Surface Versus Untargeted Intramuscular EMG Based Classification of Simultaneous and Dynamically Changing Movements

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dc.contributor.authorKamavuako, Ernest Nlandu
dc.contributor.authorRosenvang, Jakob Celander
dc.contributor.authorHorup, Ronnie
dc.contributor.authorJensen, Winnie
dc.contributor.authorFarina, Dario
dc.contributor.authorEnglehart, Kevin B.
dc.date.accessioned2023-07-04T13:14:24Z
dc.date.available2023-07-04T13:14:24Z
dc.date.issued2013
dc.description.abstractThe pattern recognition-based myoelectric control scheme is in the process of being implemented in clinical settings, but it has been mainly tested on sequential and steady state data. This paper investigates the ability of pattern recognition to resolve movements that are simultaneous and dynamically changing and compares the use of surface and untargeted intramuscular EMG signals for this purpose. Ten able-bodied subjects participated in the study. Both EMG types were recorded concurrently from the right forearm. The subjects were instructed to track dynamic contraction profiles using single and combined degrees of freedom in three trials. During trials one and two, the amplitude and the frequency of the profile were kept constant (nonmodulated data), and during trial three, the two parameters were modulated (modulated data). The results showed that the performance was up to 93% for nonmodulated tasks, but highly depended on the nature of the data used. Surface and untargeted intramuscular EMG had equal performance for data of similar nature (nonmodulated), but the performance of intramuscular EMG decreased, compared to surface, when tested on modulated data. However, the results of intramuscular recordings obtained in this study are promising for future use of implantable electrodes, because, besides the value added in terms of potential chronic implantation, the performance is theoretically the same as for surface EMG provided that enough information is captured in the recordings. Nevertheless, care should be taken when training the system since data obtained from selective recordings probably need more training data to generalize to new signals.
dc.description.copyright© 2013 IEEE. Articles accepted before 1 July 2020 were published under a CC BY 3.0 or the IEEE Open Access Publishing Agreement license.
dc.identifier.doi10.1109/tnsre.2013.2248750
dc.identifier.issn1534-4320
dc.identifier.issn1558-0210
dc.identifier.urihttps://unbscholar.lib.unb.ca/handle/1882/37251
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers
dc.relationDanish Agency for Science, Technology, and Innovation
dc.relationNSERC
dc.relationEuropean Research Council
dc.relation.hasversionhttp://dx.doi.org/10.1109/TNSRE.2013.2248750
dc.relation.ispartofIEEE Transactions on Neural Systems and Rehabilitation Engineering
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.subject.disciplineElectrical and Computer Engineering
dc.titleSurface Versus Untargeted Intramuscular EMG Based Classification of Simultaneous and Dynamically Changing Movements
dc.typejournal-article
oaire.citation.endPage998
oaire.citation.issue6
oaire.citation.startPage992
oaire.citation.titleIEEE Transactions on Neural Systems and Rehabilitation Engineering
oaire.citation.volume21
oaire.license.conditionother
oaire.versionhttp://purl.org/coar/version/c_ab4af688f83e57aa

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