Adaptive Time-Frequency Interbeat
In this paper, we address the nonstationary problem to analyze the cardiovascular control system based on beatto-beat heart rate variability (HRV) time series. A novelty information here is to perform HRV time-frequency analysis without a priori knowledge of nonstationarity. This is achieved by adaptive interactions that will decompose the HRV signal in sub-signals with well-defined time-frequency parameters. These may be used to reconstruct the signal in sub-bands or might be used in screening tests. To validate our method, we carried out the experiments with both artificial and real HRV intervals. As an application test, we consider a simple case of screening, where experiments with a database consisting of beat-to-beat samples derived from 20 normal and 15 cardiac heart failures (CHF) yielded an overall classification accuracy of 98.33％.
Fausto Lucena Yoshinori Takeuchi Noboru Ohnishi Allan Kardec Barros Yoshihiro Fujiwara
Nagoya University Graduate School of Information Science Furo-cho, Chikusa-ku, Nagoya, JPN 464–8603 Federal University of Maranh.ao Department of Electrical Engineering S.ao Luis, MA, BRA 65075.460 Aichi Medical University Department of Anesthesiology Yazako Nagakute, Aichi, JPN 480–1195
国际会议
上海
英文
2056-2059
2008-05-16（万方平台首次上网日期，不代表论文的发表时间）