arXiv AI

P2E-VQ: ECG-linked representation augmentation for PPG via discrete patch retrieval

arXiv:2608. 14656v1 Announce Type: cross Abstract: Photoplethysmography (PPG) is widely used in consumer wearables because of its low cost and ease of acquisition.

arXiv AI
Aug 7

ECG-LENS: Lead-Aware Clinical Context Enriched ECG Report Generation and Evaluation

arXiv:2608. 05893v1 Announce Type: new Abstract: Electrocardiography (ECG) is one of the most widely used non-invasive tools for diagnosing cardiovascular disease, but transforming multi-lead ECG recordings into reliable clinical reports remains challenging.

By Akanta Das, Tasinul Islam Ahon, Ahmed Mahir Sultan Rumi, Md Mahbubur Rahman, Tausif Amim Shadly, Tanzima Hashem
arXiv Machine Learning
Jul 28

Aortic Valve Disease Screening from PPG via Physiology-Guided Self-Supervised Learning

arXiv:2602. 04266v2 Announce Type: replace-cross Abstract: Aortic valve disease (AVD) represents a major public health burden, while its diagnosis relies on echocardiography, which is limited by cost and specialist expertise, restricting scalable screening and risk stratification.

By Jiaze Wang, Qinghao Zhao, Zizheng Chen, Zhejun Sun, Deyun Zhang, Yuxi Zhou, Shenda Hong
arXiv Machine Learning
Jul 31

ECG-InterpBench: Benchmarking the Interpretability of ECG Foundation Models with Matched-Scale Sparse Autoencoders

arXiv:2607. 27404v1 Announce Type: new Abstract: Existing benchmarks for electrocardiogram foundation models primarily evaluate downstream predictive performance, providing limited insight into whether their internal representations can be faithfully decomposed, clinically interpreted, or reproduced across independent analyses.

By Yixuan Duan, Wei Qiu
arXiv Machine Learning
5d ago

CardioState-JEPA: Delay-Aware Cross-Modal Learning of a Shared Cardiac Representation

arXiv:2608. 12944v1 Announce Type: new Abstract: Electrocardiography (ECG), photoplethysmography (PPG), and phonocardiography (PCG) provide complementary views of the same cardiac cycle, yet existing cardiac foundation models are trained for a single sensing modality, leaving the shared physiology across sensors unexploited.

By Hamza Shafiq, Hung Manh Pham, Bin Zhu, Pan Zhou, Jun Hu, Aaqib Saeed
arXiv Machine Learning
Aug 4

Rethinking PPG-based Sleep Staging: Datasets, Metrics, and Benchmarks

arXiv:2608. 00943v1 Announce Type: cross Abstract: Automated sleep staging assigns discrete stage labels to successive time epochs throughout an overnight recording; conventionally each window spans at least 30 seconds, reflecting the minimum temporal resolution of the clinical scoring standard.

By Shuntian Zheng, Jiawei Wang, Cong Fu, Huan Yu, Chen Chen, Yu Guan, Sai Gu
arXiv AI
Aug 12

LVCG: Learning ECG Representations in the Latent Vectorcardiogram Space

arXiv:2605. 31249v2 Announce Type: replace-cross Abstract: Electrocardiography (ECG) is a cornerstone of cardiac assessment, making the learning of informative ECG representations fundamental to tasks ranging from disease diagnosis to clinical report generation.

By Bosong Huang, Panzhen Zhao, Zengxiang Li, Patricia Lee, Wei Jin, Alan Wee-Chung Liew, Ming Jin, Shirui Pan