Decoding and mapping of right hand motor imagery tasks using EEG source imaging

Brad Edelman, Bryan Baxter, Bin He

Research output: Chapter in Book/Report/Conference proceedingConference contribution

18 Scopus citations

Abstract

Current EEG based brain computer interface (BCI) systems have achieved successful control in up to 3 dimensions; however, the current sensor-based paradigm is not well suited for many rehabilitative and recreational applications that require motor imagination (MI) tasks of fine motor movements to be recognized. Therefore there is a great need to find complex MI tasks that are intuitive for BCI users to perform and that can be classified with high accuracy. In this paper we present our results on classifying four MI tasks of the right hand, flexion, extension, supination and pronation using a novel EEG source imaging approach. Using this approach we were able to improve the four-class classification of the four tasks by nearly 10% as compared to traditional sensor-based techniques.

Original languageEnglish (US)
Title of host publication2015 7th International IEEE/EMBS Conference on Neural Engineering, NER 2015
PublisherIEEE Computer Society
Pages194-197
Number of pages4
ISBN (Electronic)9781467363891
DOIs
StatePublished - Jul 1 2015
Event7th International IEEE/EMBS Conference on Neural Engineering, NER 2015 - Montpellier, France
Duration: Apr 22 2015Apr 24 2015

Publication series

NameInternational IEEE/EMBS Conference on Neural Engineering, NER
Volume2015-July
ISSN (Print)1948-3546
ISSN (Electronic)1948-3554

Other

Other7th International IEEE/EMBS Conference on Neural Engineering, NER 2015
Country/TerritoryFrance
CityMontpellier
Period4/22/154/24/15

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

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