Institutional Repository of Coll Elect & Informat Engn
Coronary heart disease recognition based on dynamic pulse rate variability | |
Zhang, Aihua1![]() | |
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)
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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 | |
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. |
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