ECG Representation Learning with Cardiac Conduction Focus
Published:Dec 30, 2025 05:46
•1 min read
•ArXiv
Analysis
This paper addresses limitations in existing ECG self-supervised learning (eSSL) methods by focusing on cardiac conduction processes and aligning with ECG diagnostic guidelines. It proposes a two-stage framework, CLEAR-HUG, to capture subtle variations in cardiac conduction across leads, improving performance on downstream tasks.
Key Takeaways
Reference
“Experimental results across six tasks show a 6.84% improvement, validating the effectiveness of CLEAR-HUG.”