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dc.contributor.authorHollingshead, R.
dc.contributor.authorPutrino, D.
dc.contributor.authorGhosh, Soumya
dc.contributor.authorTan, Tele
dc.date.accessioned2018-02-06T06:14:42Z
dc.date.available2018-02-06T06:14:42Z
dc.date.created2018-02-06T05:49:53Z
dc.date.issued2014
dc.identifier.citationHollingshead, R. and Putrino, D. and Ghosh, S. and Tan, T. 2014. Investigation into machine learning algorithms as applied to motor cortex signals for classification of movement stages, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2014), Aug 26 2014, pp. 1290-1293. Chicago, Illinois, USA: IEEE.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/62997
dc.identifier.doi10.1109/EMBC.2014.6943834
dc.description.abstract

Neuroinformatics has recently emerged as a powerful field for the statistical analysis of neural data. This study uses machine learning techniques to analyze neural spiking activities within a population of neurons with the aim of finding spiking patterns associated with different stages of movement. Neural data was recorded during many experimental trials of a cat performing a skilled reach and withdrawal task. Using Weka and the LibSVM classifier, movement stages of the skilled task were identified with a high degree of certainty achieving an area-under-curve (AUC) of the Receiver Operating Characteristic of between 0.900 and 0.997 for the combined data set. Through feature selection, the identification of significant neurons has been made easier. Given this encouraging classification performance, the extension to automatic classification and updating of control models for use with neural prostheses will enable regular adjustments capable of compensating for neural changes.

dc.publisherIEEE
dc.titleInvestigation into machine learning algorithms as applied to motor cortex signals for classification of movement stages
dc.typeConference Paper
dcterms.source.volume2014
dcterms.source.startPage1290
dcterms.source.endPage1293
dcterms.source.titleConference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
dcterms.source.seriesConference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
dcterms.source.isbn9781424479290
dcterms.source.conference2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2014)
dcterms.source.conference-start-dateAug 26 2014
dcterms.source.conferencelocationChicago, Illinois, USA
dcterms.source.place-
curtin.accessStatusFulltext not available


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