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This study presents the use of two different methods for the automatic prediction of the onset of paroxysmal atrial fibrillation (PAF) by means of surface electrocardiographic (ECG) signal. The first method is commonly used and consists in the analysis of the heart rate variability (HRV) of the ECG signal. Two significant parameters are taken into consideration: the time domain metric standard deviation...
Atrial fibrillation (AF) is an arrhythmic behaviour of the heart, which occurs when the myocardium of the atrial chambers enter into a sustained chaotic and fractionated muscular contraction dynamic. Reliable detection of AF episodes in ECG monitoring devices, is important for early treatment and health risks reduction. A decision rule for identifying AF arrhythmic patterns was derived from RR-intervals...
QT interval is a surface ECG measure which has been the subject of great research interest. Usually, a prolongation of the QT interval beyond the normal value is associated with bad cardiac prognosis. In this paper we revisit the wavelet transform based method. Rather than using a threshold related or the highest inflection point of the derivative, we use the extreme on the second derivative which...
An algorithm using wavelets and Kalman filtering method has been developed for QRS detection. The algorithm takes following steps: i) We use a RLS adaptive algorithm to establish a model of the electrocardiogram. Thus the algorithm can change its own model according to the change of the electrocardiogram, ii) Based on the model established in stage i), we combined the wavelet and Kalman algorithm,...
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