Google Presents SensorFM for Wearable Health Data

Google Research introduced SensorFM on July 9, 2026, a foundation model pre-trained on over one trillion minutes of de-identified wearable sensor data from five million participants. The model, which learns from Fitbit and Pixel Watch signals, can transfer across 35 health prediction tasks, offering a reusable representation for label-scarce sensor analytics and personal health agents.

Google Research presented SensorFM on July 9, 2026 , a wearable-health foundation model pre-trained on more than one trillion minutes of de-identified sensor data from five million consented participants. The model learns from Fitbit and Pixel Watch signals and transfers across 35 health prediction tasks covering cardiovascular, metabolic, sleep, mental-health, lifestyle, and demographic endpoints. For practitioners, the useful signal is that Google is treating messy wearable streams as reusable representation data, not just inputs for one-off classifiers. The work is still research, not a clinical product, but it gives health AI teams an architecture pattern for label-scarce sensor analytics, daily metric infilling, prediction-head search, and grounded personal health agents.