基于环境振动的IR-UWB超感知范围人体跌倒检测方法  

Human Fall Detection Method Beyond the Sensing Range of IR-UWB Using Ambient Vibration

作　　者：王冬子 郭政鑫 桂林卿 盛碧云 蔡惠 肖甫 Wang Dongzi;Guo Zhengxin;Gui Linqing;Sheng Biyun;Cai Hui;Xiao Fu(School of Computer Science&Technology,Nanjing University of Posts and Telecommunications,Nanjing 210023;Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks(Nanjing University of Posts and Telecommunications),Nanjing 210023)

机构地区：[1]南京邮电大学计算机学院、软件学院、网络空间安全学院,南京210023 [2]江苏省无线传感网高技术研究重点实验室(南京邮电大学),南京210023

出　　处：《计算机研究与发展》2024年第11期3721-3738,共18页Journal of Computer Research and Development

基　　金：国家杰出青年科学基金项目(62125203);国家自然科学基金项目(61932013);江苏省重点研发计划(BE2022798)。

摘　　要：跌倒检测在老年人医疗保健中至关重要,传统方案主要依赖于可穿戴设备进行感知.为了避免可穿戴设备带来的负担和不适,采用射频(radio frequency,RF)的非接触式方法因其具有的普适性和非侵入性,逐渐成为一种有前景的替代方案.现有的非接触式方法主要从无线射频信号中提取人体跌倒产生的速度和加速度等运动生理特征,通过分析运动时间序列来判断目标是否发生跌倒行为.虽然目前的方法可以在视距状态下获取较高的检测精度,但是其在感知范围和非视距路径下的感知效果仍存在局限性.为解决以上问题,提出了利用最先进的商用IR-UWB设备来识别超感知范围外的人体跌倒检测方法.该方法的关键是通过识别感知范围外人体跌倒引发的环境振动特征来判断是否发生跌倒事件,并通过设计IQ熵和最远点对距离算法从微小振动中提取人体跌倒产生的信号特征.通过在商用IR-UWB设备上搭建UWFall原型系统并在各种环境下开展大量的实验测试,结果表明,单台收发器的UWFall系统识别准确率超过90%.同时,UWFall系统对7 m范围外的目标跌倒检测准确率超过86%,且在非视距场景下依然保持高鲁棒性.Fall detection is crucial in elderly healthcare,traditionally relying on wearable devices for sensing.To avoid the burden and discomfort caused by wearable devices,contact-free methods using radio frequency(RF)signals have emerged as a promising alternative due to their ubiquity and non-invasiveness.Existing contact-free methods predominantly extract physiological motion features,e.g.,the speed and acceleration of human falls from RF signals and analyze the motion time series to determine if a fall event has occurred.While current methods achieve high detection accuracy in line-of-sight(LoS)scenarios,they still face limitations in sensing range and non-light-of-sight(NLoS).To address this,we propose a method using the commercial off-the-shelf(COTS)impulse radio-ultra wideband(IR-UWB)devices to detect human falls beyond the sensing range.The key insight of our method is identifying ambient vibration features induced by falls outside the sensing range to determine fall events.By developing the IQ entropy and farthest points-pair distance algorithm,signal features from subtle vibrations caused by falls are extracted.We implement a UWFall prototype system built on COTS IR-UWB devices and conduct extensive experimental evaluations under various environments.The results demonstrate that UWFall system achieves a recognition accuracy over 90%with one single transceiver.Furthermore,the detection accuracy for falls beyond 7 meters exceeds 86%,and this system maintains high robustness in NLoS scenarios.

关 键 词：跌倒检测 射频感知 物联网 IR-UWB雷达 无线感知 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]