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|Title:||Computerised extraction and analysis of data from medical records: An examination of qt dispersion in the electrocardiogram.|
|Authors:||Bhullar, Harsangeet K.|
|Presented at:||University of Leicester|
|Abstract:||The first part of this Ph.D. thesis describes the significance and basis of QT dispersion in the light of recent clinical findings. A system is then described which was developed for the analysis of QT dispersion using standard twelve lead Electrocardiogram (ECG) paper records. In the first part of the system, ECG records are scanned and stored on computer as '.PCX' files. These files are pre-processed to remove random noise using a set of heuristic rules. An image processing technique known as 'thinning' is used to retrieve the lineal structure of the ECG waveforms. Digital data values are then extracted from these 'thinned' waveforms. The data recovery system was validated by a series of tests one of which showed that the cross-correlation coefficient between original and digitised data was greater than 0.99. A graphical interface incorporating a patient data base was designed to allow for the display and user-interactive measurement (using a cursor) of the recovered waveforms. The next part of the thesis describes the design of an 'automatic algorithm' for the detection of characteristic points of the ECG including the QRS onset, R wave peak and T wave end positions. A transformed signal which is the three-point averaged derivative of the ECG is used to detect significant areas of QRS activity. Peaks corresponding to the R waves are detected and the ECG waveforms are then segmented as a function of heart rate. A normalised threshold is found and used to detect the QRS onset position. T wave peak and end detection is carried out by the study of "area maps" in the transformed signal. Once area maps corresponding to the T wave are determined, the T wave end is detected by using a three point moving average window and a threshold which takes into account the T wave slope. Manual, user-interactive and automatic measurements revealed that (i) the user-interactive system measurements were easily performed by cardiologists and this technique resulted in more accurate and reproducible measurements than the standard manual method; and (ii) values of QT and RR intervals obtained by the automatic algorithm agreed well with measurements made by ten physicians. The final part of the study attempted to find a suitable parameter to characterise QT dispersion. The importance of QT dispersion was then investigated by undertaking a clinical study, whose results supported the value of QT dispersion as a risk indicator of patients prone to ventricular arrhythmias. Use of the automatic algorithm in finding QT dispersion gave the best discrimination of patient groups.|
|Rights:||Copyright © the author. All rights reserved.|
|Appears in Collections:||Theses, Dept. of Engineering|
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