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Synchronous brain machine interface design using focused time delay networks

International 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.

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Bibliographic Details
Main Authors:	Hema, Chengalvarayan Radhakrishnamurthy, Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr., Sazali, Yaacob, Prof. Dr., Abdul Hamid, Adom, Assoc. Prof. Dr., Ramachandran, Nagarajan, Prof. Dr.
Other Authors:	hema@unimap.edu.my
Format:	Working Paper
Language:	English
Published:	Universiti Malaysia Perlis (UniMAP) 2012
Subjects:	Brain Machine Interface (BMI) Neural network Wheelchair Focused time-delay neural network (FTDNN)
Online Access:	http://dspace.unimap.edu.my/xmlui/handle/123456789/20587
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id	my.unimap-20587
record_format	dspace
spelling	my.unimap-205872012-08-09T03:56:26Z Synchronous brain machine interface design using focused time delay networks Hema, Chengalvarayan Radhakrishnamurthy Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr. Sazali, Yaacob, Prof. Dr. Abdul Hamid, Adom, Assoc. Prof. Dr. Ramachandran, Nagarajan, Prof. Dr. hema@unimap.edu.my paul@unimap.edu.my Brain Machine Interface (BMI) Neural network Wheelchair Focused time-delay neural network (FTDNN) International 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. Focused 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. 2012-08-09T03:56:26Z 2012-08-09T03:56:26Z 2012-02-27 Working Paper http://hdl.handle.net/123456789/20587 en Proceedings of the International Conference on Man-Machine Systems (ICoMMS 2012) Universiti Malaysia Perlis (UniMAP) School of Mechatronic Engineering
institution	Universiti Malaysia Perlis
building	UniMAP Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaysia Perlis
content_source	UniMAP Library Digital Repository
url_provider	http://dspace.unimap.edu.my/
language	English
topic	Brain Machine Interface (BMI) Neural network Wheelchair Focused time-delay neural network (FTDNN)
spellingShingle	Brain Machine Interface (BMI) Neural network Wheelchair Focused time-delay neural network (FTDNN) Hema, Chengalvarayan Radhakrishnamurthy Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr. Sazali, Yaacob, Prof. Dr. Abdul Hamid, Adom, Assoc. Prof. Dr. Ramachandran, Nagarajan, Prof. Dr. Synchronous brain machine interface design using focused time delay networks
description	International 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.
author2	hema@unimap.edu.my
author_facet	hema@unimap.edu.my Hema, Chengalvarayan Radhakrishnamurthy Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr. Sazali, Yaacob, Prof. Dr. Abdul Hamid, Adom, Assoc. Prof. Dr. Ramachandran, Nagarajan, Prof. Dr.
format	Working Paper
author	Hema, Chengalvarayan Radhakrishnamurthy Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr. Sazali, Yaacob, Prof. Dr. Abdul Hamid, Adom, Assoc. Prof. Dr. Ramachandran, Nagarajan, Prof. Dr.
author_sort	Hema, Chengalvarayan Radhakrishnamurthy
title	Synchronous brain machine interface design using focused time delay networks
title_short	Synchronous brain machine interface design using focused time delay networks
title_full	Synchronous brain machine interface design using focused time delay networks
title_fullStr	Synchronous brain machine interface design using focused time delay networks
title_full_unstemmed	Synchronous brain machine interface design using focused time delay networks
title_sort	synchronous brain machine interface design using focused time delay networks
publisher	Universiti Malaysia Perlis (UniMAP)
publishDate	2012
url	http://dspace.unimap.edu.my/xmlui/handle/123456789/20587
_version_	1643793133550436352
score	13.222552

Synchronous brain machine interface design using focused time delay networks

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