SOURCE-LINKED INTELLIGENCE

Learning Human Health and Diseases from 24-hour Wrist Movement

arXiv · AI, language, vision and robotics · article · Aug 30, 2026 · UTC

Much of human health and function unfolds beyond the clinic, through the movements of everyday life. Wrist-worn accelerometers capture these movements continuously, yet their rich signals are often reduced to a small set of predefined behavioural summary measures. Here, we present Sensori, a self-supervised foundation model that learns general-purpose health representations directly from 24 hours of raw tri-axial wrist movement. We developed and evaluated the model across four population-based cohorts from the United Kingdom, China and the United States, comprising 122,640 participants contrib

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