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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...
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...
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...
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...
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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