R. K. Prasad

Hybrid feature engineering for resource-efficient Arrhythmia detection in electrocardiogram signals: An interpretable, separability-driven framework.

Deep neural networks dominate automated arrhythmia detection, yet their reported performance often relies on intra-patient evaluation, which allows models to exploit patient-specific morphology rather than learn disease-related patterns. Such shortcuts are unavailable in deployed edge monitors, motivating a fundamental...