Modified Distribution Entropy as a Complexity Measure of Heart Rate Variability (HRV) Signal

The complexity of a heart rate variability (HRV) signal is considered an important nonlinear feature to detect cardiac abnormalities. This work aims at explaining the physiological meaning of a recently developed complexity measurement method, namely, distribution entropy ([Formula: see text]), in the context of HRV signal analysis. We thereby propose modified distribution entropy ([Formula: see text]) to remove the physiological discrepancy involved in the computation of [Formula: see text]. The proposed method generates a distance matrix that is devoid of over-exerted multi-lag signal changes. Restricted element selection in the distance matrix makes “ [Formula: see text] ” a computationally inexpensive and physiologically more relevant complexity measure in comparison to [Formula: see text].