A Comparison of Nonlinear Measures for the Detection of Cardiac Autonomic Neuropathy from Heart Rate Variability

Entropy

David Cornforth¹  Herbert F. Jelinek³  Mika Tarvainen² 

[1] Applied Informatics Research Group, Faculty of Science and IT, University of Newcastle, Newcastle, NSW 2308, Australia;University of Eastern Finland, Kuopio 70210, Finland; E-Mail:;Centre for Research in Complex Systems, School of Community Health, Charles Sturt University, Albury, NSW 2640, Australia; E-mail:

关键词: multiscale entropy;    multi fractal detrended fluctuation analysis;    Renyi entropy;    heart rate variability;    cardiac autonomic neuropathy;    disease discrimination;   

DOI  :  10.3390/e17031425

来源: mdpi

【 摘 要 】

In this work we compare three multiscale measures for their ability to discriminate between participants having cardiac autonomic neuropathy (CAN) and aged controls. CAN is a disease that involves nerve damage leading to an abnormal control of heart rate, so one would expect disease progression to manifest in changes to heart rate variability (HRV). We applied multiscale entropy (MSE), multi fractal detrended fluctuation analysis (MFDFA), and Renyi entropy (RE) to recorded datasets of RR intervals. The latter measure provided the best separation (lowest p-value in Mann–Whitney tests) between classes of participants having CAN, early CAN or no CAN (controls). This comparison suggests the efficacy of RE as a measure for diagnosis of CAN and its progression, when compared to the other multiscale measures.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland