Issue |
MATEC Web Conf.
Volume 227, 2018
2018 4th International Conference on Communication Technology (ICCT 2018)
|
|
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Article Number | 02019 | |
Number of page(s) | 5 | |
Section | Communication Technology and Information Engineering | |
DOI | https://doi.org/10.1051/matecconf/201822702019 | |
Published online | 14 November 2018 |
Research on Body Posture Classification Algorithm Based on Acceleration
College of Artificial Intelligence, National University of Defence Technology, Changsha, China
a Corresponding author: 1768891410@qq.com
In this paper, based on the wireless acceleration sensor, a wearable body data acquisition system is designed. The acceleration vector magnitude and the angular velocity vector amplitude signal are selected as the breakthrough of the body posture recognition. The focus is on the classification algorithms of the 10 body types commonly used by the soldiers, including Qi Bu walking, goose step, running, low posture, side posture, high posture, push-ups, sit-ups, upstairs and downstairs. The time domain features, frequency domain features and time-frequency characteristics of the signals are analysed respectively. The high-dimensional mixed feature vectors are extracted and reduced by LDA. A support vector machine algorithm based on hybrid features is proposed. The algorithm has been verified by experiments and achieved ideal results.
© The Authors, published by EDP Sciences, 2018
This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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