Abstract:Ventricular arrhythmias (VA) are dangerous pathophysiological conditions affecting the heart which evolve over time resulting in different manifestations such as ventricular tachycardia (VT), organized VF (OVF), and disorganized VF (DVF). Success of resuscitation for patients is greatly impacted by the type of VA and swift administration of appropriate therapy options. This thesis attempts to arrive at computationally efficient, data driven approaches for classifying and tracking VAs over time for two purposes… Show more
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