Browsing by Subject "Electrocardiography."
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Item Open Access Design and implementation of a PC-based heart rate variability and respiration recording system(2005) Korkmaz, Okay TuncaDetermination of the exact effects of respiration rate on the heart rate variability requires comprehensive experimental studies. In this context, these two quantities should be analyzed simultaneously. In this thesis, design and implementation of a new PC-based heart rate variability recording system with respiration is described. The respiration rate is detected by a thermocouple placed in a nasal tube, whereas a single-channel electrocardiogram (ECG) signal is recorded for heart rate variability analysis in the system. The PC-based data acquisition part, which was designed in compliance to patient safety standards, has a Universal Serial Bus (USB) interface. The speed of data acquisition and patient comfort during recording make the system advantageous. The HRVs of different patients in both spontaneous and controlled breathing conditions were analyzed after short-term recordings with the system. Differences were observed in both its time-domain parameters and power spectral components.Item Open Access Early diagnosis of acute coronary syndromes automatically by using features of ECG recordings = EKG kayıtlarının öznitelikleri kullanılarak akut koroner sendromların otomatik olarak erken teşhisi(2014) Terzi, Merve BegümIn patients with acute coronary syndrome, temporary chest pains together with changes in the ST/T sections of ECG occur shortly before the start of myocardial infarction. In order to diagnose acute coronary syndromes early, we propose a new technique which detects changes in the ST/T sections of ECG. For this purpose, by using real ECG recordings, we identify ECG features that are critical in the detection of acute coronary syndromes. By using support vector machines (SVM) operating with linear and radial basis function (RBF) kernels, we obtain classifiers that use 2 or 3 most discriminating features of the ST/T sections. To improve performance, classification results on multiple segments are fused. The obtained results over a considerable number of patients indicate that the proposed classification technique provides highly reliable detection of acute coronary syndromes. To develop a detection technique that can be used in the absence of unhealthy ECGs, we also investigate the detection of acute coronary syndromes based on ECG recordings of a patient obtained during healthy stage only. For this purpose, a Gaussian mixture model is used to represent the joint pdf of the selected features. Then, a Neyman-Pearson type of approach is developed to provide detection of outliers that would correspond to acute coronary syndromes.Item Open Access Effect of exercise on QT dispersion(1998) Özçakır, LütfüElectrocardiogram (ECG) is the measurement of potential differences occurring on the body due to the currents that flow on the heart during diastole and systole. Cardiac abnormalities cause uncommon current flows, leading to strange waveform morphologies in the recorded ECG. Since some abnormalities become visible in ECG only during activity, exercise ECG tests are conducted. Among all abnormalities, exercise induced ischemia is considered in this study. The previous studies have shown that exercise induced ischemia increases the QT dispersion (QTD). The patients in this study have been validated by cardiologists using ST segment analysis. However, the sensitivity and specifity of ST segment analysis is low. Some of the patients have been validated as ischemic using the coronary angiography results. A different method to measure the QT interval through out the exercise ECG test has been developed . The algorithm is designed to cope with the artifacts of exercise ECG. Such as high noise level and PT fusion. A different approach to obtain the QTD has been developed.We have shown that, QTD increases signiflcantly in patients who have ischemia during exercise. The sensitivity and specifity of exercise ECG test can be increased if QTD analysis is used as an additional tool to ST analysis.Item Open Access New techniques for ventricular repolarization and heart rate variability analyses(2000) Acar, BurakThis thesis is composed of two parts: i) Development of a fully automatic Heart Rate Variability (HRV) analysis method, and ii) development of new methods for ventricular repolarization (T wave) analysis. The first part of this study deals with fully automatic measurement of heart rate variability (HRV) in short term electrocardiograms. In short, HRV analysis is the spectral analysis of the heart rate signal. Presently, all existing HRV analysis programs require user intervention for ectopic beat identification which is essential for reliable HRV analysis. This makes HRV studies in large populations problematic. A fully automatic algorithm to discriminate ventricular and supra-ventricular ectopic beats from normal beats is pre.sented. The method incorporates several approaches and uses three EGG leads. It uses the template matching for the basic morphology check of the QRS complex and the P-wave, the timing information to avoid unnecessary computation and to adjust the thresholds and also looks for a special QRS morphology which is common in ventricular ectopic beats. The method is tested on a set of real ECG recordings and statistically analyzed on the basis of sensitivity and specificity. Its performance using single ECG leads and different triplets of EGG leads is also studied. We have obtained 99% specificity and SVE sensitivity and 98% VE sensitivity and thus concluded that fully automatic HRV analysis is feasible. The second part of this thesis is on ventricular repolarization analysis (T wave analysis). It has been shown that heterogeneity in ventricular repolarization is a mark of abnormality and can be used for risk stratification. Several methods have been proposed to measure this heterogeneity, among which the QT interval measurements are the most popular ones. After a short discussion of the existing methods, we propose three new approaches for T wave analysis, which are aimed to overcome the drawbacks of the existing methods: The spatial and temporal variations in the T wave morphology and the wavefront direction difference between the ventricular depolarization and repolarization waves. All of the descriptors are defined in an ECG decomposition space constructed by Singular Value Decomposition. The spatial variation characterizes the morphology differences between standard leads. The temporal variation measures the change in interlead relations throughout the T wave. The wavefront direction difference quantizes the difference between the progress of the two processes. None of them requires time domain measurements thus avoid the inaccuracies associated with conventional methods. The new methods are compared with the conventional ones in a set of 1100 normal ECGs. The short-term intra-subject reproducibility of the new and the conventional methods is compared in a set of 760 normal (recorded from 76 normal subjects) and 630 abnormal (recorded from 63 HGM patients) EGGs. The new descriptors’ ability to discriminate normal and abnormal EGGs (both in univariate and multivariate models) is also analyzed on the same data set. A two-way blind study conducted on a set of AMI (Acute Myocardial Infarction) patients have shown that the new methods are able to discriminate the high risk group. The conventional methods were shown to be useless in this patient group in a previous study. We have concluded that the new descriptors do not correlate with the conventional ones, are more reproducible, lead to more significant separation between normal and abnormal ECGs in both univariate and multivariate models.Item Open Access Online ECG signal orthogonalization based on singular value decomposition(1996) Acar, BurakElectrocardiogram (ECG) is the measurement of potential differences occurring on the body due to the currents that flow on the heart during diastole and systole. Cardiac abnormalities cause uncommon current flows, leading to strange waveform morphologies in the recorded ECG. Since some abnormalities become visible in ECG only during activity, exercise ECG tests are conducted. The sources of noise during an exercise test are electro myogram (EMG) due to increased muscle activity and baseline wander (BW) due to mechanical motion. Frequency band filtering, used to eliminate noise, is not an efficient method for filtering noise because usually frequency spectra of the interference and the ECG overlap. Rather, a fast morphological filter is required. This thesis is focused on an online filtering approach which separates noise and ECG signals without changing the morphology. The redundancy present in standard 12 lead ECG records is made operational by a Singular Value Decomposition based orthogonalization of the input signals. ECG is represented in a minimum dimensional space whose orthogonal complement takes on noise. The signals in this low dimensional space are used to reconstruct the input signals without noise. Noise elimination also improves data compression. A comparative study of the ST analysis of original and reconstructed signals is presented at the end.Item Open Access A rhythm analysis method for exercise electrocardiograms(1996) Çağlar, B KeremExercise electrocardiography (the exercise ECG test or the stress EGG test) is one of the most popular and the most important non-invasive diagnostic tests in the field of cardiovascular disease. Arrhythmia analysis is an important part of the exercise ECG. A new approach to arrhythmia analysis is proposed in this thesis. 12 lead ECG signal is first reduced into three orthogonal channels which contain all the power of ECG. The orthogonalization process, an online Singular Value Decomposition (SVD) algorithm, maintains that these channels are free from both baseline wander and EMG noise. The third output channel has very low power with respect to first two. Making use of the orthogonality of these new channels. Total Power Signal (TPS) is calculated by summing the squares of orthogonalized channels. Employing the first two channels in TPS yields 92-99% of ECG power contained in all channels. Any arrhythmic behaviour during exercise test effects the TPS. In order to obtain the fiducial points of QRS complex first derivative of TPS is calculated. The method is compared with an algorithm proposed previously. The method and the algorithm are tested on 22 complete stress ECG test each with a duration between 9.5 to 26.5 minutes.Item Open Access Significance of QT dispersion as a diagnosis tool for cardiac patients(2000) Ben Ahmed Jemel, NabilElectrocardiogram (EGG) is the recorded electrical potentials generated by the heart during a cardiac cycle. Gardiac abnormalities cause unknown current flows leading to strange waveform morphologies in the recorded EGG. Some of these abnormalities are only visible when the heart is under stress. Exercise EGG is conducted for this reason. Ischemia is one of the important cardiac abnormalities and is the focus of our study. It occurs when a part of the heart tissue dies or is injured. QT dispersion (QTd) is a proposed method for diagnosing Ischemia. The classical deflnition for QTd is the difference between the maximum and the minimum QT intervals within the 12 leads. In this study the effect of exercise on QT dispersion (QTd) is studied and whether QTd could give significant information for diagnosing patients with ischemic heart disease is investigated. A new method for measuring QT interval is developed and is compared with previous methods. QTd is measured on average beats calculated for 10 seconds intervals throughout the exercise ECG test and a trend curve which we call QTd, is generated. Several decision rules for the diagnosis of cardiac patients are proposed by analyzing these QTd trend curves and the accompanying heart rate curves. It is shown that despite the improvement in QT interval measurements, none of the decision rules proved to be a clinically useful discriminate of cardiac patients, with sufficient confidence.