南京大学学报(自然科学版) ›› 2022, Vol. 58 ›› Issue (4): 680–688.doi: 10.13232/j.cnki.jnju.2022.04.012

• • 上一篇    

基于改进变分模态分解的生命体征检测

韩宇, 张兴敢()   

  1. 南京大学电子科学与工程学院，南京，210023
  • 收稿日期:2022-04-28 出版日期:2022-07-30 发布日期:2022-08-01
  • 通讯作者: 张兴敢 E-mail:zhxg@nju.edu.cn
  • 基金资助:
    国家自然科学基金(61976113)

Vital signs detection based on improved variational mode decomposition

Yu Han, Xinggan Zhang()   

  1. School of Electronic Science and Engineering, Nanjing University, Nanjing, 210023, China
  • Received:2022-04-28 Online:2022-07-30 Published:2022-08-01
  • Contact: Xinggan Zhang E-mail:zhxg@nju.edu.cn

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摘要：

变分模态分解方法常被用于生命体征信号检测，针对该方法模态个数确定存在主观性的问题，提出一种改进变分模态分解方法进行非接触式测量生命体征信号.利用毫米波雷达获得生命体征回波信号，经过降噪、目标距离单元定位等处理获得生命体征信号.生命体征信号成分主要包括心跳与呼吸信号.其中心跳信号能量小，受呼吸信号影响大，本方法利用余量与模态分量重构信号的自相关系数确定最优分解模态数量，避免了模态数量的过分解和欠分解，达到自适应分离生命体征信号的目的.实验结果表明，与变分模态分解方法相比，该方法可自适应确定模态分解个数.

关键词: 生命体征检测, 毫米波雷达, 变分模态, 模态分解

Abstract:

Variational modal decomposition method is often used for vital sign signal detection. Aiming at the problem of subjectivity in determining the number of modes in this method,this paper proposes an improved variational modal decomposition method for non?contact measurement of vital sign signals. Here,the millimeter wave radar is used to obtain the vital sign echo signal,and the vital sign signal is obtained through noise reduction,target distance unit positioning and other processing. The vital sign signal components mainly include heartbeat and respiration signals. Among them,the energy of the heartbeat signal is small and is greatly affected by the breathing signal. The method proposed uses the autocorrelation coefficient of the residual and modal components to reconstruct the signal to determine the optimal number of decomposed modes,which avoids over?decomposition and under?decomposition of the number of modes. The purpose of adaptively separating vital sign signals is achieved. The experimental results show that,compared with the variational modal decomposition method,the proposed method can adaptively determine the number of modal decompositions.

Key words: vital signs detection, millimeter wave radar, variational modes, mode decomposition

中图分类号: 

  • TN958

表1

体征信号相关指标"

体征信号频率（Hz）幅度（mm）
呼吸速率（成人）0.1~0.51~12
心跳速率（成人）0.8~3.00.1~0.5

图1

原始雷达回波信号(a)回波脉冲三维距离像；(b)回波脉冲二维距离像"

图2

去除静态杂波后的雷达回波信号(a)回波脉冲三维距离像；(b)回波脉冲二维距离像"

图3

相位处理波形(a)相位展开前；(b)相位展开后；(c)相位展开差分后；(d)相位展开差分中值滤波后"

图4

建模呼吸信号时域波形图(a)建模呼吸信号；(b)建模心跳信号"

图5

合成信号时域图"

图6

EMD分离结果"

图7

VMD分离结果"

图8

处理后的相位信号幅频图"

表2

AWR1642参数"

参数值备注
开始距离（m）0.3被预测目标的开始和结束距离，程序会搜索范围内最大峰值，并假设该峰值对应受试者位置
结束距离（m）0.9
距离单元长度（m）0.0337一个距离单元的间隔长度
接收天线1要处理的接收天线数量，当前实现来自单个接收天线数据
采样频率Fs（Hz）20每1 s在慢时间采样20个点

表3

不同分解模式数量下余量与模式重构信号的互相关系数"

模式数量k=2k=3k=4
归一化互相关系数0.160.100.13

图9

VMD分离后各模式时域及频域波形"

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