Monitoring Substance Use with Fitbit Biosignals: A Case Study on Training Deep Learning Models Using Ecological Momentary Assessments and Passive Sensing

Monitoring Substance Use with Fitbit Biosignals: A Case Study on Training Deep Learning Models Using Ecological Momentary Assessments and Passive Sensing

Substance use disorders affect 17.3% of Americans. Digital health solutions that use machine learning to detect substance use from wearable biosignal data can eventually pave the way for real-time digital interventions. However, difficulties in addressing severe between-subject data heterogeneity ha...

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Bibliographic Details
Main Authors: Shizhe Li, Chunzhi Fan, Ali Kargarandehkordi, Yinan Sun, Christopher Slade, Aditi Jaiswal, Roberto M. Benzo, Kristina T. Phillips, Peter Washington
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:AI
Subjects:
wearables
Fitbit
substance use
self-supervised learning
personalized models
remote monitoring
Online Access:https://www.mdpi.com/2673-2688/5/4/131

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https://www.mdpi.com/2673-2688/5/4/131

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