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The QRS complex is the most striking waveform within the electrocardiogram (ECG). QRS provides the fundamentals for almost all automated ECG analysis algorithms. We proposed a novel method for classification of ECG beats using shared counters. We first developed a real-time QRS detection technique using two-phase hashing to extract precise QRS points. Then we proposed a classifier for profiling an...
ECG morphology features, as a kind of significant diagnosis feature, are widely used by experienced cardiologists and highlighted in professional medical textbooks. Fail to utilize it should be one of the most important reasons for the underperformance of automatic ECG classification. In this paper, a framework for ECG morphology features recognition is presented. 1-nearest-neighbor with dynamic time...
The problem of detecting clinical events related to cardiac arrhythmias in long term electrocardiograms is a difficult one due to the large amount of irrelevant information that hides such events. This problem has been addressed in the literature by means of clustering or classification algorithms that create data partitions according to a cost function based on heartbeat features dissimilarity measures...
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