arXiv cs.LG
· Papers
Prototype-based Self-Supervised Multimodal Learning for PPG and Accelerometry Signals
arXiv:2510.09764v2 Announce Type: replace Abstract: Modeling multi-modal time-series data is critical for capturing system-level dynamics, particularly in biosignals where modalities such as ECG, PPG, EDA, and accelerometry provide complementary perspectives on interconnected physiological processes. While recent self-