A novel technique for analysing beat-to-beat dynamical changes of QT-RR distribution for arrhythmia prediction

Imam, Mohammad Hasan, Karmakar, Chandan, Khandoker, Ahsan and Palaniswami, Marimuthu 2015, A novel technique for analysing beat-to-beat dynamical changes of QT-RR distribution for arrhythmia prediction, in CinC 2015: 42nd Computing in Cardiology Proceedings, IEEE, Piscataway, N.J., pp. 1157-1160, doi: 10.1109/CIC.2015.7411121.

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Title A novel technique for analysing beat-to-beat dynamical changes of QT-RR distribution for arrhythmia prediction
Author(s) Imam, Mohammad Hasan
Karmakar, ChandanORCID iD for Karmakar, Chandan orcid.org/0000-0003-1814-0856
Khandoker, Ahsan
Palaniswami, Marimuthu
Conference name Computing in Cardiology Conference (42nd: 2015: Nice, France)
Conference location Nice, France
Conference dates 6-9 Sep. 2015
Title of proceedings CinC 2015: 42nd Computing in Cardiology Proceedings
Publication date 2015
Start page 1157
End page 1160
Total pages 4
Publisher IEEE
Place of publication Piscataway, N.J.
Keyword(s) Science & Technology
Technology
Computer Science, Interdisciplinary Applications
Engineering, Multidisciplinary
Engineering, Biomedical
Computer Science
Engineering
Summary Ventricular tachycardia (VT) leading to ventricular fibrillation (VF) is the major cause of sudden cardiac death (SCD) with subjects with or without any history of cardiac disease. Prediction of the initiation of ventricular fibrillation is crucial for both successful preventive measure and effective defibrillation therapy. A lot of studies have been done based on electrocardiogram (ECG) waveform analysis for VF detection but this field still needs more perfection. Both HRV and QTV related parameters were reported to be analysed for VT/VF detection and prediction with inconsistent results in different populations. In this study, we propose a novel time domain measurement tool to detect the pattern of dynamical changes of both RR and QT intervals in subjects having sustained VT/VF episodes form VFDB and AHA database (www.physionet.org). We also analyse the same pattern in some healthy subjects from Fantasia database and compare the distribution of patterns between healthy and VT/VF subjects. Our findings showed that the distribution of QT-RR dynamics are statistically significantly different (p<0.05) in healthy subjects from VT/VF in particular before the start of VF episode. Therefore, distribution of change in QT-RR dynamics may provide insight of the underlying instability before VF events and can be used for better prediction of arhythmogenesis.
ISBN 9781509006854
ISSN 2325-8861
2325-887X
Language eng
DOI 10.1109/CIC.2015.7411121
Field of Research 110201 Cardiology (incl Cardiovascular Diseases)
080109 Pattern Recognition and Data Mining
Socio Economic Objective 920102 Cancer and Related Disorders
HERDC Research category E2.1 Full written paper - non-refereed / Abstract reviewed
ERA Research output type E Conference publication
Copyright notice ©2015, CCAL
Persistent URL http://hdl.handle.net/10536/DRO/DU:30084902

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