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-  2016 

基于心率变异性分析的睡眠分期方法研究

DOI: doi:10.7507/1001-5515.20160071

Keywords: 心率变异性, 主成分分析, 支持向量机, 睡眠分期

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Abstract:

为实现对不同阶段睡眠的快速、便捷分期,本文实验分析了心率变异性(HRV)与睡眠分期的相关性,利用支持向量机(SVM)实现了基于HRV信息的睡眠自动分期的算法。对天津市胸科医院的33例临床心电数据进行了R-R提取和主成分分析(PCA),并利用SVM对睡眠中的不同阶段进行建模和预测,将分期的预测结果与基于脑电金标准的睡眠分期标注结果比对,对于三期睡眠的预测准确度超过80%,说明HRV与睡眠各期具有良好的相关性。该方法是对传统睡眠分期方法的一种补充,具有实际使用价值

References

[1]  1. GJORESKI H, RASHKOVSKA A, KOZINA S A, et al. Telehealth using ECG sensor and accelerometer[C]//201437th International Convention on Information and Communication Technology, Electronics And Microelectronics (MIPRO). Opatija:2014:270-274.
[2]  2. LEE J, JUNG J, LEE J, et al. Diagnostic device for acute cardiac disease using ECG and accelerometer[C]//2014 International Conference on Information Science and Applications (ICISA). Seoul:2014:1-3.
[3]  3. KABIR M A, SHAHNAZ C. Denoising of ECG signals based on noise reduction algorithms in EMD and wavelet domains[J]. Biomed Signal Process Control, 2012, 7(5) :481-489.
[4]  4. RECHTSCHAFFEN A, KALES A A. A manual of standardized terminology, techniques and scoring system for sleep stages of human subjects[M]. Washington:U.S. Dept. Health, Education and Welfare, 1968.
[5]  5. 张宏金, 杨军,俞梦孙,等.微动敏感床垫式睡眠监测系统与多导睡眠图的比较研究[J].实用诊断与治疗杂志,2004,18(6) :476-478.
[6]  6. ZHAO Zhidong, MA Chan. A novel cancellation method of power line interference in ECG signal based on EMD and adaptive filter[C]//11th IEEE International Conference on Communication Technology, 2008. ICCT 2008. Hangzhou:2008:517-520.
[7]  7. AGRAWAL S, GUPTA A. Fractal and EMD based removal of baseline wander and powerline interference from ECG signals[J]. Comput Biol Med, 2013, 43(11) :1889-1899.
[8]  8. PAN J, TOMPKINS W J. A real-time QRS detection algorithm[J]. IEEE Trans Biomed Eng, 1985, 32(3) :230-236.
[9]  9. 李延军, 宏峰,严洪,等.在轨睡眠质量评价的研究进展[J].航天医学与医学工程,2012,25(6) :458-462.
[10]  10. CAFFAREL J, GIBSON G J, HARRISON J P, et al. Comparison of manual sleep staging with automated neural network-based analysis in clinical practice[J]. Med Biol Eng Comput, 2006, 44(1-2) :105-110.
[11]  11. KIRSCH M R, MONAHAN K, WENG J, et al. Entropy-based measures for quantifying sleep-stage transition dynamics:relationship to sleep fragmentation and daytime sleepiness[J]. IEEE Trans Biomed Eng, 2012, 59(3) :787-796.
[12]  12. JIA R T, LIU B. Human daily activity recognition by fusing accelerometer and multi-lead ECG data[C]//2013 IEEE International Conference on Signal Processing, Communication and Computing (ICSPCC). Kunming:2013:1-4.
[13]  13. ZHANG Zhengbo, Silva I, WU Dalei, et al. Adaptive motion artefact reduction in respiration and ECG signals for wearable healthcare monitoring systems[J]. Medical & Biological Engineering & Computing, 2014, 52(12) :1019-1030.
[14]  14. ALTIMIRAS J. Understanding autonomic sympathovagal balance from short-term heart rate variations. Are we analyzing noise?[J] Comparative Biochemistry and Physiology Part A, 1999, 124(4) :447-460.
[15]  15. BOOTSMA M, SWENNE C A, VAN BOLHUIS H H, et al. Heart rate and heart rate variability as indexes of sympathovagal balance[J]. Am J Physiol, 1994, 266(4 Pt 2) :H1565-H1571.
[16]  16. GOLDBERGER A L. Is the normal heartbeat chaotic or homeostatic?[J]. News Physiol Sci, 1991, 6:87-91.
[17]  17. VANOLI E, ADAMSON P B, BA-LIN, et al. Heart rate variability during specific sleep stages. A comparison of healthy subjects with patients after myocardial infarction[J]. Circulation, 1995, 91(7) :1918-1922.
[18]  18. BRANDENBERGER G, EHRHART J, PIQUARD F, et al. Inverse coupling between ultradian oscillations in delta wave activity and heart rate variability during sleep[J]. Clin Neurophysiol, 2001, 112(6) :992-996.
[19]  19. OTZENBERGER H, SIMON C, GRONFIER C, et al. Temporal relationship between dynamic heart rate variability and electroencephalographic activity during sleep in man[J]. Neurosci Lett, 1997, 229(3) :173-176.
[20]  20. ALDREDGE J L, WELCH A J. Variations of heart rate during sleep as a fucntion of the sleep cycle[J]. Electroencephalogr Clin Neurophysiol, 1973, 35(2) :193-198.
[21]  21. 江朝晖, 李继伟,冯焕清,等.R-R间期分析与睡眠分期[J].生物医学工程研究,2003,22(3) :17-20.
[22]  22. 庄志, 高上凯,高小榕.基于心率变异分析的睡眠分期方法[J].生物医学工程学杂志,2006,23(3) :499-504.
[23]  23. 尚志刚, 张建华.生物医学数据分析及其MATLAB实现[M].北京:北京大学出版社,2009.
[24]  24. 张学工. 基于统计学习理论的支持向量机算法研究[J].自动化学报,2000,78(1) :32-42.
[25]  25. 艾娜, 吴作伟,任江华.支持向量机与人工神经网络[J].山东理工大学学报:自然科学版,2005,19(5) :45-49.

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