Development of a Real-Time, Simple and High-Accuracy Fall Detection System for Elderly Using 3-DOF Accelerometers

Van Thanh, P; Tran, DT; Nguyen, DC; Duc Anh, N; Nhu Dinh, D; El-Rabaie, S; Sandrasegaran, K

Development of a Real-Time, Simple and High-Accuracy Fall Detection System for Elderly Using 3-DOF Accelerometers

Van Thanh, P Tran, DT Nguyen, DC Duc Anh, N Nhu Dinh, D El-Rabaie, S Sandrasegaran, K

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Publication Type:: Journal Article
Citation:: Arabian Journal for Science and Engineering, 2019, 44 (4), pp. 3329 - 3342
Issue Date:: 2019-04-01

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Field	Value	Language
dc.contributor.author	Van Thanh, P	en_US
dc.contributor.author	Tran, DT	en_US
dc.contributor.author	Nguyen, DC	en_US
dc.contributor.author	Duc Anh, N	en_US
dc.contributor.author	Nhu Dinh, D	en_US
dc.contributor.author	El-Rabaie, S	en_US
dc.contributor.author	Sandrasegaran, K https://orcid.org/0000-0003-1270-5756	en_US
dc.date.issued	2019-04-01	en_US
dc.identifier.citation	Arabian Journal for Science and Engineering, 2019, 44 (4), pp. 3329 - 3342	en_US
dc.identifier.issn	2193-567X	en_US
dc.identifier.uri	http://hdl.handle.net/10453/133462
dc.description.abstract	© 2018, King Fahd University of Petroleum & Minerals. Falls represent a major problem for the elderly people aged 60 or above. There are many monitoring systems which are currently available to detect the fall. However, there is a great need to propose a system which is of optimal effectiveness. In this paper, we propose to develop a low-cost fall detection system to precisely detect an event when an elderly person accidentally falls. The fall detection algorithm compares the acceleration with lower fall threshold and upper fall threshold values to accurately detect a fall event. The post-fall recognition module is the combination of posture recognition and vertical velocity estimation that has been added to our proposed method to enhance the performance and accuracy. In case of a fall, our device will transmit the location information to the contacts instantly via SMS and voice call. A smartphone application will ensure that the notifications are delivered to the elderly person’s relatives so that medical attention can be provided with minimal delay. The system was tested by volunteers and achieved 100% sensitivity and accuracy. This was confirmed by testing with public datasets and it also achieved the same percentage in sensitivity and accuracy as in our recorded datasets.	en_US
dc.relation.ispartof	Arabian Journal for Science and Engineering	en_US
dc.relation.isbasedon	10.1007/s13369-018-3496-4	en_US
dc.rights	info:eu-repo/semantics/openAccess
dc.title	Development of a Real-Time, Simple and High-Accuracy Fall Detection System for Elderly Using 3-DOF Accelerometers	en_US
dc.type	Journal Article
utslib.citation.volume	4	en_US
utslib.citation.volume	44	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
utslib.for	0905 Civil Engineering	en_US
utslib.for	0912 Materials Engineering	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 Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CRIN - Realtime Information Networks
utslib.copyright.status	open_access	*
pubs.issue	4	en_US
pubs.publication-status	Published	en_US
pubs.volume	44	en_US

Abstract:

© 2018, King Fahd University of Petroleum & Minerals. Falls represent a major problem for the elderly people aged 60 or above. There are many monitoring systems which are currently available to detect the fall. However, there is a great need to propose a system which is of optimal effectiveness. In this paper, we propose to develop a low-cost fall detection system to precisely detect an event when an elderly person accidentally falls. The fall detection algorithm compares the acceleration with lower fall threshold and upper fall threshold values to accurately detect a fall event. The post-fall recognition module is the combination of posture recognition and vertical velocity estimation that has been added to our proposed method to enhance the performance and accuracy. In case of a fall, our device will transmit the location information to the contacts instantly via SMS and voice call. A smartphone application will ensure that the notifications are delivered to the elderly person’s relatives so that medical attention can be provided with minimal delay. The system was tested by volunteers and achieved 100% sensitivity and accuracy. This was confirmed by testing with public datasets and it also achieved the same percentage in sensitivity and accuracy as in our recorded datasets.

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

http://hdl.handle.net/10453/133462