Prediction of freezing of gait in patients with Parkinson’s disease using EEG signals

Handojoseno, AMA; Naik, GR; Gilat, M; Shine, JM; Nguyen, TN; Quynh, TLY; Lewis, SJG; Nguyen, HT

Prediction of freezing of gait in patients with Parkinson’s disease using EEG signals

Handojoseno, AMA Naik, GR

Gilat, M Shine, JM Nguyen, TN

Quynh, TLY Lewis, SJG Nguyen, HT

Permalink

Publication Type:: Journal Article
Citation:: Studies in Health Technology and Informatics, 2018, 246 pp. 124 - 131
Issue Date:: 2018-01-01

Closed Access

	Filename	Description	Size
	SHTI246-01241.pdf	Published Version	427.09 kB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Handojoseno, AMA	en_US
dc.contributor.author	Naik, GR https://orcid.org/0000-0003-1790-9838	en_US
dc.contributor.author	Gilat, M	en_US
dc.contributor.author	Shine, JM	en_US
dc.contributor.author	Nguyen, TN https://orcid.org/0000-0002-9958-9876	en_US
dc.contributor.author	Quynh, TLY	en_US
dc.contributor.author	Lewis, SJG	en_US
dc.contributor.author	Nguyen, HT https://orcid.org/0000-0003-3373-8178	en_US
dc.date.issued	2018-01-01	en_US
dc.identifier.citation	Studies in Health Technology and Informatics, 2018, 246 pp. 124 - 131	en_US
dc.identifier.isbn	9781614998440	en_US
dc.identifier.issn	0926-9630	en_US
dc.identifier.uri	http://hdl.handle.net/10453/132510
dc.description.abstract	© 2018 The authors and IOS Press. All rights reserved. Freezing of gait (FOG) is an episodic gait disturbance affecting initiation and continuation of locomotion in many Parkinson’s disease (PD) patients, causing falls and a poor quality of life. FOG can be experienced on turning and start hesitation, passing through doorways or crowded areas dual tasking, and in stressful situations. Electroencephalography (EEG) offers an innovative technique that may be able to effectively foresee an impending FOG. From data of 16 PD patients, using directed transfer function (DTF) and independent component analysis (ICA) as data pre-processing, and an optimal Bayesian neural network as a predictor of a transition of 5 seconds before the impending FOG occurs in 11 in-group PD patients, we achieved sensitivity and specificity of 85.86% and 80.25% respectively in the test set (5 out-group PD patients). This study therefore contributes to the development of a non-invasive device to prevent freezing of gait in PD.	en_US
dc.relation.ispartof	Studies in Health Technology and Informatics	en_US
dc.relation.isbasedon	10.3233/978-1-61499-845-7-124	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject.classification	Medical Informatics	en_US
dc.subject.mesh	Humans	en_US
dc.subject.mesh	Parkinson Disease	en_US
dc.subject.mesh	Gait Disorders, Neurologic	en_US
dc.subject.mesh	Electroencephalography	en_US
dc.subject.mesh	Gait	en_US
dc.subject.mesh	Bayes Theorem	en_US
dc.subject.mesh	Quality of Life	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.title	Prediction of freezing of gait in patients with Parkinson’s disease using EEG signals	en_US
dc.type	Journal Article
utslib.citation.volume	246	en_US
utslib.for	1117 Public Health and Health Services	en_US
utslib.for	0807 Library and Information Studies	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 Engineering and Information Technology/School of Biomedical Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
utslib.copyright.status	closed_access	*
pubs.publication-status	Published	en_US
pubs.volume	246	en_US

Abstract:

© 2018 The authors and IOS Press. All rights reserved. Freezing of gait (FOG) is an episodic gait disturbance affecting initiation and continuation of locomotion in many Parkinson’s disease (PD) patients, causing falls and a poor quality of life. FOG can be experienced on turning and start hesitation, passing through doorways or crowded areas dual tasking, and in stressful situations. Electroencephalography (EEG) offers an innovative technique that may be able to effectively foresee an impending FOG. From data of 16 PD patients, using directed transfer function (DTF) and independent component analysis (ICA) as data pre-processing, and an optimal Bayesian neural network as a predictor of a transition of 5 seconds before the impending FOG occurs in 11 in-group PD patients, we achieved sensitivity and specificity of 85.86% and 80.25% respectively in the test set (5 out-group PD patients). This study therefore contributes to the development of a non-invasive device to prevent freezing of gait in PD.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/132510