Detection of cardiac autonomic neuropathy using linear parametric modeling of QT dynamics

M.H Imam, C. Karmakar, A. Khandoker, Herbert Jelinek, M. Palaniswami

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

1 Citation (Scopus)
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In this study a linear parametric modeling technique is applied to model ventricular repolarisation (QT) variability from heart rate variability (RR) and respiration to investigate the change in cardiovascular system complexity in diabetes patients with cardiac autonomic neuropathy (CAN+) and without (CAN-). ECGs were recorded from 32 participants (20 CAN- and 12 CAN+), whilst in a supine resting position for 20 minutes and linear parametric autoregressive models using the first 250 beats were analysed. Models developed from the ECG derived respiration information could explain the QT-RR dynamics better than the models designed without any respiration information and may improve classification of CAN. QT-RR interaction provides useful information about cardiovascular system dynamics and autonomic nervous system modulation and ventricular repolarization on heart rate and heart rate variability.
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 (Conference proceedings) (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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