Coronary heart disease recognition based on dynamic pulse rate variability

doi:10.1007/978-3-319-42291-6_4

	Coronary heart disease recognition based on dynamic pulse rate variability
	Zhang, Aihua1 ; Wei, Boxuan 1; Chou, Yongxin 2
	2016
会议名称	12th International Conference on Intelligent Computing Theories and Application, ICIC 2016
会议录名称	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
卷号	9771
页码	28-38
会议日期	August 2, 2016 - August 5, 2016
会议地点	Lanzhou, China
出版地	GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND
出版者	Springer Verlag
摘要	Objective: In order to improve the accuracy and real-time of coronary heart disease (CHD) recognition, we propose a new method to analyze the pulse signal with the idea of sliding window iterative. Methods: Firstly, the principle of the feature extraction method(including time domain method, Poincare plot and information entropy) that combined with the idea of sliding window iterative is described. Secondly, The continuous blood pressure signals from the website database PhysioNet are chosen to generate the dynamic pulse rate variability (DPRV) signal as experimental data, and the linear and nonlinear feature is selected for classifying the healthy people and patients with CHD. Finally, the running time and accuracy of the method in this paper are comparaed with other methods. Result: The pulse signal can be online analyzed by this method. The average recognizing accuracy is 97.6%. Conclusion: This methods is entirely feasible. Compared with existing methods, its accuracy and real-time is higher. © Springer International Publishing Switzerland 2016.
关键词	Biomedical signal processing Blood pressure Cardiology Classification (of information) Computation theory Diseases Heart Intelligent computing Iterative methods Blood pressure signals Coronary heart disease Feature extraction methods Information entropy Nonlinear features Pulse rate variability Pulse signal Time-domain methods
DOI	10.1007/978-3-319-42291-6_4
收录类别	EI
语种	英语
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence ; Computer Science, Information Systems ; Computer Science, Theory & Methods
WOS记录号	WOS:000387430300004
EI入藏号	20163002641466
EI主题词	Time domain analysis
ISSN	03029743
来源库	Compendex
分类代码	461 Bioengineering and Biology - 716.1 Information Theory and Signal Processing - 721.1 Computer Theory, Includes Formal Logic, Automata Theory, Switching Theory, Programming Theory - 723.4 Artificial Intelligence - 921 Mathematics - 921.6 Numerical Methods
引用统计	被引频次：1[WOS] [WOS记录] [WOS相关记录]
文献类型	会议论文
条目标识符	https://ir.lut.edu.cn/handle/2XXMBERH/117505
专题	电气工程与信息工程学院
通讯作者	Zhang, Aihua
作者单位	1.Lanzhou Univ Technol, Coll Elect & Informat Engn, Lanzhou 730050, Peoples R China 2.Changshu Inst Technol, Sch Elect & Automat Engn, Changshu 215500, Peoples R China
第一作者单位	电气工程与信息工程学院
通讯作者单位	电气工程与信息工程学院
推荐引用方式 GB/T 7714	Zhang, Aihua,Wei, Boxuan,Chou, Yongxin. Coronary heart disease recognition based on dynamic pulse rate variability[C]. GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND:Springer Verlag,2016:28-38.