arXiv AI September 16, 2026 By Fangke Chen, Sirry Chen, Wei Chen, Zhongyu Wei

SOTER: A Generative Time-Series Foundation Model for Wearable Human Physiological Signals

SOTER is a generative foundation model designed for wearable physiological time‑series data. It integrates cross‑channel coupling, spectrum‑guided expert specialization, and continuous‑time latent evolution, using a spatial feature‑aware backbone, a PSD‑guided mixture‑of‑experts layer, and a neural controlled differential equation decoder. Trained on 226 billion time points from five public datasets, SOTER outperforms baselines in zero‑shot forecasting, classification, and imputation across six benchmarks, and remains robust to additive noise.

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