Using Blind Source Separation on accelerometry data to analyze and distinguish the toe walking gait from normal gait in ITW children

Pendharkar, G; Naik, GR; Nguyen, HT

Using Blind Source Separation on accelerometry data to analyze and distinguish the toe walking gait from normal gait in ITW children

Pendharkar, G Naik, GR

Nguyen, HT

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Publication Type:: Journal Article
Citation:: Biomedical Signal Processing and Control, 2014, 13 (1), pp. 41 - 49
Issue Date:: 2014-01-01

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Field	Value	Language
dc.contributor.author	Pendharkar, G	en_US
dc.contributor.author	Naik, GR https://orcid.org/0000-0003-1790-9838	en_US
dc.contributor.author	Nguyen, HT https://orcid.org/0000-0003-3373-8178	en_US
dc.date.issued	2014-01-01	en_US
dc.identifier.citation	Biomedical Signal Processing and Control, 2014, 13 (1), pp. 41 - 49	en_US
dc.identifier.issn	1746-8094	en_US
dc.identifier.uri	http://hdl.handle.net/10453/34069
dc.description.abstract	Gait analysis is an important aspect of Biomedical Engineering. In the recent past, researchers have applied several signal processing methods for the analysis of gait activities. Sensors such as accelerometers, gyroscopes and pressure sensors are more commonly used to identify gait activities remotely. Most of the applications have multiple sensors placed on a single board which is used for gait assessment. However, the problem with multiple sensors is the cross talk introduced by one sensor due to another sensor. Some of the applications use a single sensor such as accelerometer with dual axis measuring the gait activity in horizontal and vertical planes. Depending on the orientation of the accelerometer, the two axial outputs could have overlapping spectra which is very difficult to observe. Spectral and temporal filtering is not suitable for this because of overlapping spectra due to simultaneous movements of the foot in the horizontal and vertical planes. To reliably identify the gait activities, there is a need to decompose and separate the two vertical and horizontal acceleration signals. The earlier research has described a novel method which can be used remotely to identify the gait in ITW children. This paper discusses a lab based automated classification method using Blind Source Separation (BSS) technique to identify toe walking gait from normal gait in Idiopathic Toe Walkers (ITW) children. The outcome of the research study reveals that the BSS techniques in association with K-means classifier can suitably distinguish toe-walking gait from normal gait in ITW children with 97.9 ± 0.2% accuracy. © 2014 Elsevier Ltd.	en_US
dc.relation.ispartof	Biomedical Signal Processing and Control	en_US
dc.relation.isbasedon	10.1016/j.bspc.2014.02.009	en_US
dc.subject.classification	Biomedical Engineering	en_US
dc.title	Using Blind Source Separation on accelerometry data to analyze and distinguish the toe walking gait from normal gait in ITW children	en_US
dc.type	Journal Article
utslib.citation.volume	1	en_US
utslib.citation.volume	13	en_US
utslib.for	090305 Rehabilitation Engineering	en_US
utslib.for	090302 Biomechanical Engineering	en_US
utslib.for	0903 Biomedical Engineering	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
utslib.for	1004 Medical Biotechnology	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.issue	1	en_US
pubs.publication-status	Published	en_US
pubs.volume	13	en_US

Abstract:

Gait analysis is an important aspect of Biomedical Engineering. In the recent past, researchers have applied several signal processing methods for the analysis of gait activities. Sensors such as accelerometers, gyroscopes and pressure sensors are more commonly used to identify gait activities remotely. Most of the applications have multiple sensors placed on a single board which is used for gait assessment. However, the problem with multiple sensors is the cross talk introduced by one sensor due to another sensor. Some of the applications use a single sensor such as accelerometer with dual axis measuring the gait activity in horizontal and vertical planes. Depending on the orientation of the accelerometer, the two axial outputs could have overlapping spectra which is very difficult to observe. Spectral and temporal filtering is not suitable for this because of overlapping spectra due to simultaneous movements of the foot in the horizontal and vertical planes. To reliably identify the gait activities, there is a need to decompose and separate the two vertical and horizontal acceleration signals. The earlier research has described a novel method which can be used remotely to identify the gait in ITW children. This paper discusses a lab based automated classification method using Blind Source Separation (BSS) technique to identify toe walking gait from normal gait in Idiopathic Toe Walkers (ITW) children. The outcome of the research study reveals that the BSS techniques in association with K-means classifier can suitably distinguish toe-walking gait from normal gait in ITW children with 97.9 ± 0.2% accuracy. © 2014 Elsevier Ltd.

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http://hdl.handle.net/10453/34069