The Wrist Becomes a Foundation-Model Dataset

Google Research says SensorFM learned from minute-resolution wearable data contributed by five million consenting participants across more than 100 countries. The model ingests signals including heart activity, motion, skin temperature, and electrodermal activity, while its training method treats missing sensor periods as part of the data rather than discarding them. Google reports that frozen SensorFM embeddings beat a feature-engineered supervised baseline on 34 of 35 evaluated tasks. This is research, not a clinical product or diagnostic approval, and the health-agent results still require independent validation.