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Integration of automated ECG analysis techniques with the home monitoring devices can incorporate the necessary “smartness” which can help in earlier diagnosis of Myocardial Infarction (MI), better known as heart attack, thus reducing the mortality rate. Most of the reported techniques suffer from the disadvantages of large feature dimension, computational complexity of the features and complex classifiers...
Heart disorders are one of the most problematic issues of human health. There are currently many efforts to reduce the time for first assistance based on electronic systems that continuously records the electric heart activity for further inspection and anomalies detection. The most popular are portable monitoring systems based on the Electrocardiogram (ECG) signal. However, an efficient detection...
Myocardial infarction (MI), generally known as a heart attack, is one of the top leading causes of mortality in the world. In clinical diagnosis, cardiologists generally utilize 12-lead ECG system to classify patients into MI symptoms: 1. ST segment elevation, 2. ST segment depression or T wave inversion. However unstable ischemic syndromes have rapidly changing supply versus demand characteristics...
Myocardial infarction (MI) is one of the most common sudden-onset heart diseases. Early diagnosis and management of heart ischemia result in good prognosis. Early changes in the heart muscle activity after ischemia reflect in ST segment elevation on electrocardiogram (ECG) recordings. With the development of signal processing techniques and the portable devices, there is a need to develop a real-time...
In electrocardiogram real-time monitoring, the ST segment detection is important, it has close relationship with myocardial ischemia and myocardial infarction. In this paper, ST detection is divided into two parts, firstly using wavelet and morphology method to calculate the offset direction, waveform and summarizing features of ST, eventually divide the ST in 15 types; next analyzing the ST waveform...
An improvement of biventricular pacing (BVP) could be possible by detecting the patient specific optimal pacemaker parameters. Body surface potential map (BSPM) is used to obtain the electrophysiology and pathology of an individual patient non-invasively. The clinical measurements of BSPM are used to parameterize the computer model of the heart to represent the individual pathology. The computer model...
Abnormal intra-QRS potentials (AIQP) have been proposed as a promising new index for evaluating the risk of ventricular arrhythmias. However the clinical results are still inconsistent. Our previous study showed that the mean AIQP parameters of ventricular tachycardia (VT) patients were significantly lower than those of normal subjects. Because several previous studies have reported that myocardial...
Sudden death from cardiac arrest is a major health problem and is responsible for almost half of all heart disease deaths. This paper introduces work that has been done to distinguish the Electrocardiogram (ECG) of a normal healthy human from that of a patient who may suffer from Sudden Cardiac Death (SCD), but this condition has not been detected. In SCD, the cardiac arrest occurs for a very short...
The method for detection and evaluation of T-wave alternance in ECG was elaborated for monitoring of the status of the patients in the Intensive Care Unit of Cardiology Clinics. 24 h ECG recordings registered mostly in patients after myocardial infarction were used for elaboration of the method. Data preprocessing included ECG structural analysis, respiration and/or other factors caused baseline wander...
Myocardial infarction is one of the leading causes of morbidity and mortality in the western world. In the present investigation the statistical information about different infarctions was extracted from the results of forward simulations on a personalized electrophysiological model of the patient and then implied into the improved spatio-temporal maximum a posteriori (MAP) based estimator. Using...
Hypothesis/Objective: The aim of this study is to characterize the location and extent of moderate to large, relatively compact infarcts using ECG evidence. Method: In this paper, we proposed a method on the basis of vectorcardiography which assumes that heart vector is proportional to relevant active depolarization area(s). To examine our ideas, we used the normal VCG which includes the information...
A model-based approach to noninvasively determine the location and size of the infarction scar is proposed, that in addition helps to estimate the risk of arrhythmias. The approach is based on the optimization of an electrophysiological heart model with an introduced infarction scar to fit the multichannel ECG measured on the surface of the patient's thorax. This model delivers the distributions of...
This study presents a new method for estimation and imaging of the area at risk (AaR) in myocardial infarction (MI). The values of the ST-segment deviations of 12-lead ECG signal were used as input parameters. Based on DECARTO model, the spherical surface was chosen as a reference surface to approximate the ventricular wall. On this surface, the spatial ST vector was projected. The center of AaR was...
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