The detection of freezing of gait in Parkinson's Disease patients using EEG signals based on wavelet decomposition

Handojoseno, AM; Shine, JM; Nguyen, N; Tran, YH; Lewis, S; Nguyen, HT

The detection of freezing of gait in Parkinson's Disease patients using EEG signals based on wavelet decomposition

Handojoseno, AM Shine, JM Nguyen, N Tran, YH Lewis, S Nguyen, HT

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Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: Proceedings of the 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012, pp. 69 - 72
Issue Date:: 2012-01

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Field	Value	Language
dc.contributor.author	Handojoseno, AM	en_US
dc.contributor.author	Shine, JM	en_US
dc.contributor.author	Nguyen, N	en_US
dc.contributor.author	Tran, YH	en_US
dc.contributor.author	Lewis, S	en_US
dc.contributor.author	Nguyen, HT	en_US
dc.contributor.editor	Khoo, MCK	en_US
dc.date	2012-08-28	en_US
dc.date.issued	2012-01	en_US
dc.identifier.citation	Proceedings of the 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012, pp. 69 - 72	en_US
dc.identifier.isbn	978-1-4577-1787-1	en_US
dc.identifier.uri	http://hdl.handle.net/10453/22408
dc.description.abstract	Freezing of Gait (FOG) is one of the most disabling gait disturbances of Parkinsonâs disease (PD). The experience has often been described as â feeling like their feet have been glued to the floor while trying to walkâ and as such it is a common cause of falling in PD patients. In this paper, EEG subbands Wavelet Energy and Total Wavelet Entropy were extracted using the multiresolution decomposition of EEG signal based on the Discrete Wavelet Transform and were used to analyze the dynamics in the EEG during freezing. The Back Propagation Neural Network classifier has the ability to identify the onset of freezing of PD patients during walking using these features with average values of accuracy, sensitivity and specificity are around 75 %. This results have proved the feasibility of utilized EEG in future treatment of FOG.	en_US
dc.publisher	IEEE	en_US
dc.relation.ispartof	Proceedings of the 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society	en_US
dc.relation.ispartof	International Conference of the IEEE Engineering in Medicine and Biology Society	en_US
dc.relation.isbasedon	10.1109/EMBC.2012.6345873	en_US
dc.rights	© 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.	en_US
dc.subject.mesh	Nerve Net	en_US
dc.subject.mesh	Humans	en_US
dc.subject.mesh	Parkinson Disease	en_US
dc.subject.mesh	Electroencephalography	en_US
dc.subject.mesh	Gait	en_US
dc.subject.mesh	Entropy	en_US
dc.subject.mesh	Models, Neurological	en_US
dc.subject.mesh	Aged	en_US
dc.subject.mesh	Middle Aged	en_US
dc.subject.mesh	Female	en_US
dc.subject.mesh	Male	en_US
dc.subject.mesh	Wavelet Analysis	en_US
dc.title	The detection of freezing of gait in Parkinson's Disease patients using EEG signals based on wavelet decomposition	en_US
dc.type	Conference Proceeding
utslib.location	USA	en_US
utslib.location.activity	San Diego, California, USA	en_US
utslib.for	0903 Biomedical Engineering	en_US
dc.location.activity	San Diego, California, 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/Strength - CHT - Health Technologies
utslib.copyright.status	closed_access
pubs.consider-herdc	true	en_US
pubs.place-of-publication	USA	en_US
pubs.start-date	2012-08-28	en_US

Abstract:

Freezing of Gait (FOG) is one of the most disabling gait disturbances of Parkinsonâs disease (PD). The experience has often been described as â feeling like their feet have been glued to the floor while trying to walkâ and as such it is a common cause of falling in PD patients. In this paper, EEG subbands Wavelet Energy and Total Wavelet Entropy were extracted using the multiresolution decomposition of EEG signal based on the Discrete Wavelet Transform and were used to analyze the dynamics in the EEG during freezing. The Back Propagation Neural Network classifier has the ability to identify the onset of freezing of PD patients during walking using these features with average values of accuracy, sensitivity and specificity are around 75 %. This results have proved the feasibility of utilized EEG in future treatment of FOG.

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http://hdl.handle.net/10453/22408