MATEC Web of Conferences
Volume 45, 20162016 7th International Conference on Mechatronics and Manufacturing (ICMM 2016)
|Number of page(s)||4|
|Section||Computer aided manufacturing technology|
|Published online||15 March 2016|
Mobile Phone Based Falling Detection Sensor and Computer-Aided Algorithm for Elderly People
Department of Biomedical Engineering, School of Medicine, Keimyung University, Daegu, South Korea
Falls are dangerous for the elderly population; therefore many fall detection systems have been developed. However, previous methods are bulky for elderly people or only use a single sensor to isolate falls from daily living activities, which makes a fall difficult to distinguish. In this paper, we present a cost-effective and easy-to-use portable fall-detection sensor and algorithm. Specifically, to detect human falls, we used a three-axis accelerator and a three-axis gyroscope in a mobile phone. We used the Fourier descriptor-based frequency analysis method to classify both normal and falling status. From the experimental results, the proposed method detects falling status with 96.14% accuracy.
© Owned by the authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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