Identification of cardiac autonomic neuropathy patients using cardioid based graph for ECG biometric

Khairul A. Sidek, Herbert Jelinek, Ibrahim Khalil

Research output: Book chapter/Published conference paperConference paperpeer-review

14 Citations (Scopus)


In this paper, the application of data mining applied on Cardioid based person identification mechanism using electrocardiogram (ECG) is presented. A total of 50 subjects with Cardiac Autonomic Neuropathy (CAN) were obtained from participants with diabetes from the Charles Sturt Diabetes Complication Screening Initiative (DiScRi).The patients can be categorised into two types of CAN which are early CAN and definite/severe CAN. Euclidean distances obtained as a result of the formation of the Cardioid based graph were used as extracted features. These distances were then applied in Multilayer Perceptron to confirm the identity of individuals. Our experimentation results suggest that person identification is possible by obtaining classification accuracies of 99.6% for patients with early CAN, 99.1% for patients with severe/definite CAN and 99.3% for all the CAN patients. This result indicates that ECG biometric is possible and QRS complex is not severely affected for individuals affected by CAN with the ability to identify and differentiate individuals.
Original languageEnglish
Title of host publicationComputing in Cardiology 2011
Subtitle of host publicationVolume 38
Place of PublicationUnited States
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages4
ISBN (Print)9781457706127
Publication statusPublished - 2011
Event38th Computing in Cardiology Conference, CinC 2011
- Zhejiang University, Hangzhou, China
Duration: 18 Sept 201121 Sept 2011 (Conference website) (Conference proceedings)

Publication series

ISSN (Print)0276-6574


Conference38th Computing in Cardiology Conference, CinC 2011
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.
Internet address


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