A 3-phase threshold algorithm for smartphone-based fall detection

• Main Authors: Theepop Chaitep, Jakarin Chawachat
• Format: Conference Proceeding
• Published: 2018
• Subjects: Computer Science; Engineering; Neuroscience; Physics and Astronomy
• Online Access: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85039908690&origin=inward; http://cmuir.cmu.ac.th/jspui/handle/6653943832/57039
• Institution: Chiang Mai University

© 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.