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dc.contributor.authorHema, Chengalvarayan Radhakrishnamurthy
dc.contributor.authorPaulraj, Murugesa Pandiyan, Assoc. Prof. Dr.
dc.contributor.authorSazali, Yaacob, Prof. Dr.
dc.contributor.authorAbdul Hamid, Adom, Assoc. Prof. Dr.
dc.contributor.authorRamachandran, Nagarajan, Prof. Dr.
dc.date.accessioned2012-08-09T03:56:26Z
dc.date.available2012-08-09T03:56:26Z
dc.date.issued2012-02-27
dc.identifier.urihttp://dspace.unimap.edu.my/123456789/20587
dc.descriptionInternational Conference on Man Machine Systems (ICoMMS 2012) organized by School of Mechatronic Engineering, co-organized by The Institute of Engineer, Malaysia (IEM) and Society of Engineering Education Malaysia, 27th - 28th February 2012 at Bayview Beach Resort, Penang, Malaysia.en_US
dc.description.abstractFocused time delay neural network based design for a four-state Brain Machine Interface (BMI) to drive a wheelchair is analyzed. Motor imagery signals recorded noninvasively using two bipolar electrodes are used in the study. The performance of the proposed dynamic classifier is compared with a static feed forward neural classifier. Data collected from 10 subjects is used in this study. Average classification performance in the range of 93% to 100% is achievable. Experiment results show that the focused time delay neural network model is suitable for a four-state BMI design.en_US
dc.language.isoenen_US
dc.publisherUniversiti Malaysia Perlis (UniMAP)en_US
dc.relation.ispartofseriesProceedings of the International Conference on Man-Machine Systems (ICoMMS 2012)en_US
dc.subjectBrain Machine Interface (BMI)en_US
dc.subjectNeural networken_US
dc.subjectWheelchairen_US
dc.subjectFocused time-delay neural network (FTDNN)en_US
dc.titleSynchronous brain machine interface design using focused time delay networksen_US
dc.typeWorking Paperen_US
dc.publisher.departmentSchool of Mechatronic Engineeringen_US
dc.contributor.urlhema@unimap.edu.myen_US
dc.contributor.urlpaul@unimap.edu.myen_US


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