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作 者:琚泽东 黄晓红 Ju Zedong;Huang Xiaohong(College of Artificial Intelligence,North China University of Science and Technology,Tangshan 063210,China)
出 处:《电子测量技术》2022年第16期27-33,共7页Electronic Measurement Technology
基 金:河北省教育厅科技基础研究项目(自然科学)(JQN2019006);河北省高等学校科学技术重点研究项目(ZD2020152)资助。
摘 要:毫米波雷达测量生命体征技术具有重大医用价值,然而呼吸谐波和人体随机移动信号作为噪声信号的一种,严重影响了心跳频率的提取。针对上述问题,根据不同呼吸方式的特点提出了一种多检测点信号分离技术与自适应噪声抵消算法相结合的方法测量动态目标心率,完成实验测试。该方法先通过77 GHz调频毫米波雷达同时测量待测者胸部和腹部微动信号,再利用新提出的基于胸部和腹部的多检测点信号分离技术分离胸部和腹部基带信号,之后通过自适应噪声抵消算法消除噪声信号,最后对心跳信号进行频谱分析得到心跳频率。实验表明,在人体随机移动状态下,该方法可以有效消除噪声信号干扰,且单一目标多次测量实验中测量心率的误差率仅为1.19%,较多通道卡尔曼平滑器方法降低了0.97%。The technology of measuring vital signs by millimeter wave radar has great medical value.However,as a kind of noise signal,respiratory harmonics and human random movement signal seriously affect the extraction of heart rate.In order to solve the above problems,proposes a method of measuring dynamic target heart rate based on multi-detection signal separation technology and adaptive noise cancellation algorithm according to the characteristics of different breathing modes.The method comprises the following steps of:simultaneously measuring chest and abdominal micro-motion signals of a person to be measured by using a 77 GHz frequency modulation millimeter wave radar;separating the chest and abdominal baseband signals by using a newly proposed multi-detection point signal separation technology based on the chest and the abdomen;eliminating noise signals by using an adaptive noise cancellation algorithm;and performing frequency spectrum analysis on heartbeat signals to obtain a heartbeat frequency.Experiments show that the method can effectively eliminate the noise signal interference in the state of human random movement,and the error rate of heart rate measurement is only 1.19%in multiple measurement experiments of a single target,which is 0.97%lower than that of multi-channel Kalman smoother method.
关 键 词:毫米波雷达 呼吸谐波 人体随机移动 心跳频率 多检测点信号分离 自适应噪声抵消
分 类 号:TP391[自动化与计算机技术—计算机应用技术]
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