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Goodwin — Autism Inpatient Collection (AIC)

Citation: Goodwin, M.S., Mazefsky, C.A., Ioannidis, S., et al. (2019). Autism Research, 12(8), 1286-1296.
DOI: 10.1002/aur.2151
Access: SFARI Base — data access request required, may need IRB/data use agreement
Tier: 1

Overview

The foundational study for wearable aggression prediction in ASD. 20 youth with ASD (ages 6-17, 75% male, 85% minimally verbal) in a specialized inpatient psychiatry unit. 69 naturalistic observation sessions.

Signals

  • Cardiovascular (HR)
  • Electrodermal activity (EDA)
  • Accelerometry (motion)

Device: wrist-worn biosensor (Empatica E4 or equivalent).

Performance

  • Global model AUC: 0.71
  • Person-dependent model AUC: 0.84
  • Prediction window: 1 minute before aggression
  • Context window: 3 minutes of prior biosensor data
  • Model: ridge-regularized logistic regression

Key Findings

  • Biosensor data contributed unique predictive information beyond temporal features
  • Person-dependent models significantly outperformed global models
  • Larger training datasets improved prediction more than longer observation of aggression episodes
  • AIC phenotypic data available through SFARI Base

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