updated2024-11-01
fei.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=67650538297&origin=inward
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