Browsing by Subject "Electrocardiography"

Now showing 1 - 9 of 9

Open Access
Akut koroner sendromların otomatik ST/T sınıflandırıcısı ile erken tanısı
(IEEE, 2014-10) Terzi, M. Begüm; Arıkan, Orhan; Abacı, A.; Candemir, M.; Dedoğlu, Mehmet
In patients with acute coronary syndrome, temporary chest pains together with changes in ECG ST segment and T wave occur shortly before the start of myocardial infarction. In order to diagnose acute coronary syndromes early, a new technique which detects changes in ECG ST/T sections is developed. As a result of implementing the developed technique to real ECG recordings, it is shown that the proposed technique provides reliable detections. Therefore, the developed technique is expected to provide early diagnosis of acute coronary syndromes which will lead to a significant decrease in heart failure and mortality rates. © 2014 IEEE.
Open Access
Assessment of information redundancy in ECG signals
(IEEE, 1997-09) Acar, Burak; Özçakır, Lütfü; Köymen, Hayrettin
In this paper, the morphological information redundancy in standard 12 lead ECG channels is studied. Study is based on decomposing the ECG channels into orthogonal channels by an SVD based algorithm and then reconstructing them. Then 7 of 8 independently recorded ECG channels are decomposed and the missing channel is reconstructed from these orthogonal channels. Thus the unique morphological information content of each ECG channel is assessed through the loss of clinical information in the reconstructed signal. A comparison of the clinical parameters measured from the reconstructed and original ECG is reported.
Open Access
Concept of T-wave morphology dispersion
(IEEE, 1999) Acar, Burak; Yi, G.; Malik, M.
The detection of ventricular repolarization abnormalities is widely being done using the QT interval measurements. However, there are both technical and theoretical problems with QT measurements. We propose two robust methods for the quantification of the ventricular repolarization abnormalities: i) The quantification of the inter-lead morphology differences of the T wave (T Wave Morphology Dispersion - TMD) ii) The analysis of the T wave wavefront direction with respect to the QRS complex (Total Cosine R_To_T - TCRT). Sensitivity and specificity of 82% (84%) in supine position and 77% (79%) in standing position were achieved for TMD (TCRT). Both parameters were more reproducible than conventional QT interval based parameters.
Open Access
Ischemic stroke phenotype in patients with nonsustained atrial fibrillation
(Lippincott Williams and Wilkins, 2015) Arsava, E. M.; Bas, D. F.; Atalar, Ergin; Has, A. C.; Oguz, K. K.; Topcuoglu, M. A.
Background and Purpose: The widespread use of ambulatory cardiac monitoring has not only increased the detection of high-risk arrhythmias like persistent and paroxysmal atrial fibrillation (AF), but also made it possible to identify other aberrations such as short-lasting (<30 seconds) irregular runs of supraventricular tachycardia. Ischemic stroke phenotype might be helpful in understanding whether these nonsustained episodes play a similar role in stroke pathophysiology like their persistent and paroxysmal counterparts. Methods: In a consecutive series of patients with ischemic stroke, we retrospectively determined clinical and imaging features associated with nonsustained AF (n=126), defined as <30-second-lasting supraventricular tachyarrhythmias with irregular RR interval on 24-hour Holter monitoring, and compared them to patients with persistent/paroxysmal AF (n=239) and no AF (n=246). Results: Patients with persistent/paroxysmal AF significantly differed from patients with nonsustained AF by a higher prevalence of female sex (odds ratio [95% confidence interval], 1.8 [1.1-2.9]), coronary artery disease (1.9 [1.1-3.0]), and embolic imaging features (2.7 [1.1-6.5]), and lower frequency of smoking (0.4 [0.2-0.8]) and hyperlipidemia (0.5 [0.3-0.8]). In contrast, patients with no AF were younger (0.5 [0.4-0.6] per decade) and more likely to be male (1.7 [1.0-2.8]) in comparison with nonsustained AF population. The prevalence of nonsustained AF was similar among cryptogenic and noncryptogenic stroke patients (32% versus 29%). Voxel-wise comparison of lesion probability maps revealed no significant difference between cryptogenic stroke patients with and without nonsustained AF. Conclusions: Clinical features of patients with nonsustained AF exhibited an intermediary phenotype in between patients with persistent/paroxysmal AF and no AF. Furthermore, imaging features did not entirely resemble patterns observed in patients with longer durations of AF.
Open Access
Model based analysis of the variation in Korotkoff sound onset time during exercise
(Institute of Physics Publishing, 2001) Türkmen, A.; Ider, Y. Z.
In this study, a minimal mathematical model of the cardiovascular system is used to study the effects of changes in arterial compliance and cardiac contractility on the onset time of Korotkoff sounds during an auscultatory procedure. The model provides blood pressure waveforms in the ventricle, the aorta and the brachial artery. From these waveforms, pre-ejection time, pulse propagation time and rise time of the blood pressure at the brachial artery can be computed. The time delay between onset time of ECG Q wave and onset time of Korotkoff sound is the sum of these three times. Rise time is zero and the time delay is minimal when the cuff pressure is slightly above the diastolic pressure. This minimum time delay is represented by QKD. Simulation results suggest that during the Bruce exercise protocol QKD decreases to one-third of its pre-exercise value if the cardiac contractility increases threefold. The effect of arterial compliance is not as significant as that of the cardiac contractility. From data recorded during an exercise test, it is observed that QKD decreases considerably as the test load is increased. We show in this study that the amount of decrease in QKD can be used as an index of the amount of increase in cardiac contractility during an exercise ECG test. Use of signal averaging for reducing the effect of motion artifacts during an exercise test is also shown to be very instrumental for making accurate QKD measurements.
Open Access
Online exercise ECG signal orthogonalization
(1996) Acar, B.; Köymen H.
In this paper an efficient method of making use of the redundancy in standard 12 lead ECG signals to eliminate noise is described. The method is based on orthogonalization via online Singular Value Decomposition (SVD). Its application as a filter to remove EMG noise and baseline wander are explained. A comparative study of ST analysis results of original and processed exercise ECG data is reported.
Open Access
Supervised machine learning algorithm for arrhythmia analysis
(IEEE, 1997) Güvenir, H. Altay; Acar, Burak; Demiröz, Gülşen; Çekin, A.
A new machine learning algorithm for the diagnosis of cardiac arrhythmia from standard 12 lead ECG recordings is presented. The algorithm is called VFI5 for Voting Feature Intervals. VFI5 is a supervised and inductive learning algorithm for inducing classification knowledge from examples. The input to VFI5 is a training set of records. Each record contains clinical measurements, from ECG signals and some other information such as sex, age, and weight, along with the decision of an expert cardiologist. The knowledge representation is based on a recent technique called Feature Intervals, where a concept is represented by the projections of the training cases on each feature separately. Classification in VFI5 is based on a majority voting among the class predictions made by each feature separately. The comparison of the VFI5 algorithm indicates that it outperforms other standard algorithms such as Naive Bayesian and Nearest Neighbor classifiers.
Open Access
SVD-based on-line exercise ECG signal orthogonalization
(Institute of Electrical and Electronics Engineers, 1999-03) Acar, B.; Köymen, Hayrettin
An orthogonalization method to eliminate unwanted signal components in standard 12-lead exercise electrocardiograms (ECG's) is presented in this work. A singular-value-decomposition-based algorithm is proposed to decompose the signal into two time-orthogonal subspaces; one containing the ECG and the other containing artifacts like baseline wander and electromyogram. The method makes use of redundancy in 12-lead ECG. The same method is also tested for reconstruction of a completely lost channel. The online implementation of the method is given. It is observed that the first two decomposed channels with highest energy are sufficient to reconstruct the ST-segment and J- point. The dimension of the signal space, on the other hand, does not exceed three. Data from 23 patients, with duration ranging from 9 to 21 min, are used.An orthogonalization method to eliminate unwanted signal components in standard 12-lead exercise electrocardiograms (ECG's) is presented in this work. A singular-value-decomposition-based algorithm is proposed to decompose the signal into two time-orthogonal subspaces; one containing the ECG and the other containing artifacts like baseline wander and electromyogram. The method makes use of redundancy in 12-lead ECG. The same method is also tested for reconstruction of a completely lost channel. The online implementation of the method is given. It is observed that the first two decomposed channels with highest energy are sufficient to reconstruct the ST-segment and J-point. The dimension of the signal space, on the other hand, does not exceed three. Data from 23 patients, with duration ranging from 9 to 21 min, are used.
Open Access
A window-based time series feature extraction method
(Elsevier, 2017) Katircioglu-Öztürk, D.; Güvenir, H. A.; Ravens, U.; Baykal, N.
This study proposes a robust similarity score-based time series feature extraction method that is termed as Window-based Time series Feature ExtraCtion (WTC). Specifically, WTC generates domain-interpretable results and involves significantly low computational complexity thereby rendering itself useful for densely sampled and populated time series datasets. In this study, WTC is applied to a proprietary action potential (AP) time series dataset on human cardiomyocytes and three precordial leads from a publicly available electrocardiogram (ECG) dataset. This is followed by comparing WTC in terms of predictive accuracy and computational complexity with shapelet transform and fast shapelet transform (which constitutes an accelerated variant of the shapelet transform). The results indicate that WTC achieves a slightly higher classification performance with significantly lower execution time when compared to its shapelet-based alternatives. With respect to its interpretable features, WTC has a potential to enable medical experts to explore definitive common trends in novel datasets. © 2017 Elsevier Ltd