Inertial sensor based post fall analysis for false alarming reduction

Ye, L; Cao, K; Guo, J; Huang, X; Beadle, P; Argha, A; Piccardi, M; Zhang, G; Su, SW

Inertial sensor based post fall analysis for false alarming reduction

Ye, L Cao, K

Guo, J

Huang, X

Beadle, P Argha, A

Piccardi, M

Zhang, G

Su, SW

Permalink

Publication Type:: Conference Proceeding
Citation:: Proceedings of the 3rd IASTED International Conference on Telehealth and Assistive Technology, TAT 2016, 2016, pp. 36 - 43
Issue Date:: 2016-01-01

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Adobe PDF

Download Published versionAdobe PDF (1.45 MB)

View on publisher's site

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Ye, L	en_US
dc.contributor.author	Cao, K https://orcid.org/0000-0002-4473-2065	en_US
dc.contributor.author	Guo, J https://orcid.org/0000-0001-6008-9682	en_US
dc.contributor.author	Huang, X https://orcid.org/0000-0001-6869-5732	en_US
dc.contributor.author	Beadle, P	en_US
dc.contributor.author	Argha, A https://orcid.org/0000-0002-8276-9774	en_US
dc.contributor.author	Piccardi, M https://orcid.org/0000-0001-9250-6604	en_US
dc.contributor.author	Zhang, G https://orcid.org/0000-0003-3960-0583	en_US
dc.contributor.author	Su, SW https://orcid.org/0000-0002-5720-8852	en_US
dc.date.issued	2016-01-01	en_US
dc.identifier.citation	Proceedings of the 3rd IASTED International Conference on Telehealth and Assistive Technology, TAT 2016, 2016, pp. 36 - 43	en_US
dc.identifier.isbn	9780889869868	en_US
dc.identifier.uri	http://hdl.handle.net/10453/97185
dc.description.abstract	One of the major public health problems among elderly people is falling injury. This study investigates fall detection and prevention by using inertial sensors for which the major existing challenging is how to significantly reduce false alarming in order to enhance the acceptance of elderly users during rehabilitation and daily exercises. Different from most existing approaches in the literature, the behavior after falling will be analyzed in details, which can not only greatly reduce false alarming, but also significantly improves the accuracy of the assessment of the severity of falling injuries.	en_US
dc.relation.ispartof	Proceedings of the 3rd IASTED International Conference on Telehealth and Assistive Technology, TAT 2016	en_US
dc.relation.isbasedon	10.2316/P.2016.846-011	en_US
dc.title	Inertial sensor based post fall analysis for false alarming reduction	en_US
dc.type	Conference Proceeding
utslib.for	0906 Electrical and Electronic Engineering	en_US
utslib.for	0903 Biomedical Engineering	en_US
utslib.for	080105 Expert Systems	en_US
utslib.for	080108 Neural, Evolutionary and Fuzzy Computation	en_US
utslib.for	080605 Decision Support and Group Support Systems	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/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Students
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US

Abstract:

One of the major public health problems among elderly people is falling injury. This study investigates fall detection and prevention by using inertial sensors for which the major existing challenging is how to significantly reduce false alarming in order to enhance the acceptance of elderly users during rehabilitation and daily exercises. Different from most existing approaches in the literature, the behavior after falling will be analyzed in details, which can not only greatly reduce false alarming, but also significantly improves the accuracy of the assessment of the severity of falling injuries.

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

http://hdl.handle.net/10453/97185