Novel application of multi dynamic trend analysis as a sensitive tool for detecting the effects of aging and congestive heart failure on heart rate variability

Yu Cheng Lin, Yu Hsuan Lin, Men Tzung Lo, Chung Kang Peng, Norden E. Huang, Cheryl C.H. Yang, Terry B.J. Kuo

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number023109
JournalChaos
Volume26
Issue number2
DOIs
Publication statusPublished - Feb 1 2016
Externally publishedYes

Fingerprint

trend analysis
Congestive Heart Failure
Trend Analysis
Heart Rate Variability
heart rate
Dynamic Analysis
Dynamic analysis
Aging of materials
Fluctuations
Cardiac
Curve
curves
Deviation
Hilbert-Huang Transform
frequency domain analysis
Frequency Domain Analysis
deviation
Time Domain Analysis
time domain analysis
Sliding Window

ASJC Scopus subject areas

  • Statistical and Nonlinear Physics
  • Mathematical Physics
  • Physics and Astronomy(all)
  • Applied Mathematics

Cite this

Novel application of multi dynamic trend analysis as a sensitive tool for detecting the effects of aging and congestive heart failure on heart rate variability. / Lin, Yu Cheng; Lin, Yu Hsuan; Lo, Men Tzung; Peng, Chung Kang; Huang, Norden E.; Yang, Cheryl C.H.; Kuo, Terry B.J.

In: Chaos, Vol. 26, No. 2, 023109, 01.02.2016.

Research output: Contribution to journalArticle

Lin, Yu Cheng ; Lin, Yu Hsuan ; Lo, Men Tzung ; Peng, Chung Kang ; Huang, Norden E. ; Yang, Cheryl C.H. ; Kuo, Terry B.J. / Novel application of multi dynamic trend analysis as a sensitive tool for detecting the effects of aging and congestive heart failure on heart rate variability. In: Chaos. 2016 ; Vol. 26, No. 2.
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