Fall Detection System for Monitoring an Elderly Person Based on Six-Axis Gyroscopes

DOI

10.2991/eame-18.2018.51How to use a DOI?

Keywords

component; fall detecion system; six-axis gyroscope; feature vector generation method; support vector machine

Abstract

Accidental falls are crucial causes of death due to injury among the elderly. Many researches about fall detection applied complex algorithms and required heavy equipment. However, these approaches can hardly apply to the elderly’s daily life. In this paper, we employ a six-axis gyroscope that integrated in a small smart bracelet. Users who wear the smart bracelet can get the information including acceleration for X, Y, and Z movement, and the rate of rotation in space. Then, we introduce three feature vector generation methods based on the information and feed these three vectors into support vector machine (SVM) algorithm for fall detection. From a dataset of 66 people, we show that the geometric parameters method is the best of the three with a high accuracy (100%), low false alarm rate (0%) and low missing alarm rate (0%) in a simulated home environment.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Maojie Tang
AU  - Dongxiu Ou
PY  - 2018/06
DA  - 2018/06
TI  - Fall Detection System for Monitoring an Elderly Person Based on Six-Axis Gyroscopes
BT  - Proceedings of the 2018 3rd International Conference on Electrical, Automation and Mechanical Engineering (EAME 2018)
PB  - Atlantis Press
SP  - 244
EP  - 247
SN  - 2352-5401
UR  - https://doi.org/10.2991/eame-18.2018.51
DO  - 10.2991/eame-18.2018.51
ID  - Tang2018/06
ER  -