兰州理工大学学报

兰州理工大学学报 ›› 2025, Vol. 51 ›› Issue (5): 100-106.

• 自动化技术与计算机技术 • 上一篇    下一篇

遮蔽环境下基于ITVFEMD的人体生命体征提取

黄玲*1,2,3, 李欣欣1, 姚璐媛1   

  1. 1.兰州理工大学 微电子现代产业学院, 甘肃 兰州 730050;
    2.兰州理工大学 甘肃省工业过程先进重点实验室, 甘肃 兰州 730050;
    3.兰州理工大学 电气与控制工程国家级实验教学示范中心, 甘肃 兰州 730050
  • 收稿日期:2023-02-21 发布日期:2025-10-25
  • 通讯作者: 黄 玲(1976-),女,甘肃武威人,博士,教授,博导. Email:hlfighting@163.com
  • 基金资助:
    甘肃省自然科学基金重点项目(25JRRA062),甘肃省产业支撑计划(2025CYZC-029),甘肃省重点人才项目(2025RCXM022)

Extraction of human vital signs based on ITVFEMD in sheltered environment

HUANG Ling1,2,3, LI Xin-xin1, YAO Lu-yuan1   

  1. 1. School of Microelectronics Industry-Education Integration, Lanzhou University of Technology, Lanzhou 730050, China;
    2. Key Lab of Advanced Control for Industrial Process in Gansu Province, Lanzhou University of Technology, Lanzhou 730050, China;
    3. National Demonstration Center for Experimental Electrical and Control Engineering Education, Lanzhou University of Technology, Lanzhou 730050, China
  • Received:2023-02-21 Published:2025-10-25

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摘要： 为了解决遮蔽环境中雷达回波信号低信噪比以及人体心跳信号被呼吸谐波以及其他杂波淹没的问题,联合提出一种基于改进奇异值分解(ISVD)的降噪方法和基于改进的时变滤波经验模态分解(ITVFEMD)的生命体征提取方法.该方法首先利用改进的奇异值分解算法对雷达回波信号进行信号预处理,然后对预处理后的回波信号进行基于参数优化的时变滤波经验模态分解,最后选取合适的IMF分量进行呼吸心跳信号的重构,并对重构的呼吸和心跳信号进行FFT得到估计的呼吸心跳信号频率,再将估计的呼吸心跳频率与佩戴血氧仪实际测量的呼吸率和心率进行数据一致性分析,结果表明,心率和呼吸率的估计准确率分别达到了95%和98%以上.

关键词: 遮蔽环境, ITVFEMD, 生命体征提取

Abstract: In order to solve the problem of low signal-to-noise ratio for radar echo signals in a sheltered environment and the masking of human heartbeat signal by respiratory harmonics and other clutter, a noise reduction method based on improved singular value decomposition (ISVD) and a vital signs extraction method based on improved time-varying filtering empirical mode decomposition (ITVFEMD) is proposed. First, the radar echo signals are preprocessed using the improved singular value decomposition algorithm. Subsequently, the preprocessed signals undergo parameter-optimized ITVFEMD to decompose the signal into intrinsic mode functions (IMFs). Appropriate IMFs are then selected to reconstruct the respiratory and heartbeat signals. The reconstructed signals are analyzed via Fast Fourier Transform (FFT) to estimate the corresponding respiratory and heartbeat frequencies. Finally, the estimated frequencies are compared with ground truth data obtained from a pulse oximeter for consistency analysis. Experimental results show that the proposed method achieves estimation accuracies of over 95% for heart rate and 98% for respiratory rate.

Key words: sheltered environment, ITVFEMD, vital signs extraction

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