American Institute of Physics;United States: American Institute of Physics
摘要:
摘要： The complex fluctuations in heart rate variability (HRV) reflect cardiac autonomic modulation and are an indicator of congestive heart failure (CHF). This paper proposes a novel nonlinear approach to HRV investigation, the multi dynamic trend analysis (MDTA) method, based on the empirical mode decomposition algorithm of the Hilbert–Huang transform combined with a variable-sized sliding-window method. Electrocardiographic signal data obtained from the PhysioNet database were used. These data were from subjects with CHF (mean age = 59.4 ± 8.4), an age-matched elderly healthy control group (59.3 ± 10.6), and a healthy young group (30.3 ± 4.8); the HRVs of these subjects were processed using the MDTA method, time domain analysis, and frequency domain analysis. Among all HRV parameters, the MDTA absolute value slope (MDTS) and MDTA deviation (MDTD) exhibited the greatest area under the curve (AUC) of the receiver operating characteristics in distinguishing between the CHF group and the healthy controls (AUC = 1.000) and between the healthy elderly subject group and the young subject group (AUC = 0.834 ± 0.067 for MDTS; 0.837 ± 0.066 for MDTD). The CHF subjects presented with lower MDTA indices than those of the healthy elderly subject group. Furthermore, the healthy elderly subjects exhibited lower MDTA indices than those of the young controls. The MDTA method can adaptively and automatically identify the intrinsic fluctuation on variable temporal and spatial scales when investigating complex fluctuations in the cardiac autonomic regulation effects of aging and CHF. 其他題名： Chaos 出版者： United States: American Institute of Physics 出版日期： 2016-02 出處： Chaos (Woodbury, N.Y.), 2016-02, Vol.26 (2), p.023109 資源來源： AIP Publishing Journals 版權： AIP Publishing LLC 版權： 2016 AIP Publishing LLC. 識別號： ISSN: 1054-1500 識別號： EISSN: 1089-7682 識別號： DOI: 10.1063/1.4941673 識別號： PMID: 26931590 識別號： CODEN: CHAOEH
