Google Research·· 2026-07-09
SensorFM: Towards a general intelligence and interface for wearable health data
SensorFM: Towards a general intelligence and interface for wearable health data
AI summary
Google Research and Google DeepMind proposed SensorFM, a large sensor foundation model learning directly from unlabelled wearable data. Pretraining uses over 1 trillion minutes of multimodal sensor signals from 5 million consenting participants across more than 100 countries and over 20 Fitbit and Pixel Watch devices.
Selection record
Threshold 60Official, first-handFirst 62Second 58
AdmittedSum of both 120 ≥ twice the threshold 120
- Source tier
- Official, first-hand; this tier's threshold is 60
- Pre-filter
- passed：介绍可穿戴健康基础模型SensorFM及AI智能体
- Why it was chosen
- Pretraining scale, scaling experiments and downstream comparisons show the limits of generalisation for wearable health foundation models.
A model scores each item twice, independently, against one written standard, out of 100. An item is admitted only when the two scores add up to twice the threshold. The threshold is set per source tier.
Source: Google Research · research.google