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dc.contributor.authorHema, Chengalvarayan Radhakrishnamurthy-
dc.contributor.authorLeong, Shi Wei-
dc.contributor.authorErdy Sulino, Mohd Muslim Tan-
dc.date.accessioned2010-11-10T08:20:14Z-
dc.date.available2010-11-10T08:20:14Z-
dc.date.issued2010-05-21-
dc.identifier.citationp.1-2en_US
dc.identifier.isbn978-1-4244-7122-5-
dc.identifier.urihttp://ezproxy.unimap.edu.my:2080/stamp/stamp.jsp?tp=&arnumber=5545306-
dc.identifier.urihttp://dspace.unimap.edu.my/123456789/10176-
dc.descriptionLink to publisher's homepage at http://ieeexplore.ieee.org/en_US
dc.description.abstractA simple brain word dictionary (BWD) system using wavelet decomposition to form feature sets is developed. A BWD is an essential tool in the rehabilitation of paralyzed individuals which converts the brain EEG signals into audio words. A feed forward neural network classifier is proposed to classify ten simple words. EEG signals acquired from two subjects are used in the experiments. Performance of the single trial analysis has an average recognition rate of 87.7%.en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.ispartofseriesProceedings of the 6th International Colloquium on Signal Processing & Its Applications (CSPA) 2010en_US
dc.subjectBrain word dictionary (BWD)en_US
dc.subjectEEG signalsen_US
dc.subjectCommunicationen_US
dc.titleEEG signal recognition for brain word interface using wavelet decompositionen_US
dc.typeWorking Paperen_US
dc.contributor.urlhemacr@yahoo.comen_US
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