基于连续小波变换的多数据心率提取方法
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摘要
针对多普勒雷达生命体征检测时强谐波干扰问题,提出一种基于连续小波变换特征提取的改进方法。首先,针对特征信号选择多组不同时间长度的数据集;然后,在小波域分别进行连续小波变换。根据频谱峰值位置是否与数据时间长度相关,识别呼吸信号、呼吸谐波和心跳信号提取心率信息,并对频率分辨率进行分析。实验结果表明:采用文中提出的方法利用4 s～5 s的数据即可检测出心率,当频率分辨率要求为0.1 Hz时,该方法在有效消除谐波和快速识别心率方面得到了较为满意的效果。
Aiming at the problem of strong harmonic interference in vital signs detection based on Doppler radar, an improved method based on continuous wavelet transform(CWT) feature extraction is proposed. First, multiple sets of data sets with different time lengths are selected for the feature signal, and then CWT is performed in the wavelet domain. Respiratory signals, respiratory harmonics, and heartbeat signals are identified based on whether or not the spectral peak position is independent of the length of the data. On this basis, the heart rate(HR) is extracted and the frequency resolution is analyzed. Experimental result shows that the heartbeat signal can be quickly detected by using the method proposed in this paper using data from 4 s to 5 s. When the frequency resolution requirement is 0.1 Hz, the multi-data HR extraction method has relatively satisfactory results in effectively eliminating harmonics and quickly identifying the heartbeat signal.
Aiming at the problem of strong harmonic interference in vital signs detection based on Doppler radar, an improved method based on continuous wavelet transform(CWT) feature extraction is proposed. First, multiple sets of data sets with different time lengths are selected for the feature signal, and then CWT is performed in the wavelet domain. Respiratory signals, respiratory harmonics, and heartbeat signals are identified based on whether or not the spectral peak position is independent of the length of the data. On this basis, the heart rate(HR) is extracted and the frequency resolution is analyzed. Experimental result shows that the heartbeat signal can be quickly detected by using the method proposed in this paper using data from 4 s to 5 s. When the frequency resolution requirement is 0.1 Hz, the multi-data HR extraction method has relatively satisfactory results in effectively eliminating harmonics and quickly identifying the heartbeat signal.
引文
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[12] TARIQ A,CHAFOURI-SHIRAZ H.Vital signs detection using Doppler radar and continuous wavelet transform[C]// Proceedings of the 5th European Conference on Antennas and Propagation (EUCAP).Rome:IEEE Press,2011:285-288.
[13] 行正世,谢永亮,刘正奇.基于小波变换低信噪比下的雷达目标提取[J].现代雷达,2015,37(5):47-48.XING Zhengshi,XIE Yongliang,LIU Zhengqi.Detection of low signal-noise ratio target based on wavelet transform[J].Modern Radar,2015,37(5):47-48.
[14] TARIQ A,CHAFOURI-SHIRAZ H.Noncontact heart rate monitoring using Doppler radar and continuous wavelet transform[J].Microwave & Optical Technology Letters,2011,53(8):1793-1797.
[2] CHEN K M,HUANG Y,ZHANG J P,et al.Microwave life-detection systems for searching human-subjects under earthquake rubble or behind barrier[J].IEEE Transactions on Biomedical Engineering,2000,47(1):105-114.
[3] LI C Z,LIN J S,XIAO Y M.Robust overnight monitoring of human vital signs by a non-contact respiration and heartbeat detector[C]//IEEE EMBS Annual International Conference.New York:IEEE Press,2006:2235-2238.
[4] 胡巍.基于多普勒雷达的非接触式生命体征检测技术研究[D].合肥:中国科学技术大学,2014.HU Wei.Non-contact vital sign detection based on Doppler radar[D].Hefei:University of Science and Technology of China,2014.
[5] SINGH M,RAMACHANDRAN G.Reconstruction of sequential cardiac in-plane displacement patterns on the chest wall by laser speckle interferometry[J].IEEE Transactions on Biomedical Engineering,1991,38(5):483-489.
[6] 史林,姜敏,黄莉.基于谐波模型的生命探测雷达人体状态识别方法[J].西安电子科技大学学报(自然科学版),2005,32(2):179-183.SHI Lin,JIANG Ming,HUANG Li.Human status recognition method for the life detection radar based on the harmonic model[J].Journal of Xidian University (Natural Science Edition),2005,32(2):179-183.
[7] PARK B K,BORIC-LUBECKE O,LUBECKE V M.Arctangent demodulation with DC offset compensation in quadrature Doppler radar receiver systems[J].IEEE Transactions on Microwave Theory Technology,2007,55(5):1073-1079.
[8] LI C Z,LIN J S.Complex signal demodulation and random body movement cancellation techniques for non-contact vital sign detection[C]//IEEE MTT-S International Microwave Symposium Digest.Atlanta,CA:IEEE Press,2008:567-570.
[9] TU J X,LIN J S.Respiration harmonics cancellation for accurate heart rate measurement in non-contact vital sign detection[C]// IEEE MTT-S International Microwave Symposium Digest.Seattle,WA:IEEE Press,2013:1-3.
[10] 甄蜀春,张善文,赵兴录.低信噪比下的一种信号检测方法[J].现代雷达,2001,23(5):32-33.ZHEN Shuchun,ZHANG Shanwen,ZHAO Xinglu.A method of detecting signal embedded in strong jamming[J].Modern Radar,2001,23(5):32-33.
[11] LU X Q,LIU H D,KANG J W,et al.Wavelet frequency spectrum and its application in analyzing an oscillating chemical system[J].Analytica Chimica Acta,2003,484(2):201-210.
[12] TARIQ A,CHAFOURI-SHIRAZ H.Vital signs detection using Doppler radar and continuous wavelet transform[C]// Proceedings of the 5th European Conference on Antennas and Propagation (EUCAP).Rome:IEEE Press,2011:285-288.
[13] 行正世,谢永亮,刘正奇.基于小波变换低信噪比下的雷达目标提取[J].现代雷达,2015,37(5):47-48.XING Zhengshi,XIE Yongliang,LIU Zhengqi.Detection of low signal-noise ratio target based on wavelet transform[J].Modern Radar,2015,37(5):47-48.
[14] TARIQ A,CHAFOURI-SHIRAZ H.Noncontact heart rate monitoring using Doppler radar and continuous wavelet transform[J].Microwave & Optical Technology Letters,2011,53(8):1793-1797.