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

Entropy

Marimuthu Palaniswami¹  Peng Li²  Xinpei Wang³  Radhagayathri Udhayakumar⁴  Chandan Karmakar⁴ 

[1] Department of Electrical & Electronic Engineering, The University of Melbourne, Melbourne 3010, Australia;Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA;School of Control Science and Engineering, Shandong University, Jinan 250100, China;School of Information Technology, Deakin University, 75 Pigdons Road, Waurn Ponds, Geelong, VIC 3216, Australia;

关键词: distribution entropy;    complexity analysis;    heart rate variability;    Shannon entropy;   

DOI  :  10.3390/e22101077

来源: DOAJ

【 摘 要 】

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 ($DistEn$), in the context of HRV signal analysis. We thereby propose modified distribution entropy ($mDistEn$) to remove the physiological discrepancy involved in the computation of $DistEn$. 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 “$mDistEn$” a computationally inexpensive and physiologically more relevant complexity measure in comparison to $DistEn$.

【 授权许可】

Unknown