Time-series Network Analysis for Detecting Cardiac Autonomic Neuropathy using RR Interval Data

Chandan Karmakar, Ahsan Khandoker, Herbert Jelinek, Marimuthu Palaniswami

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Cardiovascular autonomic neuropathy (CAN) is highly prevalent and a serious complication in patients with diabetes mellitus. In this study, we investigate the effect of changing the degree and data length on network properties (transition asymmetry and network efficiency)to differentiate negative CAN (NCAN) subjects from definite CAN (DCAN). Forty-one patients with Type 2 diabetes mellitus were included in the study: J 5 patients had definite CAN (DCAN), whilst the remaining 26 were negative for CAN (NCAN), being without clinical signs and symptoms of CAN. Symbolic Aggregate approximation (SAX) was used as the discretization procedure to convert the heart rate variability (HRV) time-series signal to network. The optimal degree (m) and data length (n) were found to be mopt = 270 and nopt = 200 respectively with leave-one-out accuracy of 85.37% using transition asymmetry (A(G)) and network efficiency (EF) indexes. Both, A(G) and EF indexes are found to be a potential parameter for detecting CAN in diabetes.
Original languageEnglish
Title of host publicationComputing in Cardiology 2013
Subtitle of host publicationVolume 40
Place of PublicationUnited States
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages4
ISBN (Electronic)9781479908868
ISBN (Print)9781479908844
Publication statusPublished - 2013
Event40th Computing in Cardiology Conference, CinC 2013
- School of Engineering (Betancourt Building), The University of Zaragoza, Zaragoza, Spain
Duration: 22 Sept 201325 Sept 2013
http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6695807 (Conference proceedings)
https://web.archive.org/web/20130825093106/http://cinc2013.org/ (Conference website)

Publication series

ISSN (Print)2325-8861


Conference40th Computing in Cardiology Conference, CinC 2013
OtherComputing in Cardiology provides an international forum for scientists and professionals from the fields of medicine, physics, engineering and computer science, and has been held annually since 1974.
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