BeatGraph: Self-Supervised Heartbeat Graphs for Infant ECG Representations from the Home Environment
Paper recorded by Signals 4 on 2026-09-25 in cs.LG. Abstract reproduced from arXiv; link to the original below.
Published 2026-09-25 on arXiv · recorded by Signals 4 on 2026-09-28
Category: cs.LG · 机器学习 · first seen 2026-09-28
Abstract
Electrocardiogram (ECG) foundation models typically tokenize the signal into fixed-length patches that ignore cardiac structure, so a patch may split a heartbeat and the number of beats in each patch shifts with heart rate. This matters most for infants, whose heart rates are higher and whose ECG differs from the adult, clinic-recorded 12-lead data these models are built on. A model for infant ECG
Read on arXiv →
Cite this page: BeatGraph: Self-Supervised Heartbeat Graphs for Infant ECG Representations from the Home Environment: the #12 most recent of 310 cs.LG papers we have recorded (as of 2026-09-25). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/beatgraph-self-supervised-heartbeat-graphs-for-infant-ecg-representations-from-t.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable:
papers.json
Get 4 AI signals a day by email — free.
Get 4 AI signals a day by email — free