Segmentation Study of Aged Gait Based on FFT

DOI

10.2991/aiie-16.2016.75How to use a DOI?

Keywords

wearable sensor; motion characteristics; motion data segmentation; FFT

Abstract

To study the rules and characteristics of the daily actions of the aged, a set of multi-sensor wearable device has been developed. As for the segmenting method of action data collected from the aged wearing this device, the human action sequence segmentation method has been proposed based on the motion characteristics in this paper. That is to say, collecting the data for Fourier transform, determining the equilibrium position of the motion, and then returning back to the time domain and determining the segmentation point by judging the changing trend of signal waveform, so as to realize the segmentation of the entire signal. Experiments show that this method can effectively segment the daily actions of the aged, extract valid action sequence, and is particularly effective in the segmentation of regular actions.

Copyright

© 2016, 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  - Li Zhu
AU  - Yuchuan Wu
AU  - Shuangbao Ma
AU  - Shengfeng Qi
PY  - 2016/11
DA  - 2016/11
TI  - Segmentation Study of Aged Gait Based on FFT
BT  - Proceedings of the 2016 2nd International Conference on Artificial Intelligence and Industrial Engineering (AIIE 2016)
PB  - Atlantis Press
SP  - 330
EP  - 333
SN  - 1951-6851
UR  - https://doi.org/10.2991/aiie-16.2016.75
DO  - 10.2991/aiie-16.2016.75
ID  - Zhu2016/11
ER  -