Structured data model

SensorFM

SensorFM is a foundation model for wearable health data, pre-trained on more than one trillion minutes of multimodal sensor signals from five million people. It learns a general-purpose representation of human physiology from heart rate, blood oxygen, sleep, motion, and skin conductance signals, transferring across 35 health prediction tasks spanning cardiovascular, metabolic, sleep, and mental health domains.

Type
Structured data