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Lightweight Deep Learning for Atrial Fibrillation Detection from Single-Lead Wearable ECG: A Systematic Benchmark of Convolutional, Temporal, and State-Space Architectures

2026-07-03

Abstract excerpt

Atrial fibrillation (AF) affects more than 37 million people worldwide and substantially raises the risk of stroke, heart failure, and premature death. Wearable single-lead ECG devices offer a natural platform for continuous AF surveillance, yet automated detection from short, noisy recordings remains an unsolved clinical engineering problem. This paper presents a sys tematic benchmark of three deep learning archi...

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Literature Corpus work: f09d9dfb-b431-553d-8f4f-9de759ecc1b1
DOI: 10.20944/preprints202607.0241.v1

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