AINeutralarXiv – CS AI · 6h ago6/10
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Motif-based morphology signatures for interpretable ECG screening and monitoring
Researchers propose a motif-based framework for ECG analysis that identifies interpretable cardiac signatures through beat-aligned morphology patterns, enabling early detection of cardiovascular abnormalities. Using Dynamic Time Warping to extract representative cardiac cycles, the method quantifies morphological drift across short and long-term monitoring with three metrics: deviation from normal sinus rhythm, personalized baseline deviation, and motif instability. Testing on standard ECG datasets demonstrates significant separation between normal and arrhythmic subjects with high statistical significance.