Key result
Nonlinear analysis of ECG R-R interval time-series was performed on 6 healthy individuals and 3 cardiac patients to calculate the largest Lyapunov exponent and correlation dimension.
Observational (n=9)
This study demonstrates the application of nonlinear analysis, including Lyapunov exponent and correlation dimension, to ECG R-R interval time-series in healthy and cardiac patients.
Nonlinear ECG metrics may differentiate states in small cohorts; leaves open clinical utility pending larger validation.
This article reports nonlinear analysis of ECG R-R interval time-series obtained from healthy individuals and some cardiac patients. The R-R interval time-series data from 6 healthy individuals and 3 cardiac patients were transformed into multidimensional phase-space vectors by time-delay embedding. The largest Lyapunov exponent and correlation dimension (CD) were calculated. Nonlinearity was tested by comparing the CDs obtained from the original data with those obtained from surrogate data sets. Results are discussed with reference to results obtained in previous studies.
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Uzun et al. (2005) conducted an observational in Healthy individuals and cardiac patients (n=9). Cardiac condition vs. Healthy individuals was evaluated on Largest Lyapunov exponent and correlation dimension (CD). Nonlinear analysis of ECG R-R interval time-series was performed on 6 healthy individuals and 3 cardiac patients to calculate the largest Lyapunov exponent and correlation dimension.
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