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01-10-2015 | Mobile Systems

Fall Down Detection Under Smart Home System

Authors: Li-Hong Juang, Ming-Ni Wu

Published in: Journal of Medical Systems | Issue 10/2015

Abstract

Medical technology makes an inevitable trend for the elderly population, therefore the intelligent home care is an important direction for science and technology development, in particular, elderly in-home safety management issues become more and more important. In this research, a low of operation algorithm and using the triangular pattern rule are proposed, then can quickly detect fall-down movements of humanoid by the installation of a robot with camera vision at home that will be able to judge the fall-down movements of in-home elderly people in real time. In this paper, it will present a preliminary design and experimental results of fall-down movements from body posture that utilizes image pre-processing and three triangular-mass-central points to extract the characteristics. The result shows that the proposed method would adopt some characteristic value and the accuracy can reach up to 90 % for a single character posture. Furthermore the accuracy can be up to 100 % when a continuous-time sampling criterion and support vector machine (SVM) classifier are used.

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Title: Fall Down Detection Under Smart Home System
Authors: Li-Hong Juang
Ming-Ni Wu
Publication date: 01-10-2015
Publisher: Springer US
Published in: Journal of Medical Systems / Issue 10/2015
Print ISSN: 0148-5598
Electronic ISSN: 1573-689X
DOI: https://doi.org/10.1007/s10916-015-0286-3

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