AIFMS autonomous intelligent fall monitoring system for the elderly persons

Falls are the major cause of injuries and death of elders who live alone at home. Various research works have provided the best solution to the fall detection approach during day vision. However, fall occurs more at the night due to many factors such as low or zero lighting conditions, intake of med...

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Main Authors: Ramanujam, Elangovan, Perumal, Thinagaran
Format: Article
Published: IGI Global 2022
Online Access:http://psasir.upm.edu.my/id/eprint/100157/
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author Ramanujam, Elangovan
Perumal, Thinagaran
author_facet Ramanujam, Elangovan
Perumal, Thinagaran
author_sort Ramanujam, Elangovan
building UPM Institutional Repository
collection Online Access
description Falls are the major cause of injuries and death of elders who live alone at home. Various research works have provided the best solution to the fall detection approach during day vision. However, fall occurs more at the night due to many factors such as low or zero lighting conditions, intake of medication/ drugs, frequent urination due to nocturia disease, and slippery restroom. Based on the required factors, an autonomous monitoring system based on night condition has been proposed through retro-reflective stickers pasted on their upper cloth and infrared cameras installed in the living environment of elders. The developed system uses features such as changes in orientation angle and distance between the retro-reflective stickers to identify the human shape and its characteristics for fall identification. Experimental analysis has also been performed on various events of fall and non-fall activities during the night exclusively in the living environment of the elder, and the system achieves an accuracy of 96.2% and fall detection rate of 92.9%.
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institution Universiti Putra Malaysia
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last_indexed 2025-11-15T13:29:54Z
publishDate 2022
publisher IGI Global
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spelling upm-1001572024-07-17T04:23:22Z http://psasir.upm.edu.my/id/eprint/100157/ AIFMS autonomous intelligent fall monitoring system for the elderly persons Ramanujam, Elangovan Perumal, Thinagaran Falls are the major cause of injuries and death of elders who live alone at home. Various research works have provided the best solution to the fall detection approach during day vision. However, fall occurs more at the night due to many factors such as low or zero lighting conditions, intake of medication/ drugs, frequent urination due to nocturia disease, and slippery restroom. Based on the required factors, an autonomous monitoring system based on night condition has been proposed through retro-reflective stickers pasted on their upper cloth and infrared cameras installed in the living environment of elders. The developed system uses features such as changes in orientation angle and distance between the retro-reflective stickers to identify the human shape and its characteristics for fall identification. Experimental analysis has also been performed on various events of fall and non-fall activities during the night exclusively in the living environment of the elder, and the system achieves an accuracy of 96.2% and fall detection rate of 92.9%. IGI Global 2022 Article PeerReviewed Ramanujam, Elangovan and Perumal, Thinagaran (2022) AIFMS autonomous intelligent fall monitoring system for the elderly persons. International Journal of Ambient Computing and Intelligence, 13 (1). pp. 1-22. ISSN 1941-6237; ESSN: 1941-6245 https://www.igi-global.com/gateway/article/304727 10.4018/IJACI.304727
spellingShingle Ramanujam, Elangovan
Perumal, Thinagaran
AIFMS autonomous intelligent fall monitoring system for the elderly persons
title AIFMS autonomous intelligent fall monitoring system for the elderly persons
title_full AIFMS autonomous intelligent fall monitoring system for the elderly persons
title_fullStr AIFMS autonomous intelligent fall monitoring system for the elderly persons
title_full_unstemmed AIFMS autonomous intelligent fall monitoring system for the elderly persons
title_short AIFMS autonomous intelligent fall monitoring system for the elderly persons
title_sort aifms autonomous intelligent fall monitoring system for the elderly persons
url http://psasir.upm.edu.my/id/eprint/100157/
http://psasir.upm.edu.my/id/eprint/100157/
http://psasir.upm.edu.my/id/eprint/100157/