Motion detection using RF signals for the first responder in emergency operations: A PHASER project
Motion detection using RF signals for the first responder in emergency operations: A PHASER project
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DOI：
10.1109/pimrc.2013.6666161
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发表时间：
2013-11
期刊：
影响因子：
--
通讯作者：
Y. Geng;Jin Chen;K. Pahlavan
中科院分区：
文献类型：
--
作者：
Y. Geng;Jin Chen;K. Pahlavan
实时健康监护系统是提高消防员在恶劣危险环境中工作的安全性的一种很有前途的体域网络应用。除了对消防员的生理状态进行监测外，身体监测网络也可以作为运动检测和分类的候选解决方案。本文利用射频信号作为分类特征，实现了一种新的支持向量机分类器。该分类器能够对消防员站立、行走、奔跑、躺卧、爬行、攀登和跑上楼梯等七种常见动作进行检测和分类。该分类器的平均真实分类率达到87.9175%，并通过绘制接收器工作特性曲线分析了不同人体运动和传感器位置对分类结果的影响。
The real-time health monitoring system is a promising body area network application to enhance the safety of fire fighters when they are working in harsh and dangerous environment. Except for monitoring the physiological status of the fire fighters, on-body monitoring network can be also regarded as a candidate solution of motion detection and classification. In this paper, a novel Support Vector Machine (SVM) classifier has been implemented using RF signals as classification features. The classifier is capable of detecting and classifying seven frequently appeared motions of fire fighters including standing, walking, running, lying, crawling, climbing and running up stairs. The average true classification rate of our classifier reaches 87.9175% and the effects of different human motions and sensor locations have been analyzed by plotting Receiver Operating Characteristics (ROC) curves.