可重构智能超表面辅助的非视距人体生命体征感知  

Non-Line-of-Sight Human Vital-Sign Sensing Aided by Reconfigurable Intelligent Surfaces

作　　者：李新羽 张静远 蔡子轩 秦世龙 马骞 游检卫[1] 崔铁军[1] LI Xin-yu;ZHANG Jing-yuan;CAI Zi-xuan;QIN Shi-long;MA Qian;YOU Jian-wei;CUI Tie-jun(School of Information Science and Engineering,Southeast University,Nanjing,Jiangsu 211189,China)

机构地区：[1]东南大学信息科学与工程学院,江苏南京211189

出　　处：《电子学报》2025年第1期1-13,共13页Acta Electronica Sinica

基　　金：国家重点研发计划(No.2023YFB3813100);国家自然科学基金(No.62101124,No.62301149,No.62288101);江苏省自然科学基金(No.BK20210209,No.BK20230820);111项目(No.111-2-05);东南大学科研启动基金(No.RF1028623244)。

摘　　要：本文提出非视距场景下的无接触式人体生命体征感知方法,将可重构智能超表面与人体无线感知技术相结合,利用可重构智能超表面对电磁波的灵活调控能力,实现有障碍物遮挡情况下的人体生命体征监测.本文首先通过视觉辅助机制,利用Yolo-v7深度学习模型,实现人体目标的定位.在此基础上,可重构智能超表面根据人体位置估计结果进行编码优化,进而改变感知信号传播路径,实现非视距场景下的人体感知;同时,本文针对传统变分模态分解算法在人体生命体征感知方面的不足,进一步提出一种基于滤波的变分模态分解算法,实现人体呼吸、心跳速率的精准估计.实验结果表明,视觉辅助模块可以准确定位人体胸腔所在位置,从而使可重构智能超表面能够精准调控电磁波束,使感知信号聚焦于人体.所提出的基于滤波的变分模态分解算法可以实现人体生命体征精准估计,其呼吸和心跳平均估计误差分别为0.6 RPM和5.3 BPM.与此同时,进一步分析与讨论也证明了基于可重构智能超表面的感知方案在非视距场景下进行人体生命体征感知的有效性和准确性.This paper proposes a contactless human vital-sign sensing method in non-line-of-sight(NLoS)scenarios,which integrates reconfigurable intelligent surfaces(RISs)into wireless human sensing,and achieves NLoS human vitalsign sensing by utilizing the flexible manipulation capability of RISs over electromagnetic waves.Firstly,through a visualaided mechanism,this paper locates human targets using the deep learning model Yolo-v7.Then,the metasurface optimizes the coding matrix based on the estimated human location,thereby altering the propagation path of sensing signals to achieve human sensing in non-line-of-sight scenarios.Additionally,addressing the shortcomings of traditional variational mode decomposition(VMD)algorithms in human vital-sign sensing,we further propose an improved VMD algorithm to achieve precise estimation of breathing rate and heartbeat rate.Experimental results demonstrate that the visual-aided module can accurately locate the position of human chest,thus enabling precise beamforming controlled by the intelligent metasurface.The proposed filtering-based VMD algorithm can achieve precise estimation of human vital signs,with average estimation errors of 0.6 RPM for respiration and 5.3 BPM for heartbeat,respectively.Furthermore,further analysis also demonstrates the effectiveness and accuracy of the RIS-based sensing scheme for human vital-sign sensing in NLoS scenarios.

关 键 词：可重构智能超表面 非视距感知 人体无线感知 生命体征探测 变态模式分解 视觉辅助 

分 类 号：TN929.533[电子电信—通信与信息系统]