Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/43489
Title: A 3-phase threshold algorithm for smartphone-based fall detection
Authors: Theepop Chaitep
Jakarin Chawachat
Keywords: Computer Science
Engineering
Agricultural and Biological Sciences
Arts and Humanities
Issue Date: 3-Nov-2017
Abstract: © 2017 IEEE. Falls are one of the prominent causes of injury in elderly. A fall detection could help reduce the health risk following the fall that would otherwise get overlooked. Many research studies mostly focus on distinguish a fall from other activities in daily life using smartphone. However, one major problem is a false positive created by a smartphone drop. In this paper, we propose a 3-phase threshold based fall detection algorithm for smartphone which can distinguish a fall from a smartphone drop. The experimental results show that our algorithm achieves a better performance than 2-phase threshold algorithm. Moreover, in smartphone drop cases, our algorithm has 72% specificity higher than 2-phase threshold algorithm which has 31% specificity.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85039908690&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/43489
Appears in Collections:CMUL: Journal Articles

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