AINeutralarXiv – CS AI · 10h ago6/10
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WavesFM: Hierarchical Representation Learning for Longitudinal Wearable Sensor Waveforms
Researchers introduce WavesFM, a foundation model using hierarchical self-supervised learning to extract health insights from continuous wearable sensor data. Trained on 6.8M hours of physiological recordings from 324k individuals, the model captures both local waveform patterns and long-term behavioral dynamics, demonstrating strong performance across 58 health-related prediction tasks.