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基于压缩采样脉搏信号的抗运动干扰心率提取算法 被引量:4

Heart Rate Extraction Algorithm of Anti-motion Interference Based on Compressive Sampled Photoplethysmography Signals
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摘要 针对使用脉搏信号进行长时间心率监测时存在高功耗和易受运动伪迹影响的问题,提出一种从压缩采样脉搏信号中提取心率的算法。利用Lomb-Scargle周期图法从压缩采样的脉搏信号和未压缩的加速度信号中提取频谱,采用最小二乘谱减法获得差分谱。在此基础上,通过谱峰追踪得到心率估计值。实验结果表明,在25倍压缩率下,与TROIKA算法相比,该算法能够降低功耗,且具有较强的抗干扰性和较好的心率估计性能。 Aiming at the problem of high power consumption and vulnerability to motion artifacts for long-term heart rate monitoring using pulse signals,an algorithm for extracting heart rate from compressed sampled pulse signals is proposed.The Lomb-Scargle spectral analysis method is used to extract the spectrum from the compressed sampled pulse signal and the uncompressed acceleration signal.The least squares spectrum subtraction method is used to obtain the differential spectrum.On this basis,the heart rate estimation is obtained by spectral peak tracking.Experimental results show that compared with TROIKA algorithm,the algorithm can reduce power consumption,has strong anti-interference and better heart rate estimation performance at 25 times compression ratio.
作者 张爱华 胡憬韬 贾彬彬 ZHANG Aihua;HU Jingtao;JIA Binbin(College of Electrical and Information Engineering,Lanzhou University of Technology,Lanzhou 730050,China;Key Laboratory of Gansu Advanced Control for Industrial Processes,Lanzhou University of Technology,Lanzhou 730050,China;National Demonstration Center for Experimental Electrical and Control Engineering Education,Lanzhou University of Technology,Lanzhou 730050,China)
出处 《计算机工程》 CAS CSCD 北大核心 2019年第4期302-306,310,共6页 Computer Engineering
基金 国家自然科学基金(81360229) 甘肃省自然科学基金(1610RJYA007) 甘肃省基础研究创新群体项目(1506RJIA031)
关键词 压缩采样 脉搏信号 运动伪迹 谱减法 心率估计 compressive sample photoplethysmography motion artifact spectrum subtraction heart rate estimation
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  • 1李小鹰,王洁,何耀,范利.老年周围动脉硬化闭塞病与心血管疾病的关系——北京万寿路地区老年人群横断面调查[J].中华医学杂志,2003,83(21):1847-1851. 被引量:36
  • 2李立明,饶克勤,孔灵芝,姚崇华,向红丁,翟凤英,马冠生,杨晓光,中国居民营养与健康状况调查技术执行组.中国居民2002年营养与健康状况调查[J].中华流行病学杂志,2005,26(7):478-484. 被引量:1783
  • 3Donoho D L.Compressed Sensing[J].IEEE Trans.on Infor- mation Theory, 2006, 52(4): 1289-1306.
  • 4Candes E J.Compressive Sampling[C]//Proc.of the Inter- national Congress of Mathematics.Madrid, Spain: European Mathematical Society Publishing House, 2006.
  • 5Candes E, Romberg J, Tao T.Stable Signal Cecovery from Incomplete and Inaccurate Measurements[J].Communications on Pure and Applied Mathematics, 2006, 59(8): 1207-1223.
  • 6Do T T, Gan Lu, Nguyen N, et al.Sparsity Adaptive Matching Pursuit Algorithm for Practical Compressed Sensing[C]//Proc.of the 42nd Asilomar Conference on Signals, Systems, and Computers.Pacific Grove, USA: [s.n.], 2008.
  • 7Mallat S, Zhang Zhifeng.Matching Pursuit with Time- frequency Dictionaries[J].IEEE Trans.on Signal Processing, 1993, 41(12): 3397-3415.
  • 8Tropp J, Gilbert A.Signal Recovery from Random Measure- ments via Orthogonal Matching Pursuit[J].IEEE Trans.on Information Theory, 2007, 53(12): 4655-4666.
  • 9Needell D, Vershynin D.Uniform Uncertainty Principle and Signal Recovery via Regularized Orthogonal Matching Pursuit[J].Foundations of Computational Mathematics, 2009, 9(3): 317-334.
  • 10Needell D, Tropp J A.CoSaMP: Iterative Signal Recovery form Incomplete and Inaccurate Samples[J].Applied and Computational Harmonic Analysis, 2008, 26(3): 301-321.

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