期刊文献+

由心电信号提取呼吸信息的算法及其仿真实现 被引量:2

Study and Simulated Implementation of ECG-Derived Respiratory Algorithm
在线阅读 下载PDF
导出
摘要 为了使单纯的心电监护设备实现对多种生理信号的检测,减小设备的复杂性,根据心跳频率和呼吸频率处在不同的频段,提出2种由心电信号提取呼吸信息(ECG-derived respiratory signal,EDR)的算法:离散傅里叶变换EDR算法和离散小波变换EDR算法.利用MATLAB软件在时域和频域分别对这2种算法进行验证,并进行了相关分析比较.经过筛选比较,离散小波变换EDR算法选用coifN小波作为母小波.仿真结果表明,文中所提出的2种算法均能有效地从心电信号中提取出呼吸信息,但离散小波变换EDR算法的准确性与母小波的选取有很大关系,当选取coif3小波时,离散小波变换EDR算法比离散傅立叶变换EDR算法更为有效. To realize a host of biological signal detection by a simple ECG monitoring equipment, and reduce the complexity of it, two EDR (ECG-derived Respiratory) algorithms are proposed aiming to extract respiratory informa- tion from ECG in accordance with the frequency of heartbeat and respiration in different frequency bands. They are the discrete Fourier transform EDR algorithm and the discrete Wavelet transform EDR algorithm. The simulation ex- periment, the comparison and the correlation analysis of these two algorithms were performed in time domain and fre- quency domain by the MATLAB software. For the discrete Wavelet transform EDR algorithm, coifN Wavelet was se- lected as the mother Wavelet, which has better performance. The experimental results showed that both algorithms can effectively extract respiratory information from the ECG, but the accuracy of the discrete Wavelet transform EDR al- gorithm has much to do with the mother Wavelet. When the coif3 Wavelet is selected, the discrete Wavelet transform EDR algorithm is more effective than the discrete Fourier transform EDR algorithm.
出处 《南通大学学报(自然科学版)》 CAS 2014年第1期12-17,共6页 Journal of Nantong University(Natural Science Edition) 
基金 江苏省"六大人才高峰"项目(2010-WLW-006) 江苏高校优势学科建设工程资助项目 江苏省高校科研成果产业化推进项目(JHB2011-45) 上海市信息安全综合管理技术研究重点实验室开放课题(AGK2009006) 南通市应用研究计划项目(K2010028 BK2011011)
关键词 心电信号 呼吸信息 傅里叶变换 小波变换 仿真 算法 ECG respiration information discrete Fourier transform discrete Wavelet transform simulation algorithm
  • 相关文献

参考文献13

  • 1Moody G B, Mark R G, Zoccola A, et al. Derivation of res- piratory signals from multi-lead ECGs [C]//Proceedings of IEEE International Conference on Computers in Cardiology. Washington, DC: IEEE Xplore, 1985 : 113-116.
  • 2Wang R C, Calvert T W. A model to estimate respirationfrom vectorcardiogram measurements[J]. Annals of Biomed- ical Engineering, 1974, 2(1 ) :47-57.
  • 3Bailon R, Sornmo L, Laguna P. A robust method for ECG- based estimation of the respiratory frequency during stress testing [C ]. IEEE Transactions on Biomedical Engineering, 2006, 53(7) : 1273-1285.
  • 4邓宝芸,潘燕,孟延,刘兵,孙文红,张玉华,戚焰,李桥.基于心电和脉搏波数据融合的呼吸率估计[J].中国生物医学工程学报,2012,31(2):211-216. 被引量:8
  • 5Orphanidou C, Fleming S, Shah S A, et al. Data fusion for estimating respiratory rate from a single-lead ECG [J]. Bio- medical Signal Processing and Control, 2013, 8(1 ) :98-105.
  • 6Zhao Yanna, Zhao Jie, Li Qun. Derivation of respiratory signals from single-lead ECG[C]//Proceedings of 2008 International Seminar on Future BioMedical Information Engineering, Dec 18-18, 2008, Wuhan, Hubie. New York : IEEE Xplore, 2008 : 15-18.
  • 7魏宝琴,李白萍.最优小波基的选取原则[J].甘肃科技,2007,23(10):42-43. 被引量:14
  • 8伯晓晨,李涛,刘路,等.Matlab工具箱应用指南:信息工程篇[M].北京:电子工业出版社,2000:328-331.
  • 9MIT-BIH Polysomnographic Database [DB/OL]. (2000-07- 13) [2013-02-12]. http://www, physionet, org/physiobank/ database/slpdb.
  • 10金天融,俞衡,严荣国,颜国正,郭旭东.MATLAB环境中生物医学信号采集与处理的应用[J].计算机应用与软件,2010,27(8):26-28. 被引量:4

二级参考文献23

共引文献75

同被引文献19

引证文献2

二级引证文献5

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部