Analysing cardiac autonomic neuropathy in diabetes using electrocardiogram derived systolic-diastolic interval interactions

Mohammad Hasan Imam, Chandan Karmakar, Ahsan Khandoker, Herbert F. Jelinek, Marimuthu Palaniswami

Research output: Contribution to journalConference articlepeer-review

4 Scopus citations


Systole and diastole are the fundamental periods of the cardiac cycle and their relative duration is used to evaluate heart function in various physiological and pathological conditions. In clinical practice, systolicdiastolic interval is generally measured using echocardiography. However, recent studies have shown that the QT and TQ intervals of the electrocardiogram (ECG) signal can be used as surrogate systolic and diastolic intervals respectively and the ratio of beat-tobeat QT-TQ intervals can be used as the systolic-diastolic interval interaction (SDI) parameter. In this study, we propose a new parameter, beat-to-beat TQ-RR ratio, to investigate the SDI. Performance of both QT-TQ and TQRR based SDI measures were analyzed using a case study to detect and monitor the progression of cardiac autonomic neuropathy (CAN) in diabetes. ECGs recorded in supine resting condition of 72 diabetic subjects with no CAN (CAN-) and 70 diabetic subjects with CAN were analyzed in this study. Fifty-five subjects of the CAN group had early level of CAN (ECAN) and 15 subjects were at the severe or definite stage of CAN (DCAN). The results show that variability of the TQ-RR based SDI measure can significantly (p<0.001) differentiate all three groups (CAN-, ECAN and DCAN) and the level of CAN. In contrast, the variability of the QT-TQ based SDI measures showed significant difference only between CAN-and DCAN groups. This result suggested that TQRR based SDI analysis was more sensitive in tracking progression of CAN than the QT-TQ based approach, which is crucial for the early detection of CAN.

Original languageBritish English
Article number7042985
Pages (from-to)85-88
Number of pages4
JournalComputing in Cardiology
Issue numberJanuary
StatePublished - 2014
Event41st Computing in Cardiology Conference, CinC 2014 - Cambridge, United States
Duration: 7 Sep 201410 Sep 2014


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