Nonlinear Analysis of Heart Rate Variability: Fractal and Complexity Measures of Heart Rate Behavior

Many new methods of analyzing heart rate (HR) variability have been developed to describe the features in HR behavior that cannot be detected by traditional time‐ and frequency‐domain methods. Some of the new methods, such as analysis of fractal correlation properties and complexity of HR dynamics, have provided clinically useful information in various patient populations. Importantly, some fractal analysis methods are better risk predictors of mortality than traditional HR variability measures, and analysis of complexity of HR dynamics has been shown to predict the spontaneous onset of atrial fibrillation. New analysis methods based on nonlinear dynamics are a promising tool for better understanding of normal and abnormal HR behavior. More work will be needed to establish the clinical applicability of traditional and new analysis methods of HR variability.