A Foundation Model for Wearable Movement Data in Mental Health Research (PAT)

Ruan FY, Zhang A, Oh JY, Jin S, Jacobson NC

Summary

PAT is a masked-autoencoder transformer over one week of minute-level actigraphy (10,080 minutes per participant), pretrained on 21,538 NHANES participants and evaluated on five mental-health labels. It is the first open-source foundation model for wearable movement data aimed at psychiatric outcomes, and the clearest published demonstration that long-context behavioural structure — not short-window signal fidelity — is where movement data pays off for mental health.