Distinguishing healthy subjects from patients with congestive heart failure using scale-dependent Lyapunov ezponent

摘要：

Heart rate variability (HRV) time series is highly nonlinear and nonstationary. To effectively characterize its complexity, we employ a newly developed multiscale complexity measure, the scale-dependent Lyapunov exponent (SDLE). We derive two readily computable features from the SDLE and show that they can readily distinguish healthy subjects from patients with congestive heart failure (CHF). The same task is evaluated using other complexity measures, including the Hurst parameter, the sample entropy, and the multiscale entropy. It is shown that for the purpose of distinguishing healthy subjects from patients with CHF, the features derived from the SDLE are much more effective than the Hurst parameter, the sample entropy, and the multiscale entropy.

作者: Jing Hu Jianbo Gao Wen-wen Tung Xingsong Wang Yinghui Hu Yinhe Cao

作者单位: Department of Electrical and Computer Engineering University of Florida Gainesville, FL 32611 Department of Earth and Atmospheric Sciences Purdue University West Lafayette, IN 47907 School of Mechanical Engineering Southeast University Nanjing, 211189 P.R. China College of Medicine, Nanchang University, Fuzhou Branch Fuzhou, Jiangxi, 344000, China BioSieve, 1026 Springfield Drive Campbell, CA 95008

会议类型: 国际会议

会议名称: The 2nd International Conference on Bioinformatics and Biomedical Engineering(iCBBE 2008)(第二届生物信息与生物医学工程国际会议)

会议地点: 上海

会议语种:英文

页码: 498-501

在线出版日期: 2008-05-16（万方平台首次上网日期，不代表论文的发表时间）