Using fractal analysis to improve switching rates in "hands free" environmental control technology for the severely disabled

Tran, Y; Thuraisingham, RA; Boord, P; Nguyen, HT; Craig, A

Using fractal analysis to improve switching rates in "hands free" environmental control technology for the severely disabled

Tran, Y

Thuraisingham, RA Boord, P Nguyen, HT

Craig, A

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Publication Type:: Conference Proceeding
Citation:: Proceedings of the 3rd International IEEE EMBS Conference on Neural Engineering, 2007, pp. 406 - 409
Issue Date:: 2007-09-25

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Field	Value	Language
dc.contributor.author	Tran, Y https://orcid.org/0000-0002-1741-4205	en_US
dc.contributor.author	Thuraisingham, RA	en_US
dc.contributor.author	Boord, P	en_US
dc.contributor.author	Nguyen, HT https://orcid.org/0000-0003-3373-8178	en_US
dc.contributor.author	Craig, A	en_US
dc.date.issued	2007-09-25	en_US
dc.identifier.citation	Proceedings of the 3rd International IEEE EMBS Conference on Neural Engineering, 2007, pp. 406 - 409	en_US
dc.identifier.isbn	1424407923	en_US
dc.identifier.isbn	9781424407927	en_US
dc.identifier.uri	http://hdl.handle.net/10453/2824
dc.description.abstract	A negative impact on the quality of life of the severely neurologically disordered such as spinal cord injured persons is the loss of the ability to control devices in their immediate environment. Consequently, we have conducted research on technology designed to restore some measure of independence by providing hands free control over these devices by using EEG signals associated with eye closure (EC) and eye opening (EO). In a previous study we demonstrated that the nonlinear technique fractal dimension analysis was a viable alternative to spectral analysis in detecting these signals in the EEG of able bodied persons. This paper explores the efficacy of using fractal dimension to detect EC/EO signals in a spinal cord injured population. The fractal dimension method was found to improve from the standard spectral analysis technique in that there was a significant reduction is the occurrence of false positive and false negative switching. This improved detection of EC/EO in the brain activity of severely disabled people will be utilised in our technology for remote switching of electrical devices. © 2007 IEEE.	en_US
dc.relation.ispartof	Proceedings of the 3rd International IEEE EMBS Conference on Neural Engineering	en_US
dc.relation.isbasedon	10.1109/CNE.2007.369695	en_US
dc.title	Using fractal analysis to improve switching rates in "hands free" environmental control technology for the severely disabled	en_US
dc.type	Conference Proceeding
utslib.for	090305 Rehabilitation Engineering	en_US
dc.location.activity	Kohala, Hawaii, USA	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

A negative impact on the quality of life of the severely neurologically disordered such as spinal cord injured persons is the loss of the ability to control devices in their immediate environment. Consequently, we have conducted research on technology designed to restore some measure of independence by providing hands free control over these devices by using EEG signals associated with eye closure (EC) and eye opening (EO). In a previous study we demonstrated that the nonlinear technique fractal dimension analysis was a viable alternative to spectral analysis in detecting these signals in the EEG of able bodied persons. This paper explores the efficacy of using fractal dimension to detect EC/EO signals in a spinal cord injured population. The fractal dimension method was found to improve from the standard spectral analysis technique in that there was a significant reduction is the occurrence of false positive and false negative switching. This improved detection of EC/EO in the brain activity of severely disabled people will be utilised in our technology for remote switching of electrical devices. © 2007 IEEE.

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