Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/85192
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dc.contributor.advisorBaumert, Mathiasen
dc.contributor.advisorAbbott, Dereken
dc.contributor.authorHasan, Muhammad Asrafulen
dc.date.issued2014en
dc.identifier.urihttp://hdl.handle.net/2440/85192-
dc.description.abstractThe human heart is a significant research topic in biomedical engineering due to the high incidence of heart disease in the developing world. Electrocardiography (ECG) is considered the primary diagnostic tool for the assessment of cardiac diseases and various heart arrhythmias. Note that ECG is the electrical representation of heart activity and can be recorded noninvasively by placing electrodes on the limbs and chest of the body. It is stated that certain heart diseases affect depolarization and repolarization. While the entire depolarization and repolarization of the heart is important, there is significant interest in the study and investigation of the ventricular depolarization and repolarization that is reflected by QT interval duration. The main reason for studying ventricular depolarization and repolarization is that some cardiac diseases, which are associated with ventricles of the heart, have an immediate effect on the body and can cause sudden cardiac death. Further, the knowledge of ventricular activation sequence and its abnormalities has contributed to our understanding of cardiac arrhythmias, but the underlying mechanisms and role of repolarization abnormalities is still not completely known. Therefore, this thesis presents several studies to explain more about the instability of repolarization duration in various cardiac patients by analysing different QT parameters. The main results of the thesis are: (i) Beat-to-beat QT interval variability (QTV) varies between the 12 standard ECG leads and caution should be paid when comparing beat-to-beat QTV results obtained from different leads across studies. (ii) The inter-lead correlation of beat-to-beat QTV is lead dependent. (iii) A negative correlation exists between beat-to-beat QTV and T-wave amplitude. (iv) No significant effect of mean heart rate, age and gender on beat-to-beat QTV in 12-lead resting ECG in healthy subjects. (v) An improved ECG-preprocessing technique is introduced and recommended for accurate measurement of beat-to-beat QTV. It substitutes the R-peak detection algorithm and implements an efficient baseline removal algorithm in the existing template matching approach. (vi) Effects of T-wave amplitude and ECG lead on beat-to-beat QTV in patients with Myocardial Infarction (MI) compared to healthy subjects are studied and suggest that increased beat-to-beat QTV in patients with MI is partly due to the lower T-wave amplitudes and some other unknown reason. (vii) The study also confirms that patients with MI have lower heart rate variability (HRV) compared to healthy subjects. (viii) Moreover, beat-to-beat QTV remains higher in patients with MI even after controlling the T-wave amplitudes. (ix) Two new beat-to-beat VCG (vectorcardiography) descriptors that have independent diagnostic attributes for assessing patient populations are introduced. (x) Overall spatial and temporal VCG descriptors may provide markers of electrical instability in the heart of patients with MI but need further research for the quantification and analysis of beat-to-beat VCG descriptors. (xi) Effect of pacing and pharmacologically induced autonomic nervous system modulation on VCG parameters and on beat-to-beat QTV is limited in heart failure patients. In addition to this, the thesis offers an introductory background and overview chapter revolving around repolarization lability. The results should be taken into account in further studies, so that the beat-to-beat variations of QT interval in ECG parameters and VCG descriptors can be utilized more effectively in clinical applications.en
dc.subjectECG signal processing; QT interval; QT interval variability; heart rate variability; vectorcardiographyen
dc.titleAnalysis of beat-to-beat QT interval variability in 12-lead ECG signals.en
dc.typeThesisen
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen
dc.provenanceThis electronic version is made publicly available by the University of Adelaide in accordance with its open access policy for student theses. Copyright in this thesis remains with the author. This thesis may incorporate third party material which has been used by the author pursuant to Fair Dealing exceptions. If you are the owner of any included third party copyright material you wish to be removed from this electronic version, please complete the take down form located at: http://www.adelaide.edu.au/legalsen
dc.description.dissertationThesis (Ph.D.) -- University of Adelaide, School of Electrical and Electronic Engineering, 2014en
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