Journal
ANNALS OF BIOMEDICAL ENGINEERING
Volume 38, Issue 3, Pages 854-864Publisher
SPRINGER
DOI: 10.1007/s10439-009-9863-2
Keywords
Heart rate variability; Cardiovascular system; Multiscale analysis; Scale-dependent Lyapunov exponent
Categories
Funding
- NSF [CMMI-0825311, 0826119]
- Directorate For Engineering
- Div Of Civil, Mechanical, & Manufact Inn [0826119] Funding Source: National Science Foundation
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Heart rate variability (HRV) is an important dynamical variable of the cardiovascular function. There have been numerous efforts to determine whether HRV dynamics are chaotic or random, and whether certain complexity measures are capable of distinguishing healthy subjects from patients with certain cardiac disease. In this study, we employ a new multiscale complexity measure, the scale-dependent Lyapunov exponent (SDLE), to characterize the relative importance of nonlinear, chaotic, and stochastic dynamics in HRV of healthy, congestive heart failure (CHF), and atrial fibrillation subjects. We show that while HRV data of all these three types are mostly stochastic, the stochasticity is different among the three groups. Furthermore, we show that for the purpose of distinguishing healthy subjects from patients with CHF, features derived from SDLE are more effective than other complexity measures such as the Hurst parameter, the sample entropy, and the multiscale entropy.
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