Remote human body posture monitoring system based on smart phone terminal

被引：0

作者：

Liu Y. ^{[1
]}

Hui H. ^{[1
]}

Lu Y. ^{[1
]}

Qi L. ^{[1
]}

Zou X. ^{[1
]}

Li R. ^{[1
]}

机构：

[1] Chongqing Engineering Research Center of Intelligent Sensing Technology and Microsystem, Chongqing University of Post and Telecommunications, Chongqing

来源：

Zhongguo Guanxing Jishu Xuebao/Journal of Chinese Inertial Technology | 2019年 / 27卷 / 06期

关键词：

Fall detection; Inertial sensor; Multiclassification identification; Smartphone terminal; Softmax regression;

D O I：

10.13695/j.cnki.12-1222/o3.2019.06.003

中图分类号：

学科分类号：

摘要：

In order to use the portable device to accurately monitor the fall of the elderly, a method of classifying and identifying multiple behavior patterns based on softmax regression is proposed, and a remote human posture monitoring system based on smart phone terminal is implemented. First, a softmax classifier is constructed to analyze the acceleration modulus characteristics under 8 daily behavior modes. Since the acceleration modulus during running is similar to that during a sudden fall, the inclination angle feature is introduced for secondary discrimination to identify the sudden fall behavior. Aiming at the problem that the acceleration modulus value characteristics are not obvious under the slow fall behavior, the lying-down time feature is introduced in the softmax classifier. The slow fall behavior is identified by setting the time threshold and judging whether the original position is recovered within the time threshold. Experiment and test results show that the accuracy, specificity and sensitivity of the system are 95.40%, 95.33%, and 95.50% respectively with high recognition accuracy for falling down behavior, which provides a feasible solution for the elderly's health monitoring. © 2019, Editorial Department of Journal of Chinese Inertial Technology. All right reserved.

引用

页码：713 / 718

页数：5

共 10 条

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