文章基本信息

标题：Research on Body Posture Classification Algorithm Based on Acceleration
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作者：Kaiyue Zhang ; Xiangbin Ye ; Jiulong Xiong 等
期刊名称：MATEC Web of Conferences
电子版ISSN：2261-236X
出版年度：2018
卷号：227
DOI：10.1051/matecconf/201822702019
语种：English
出版社：EDP Sciences
摘要：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.