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...

Полное описание

Библиографические подробности

Главные авторы:	Shizhe Li, Chunzhi Fan, Ali Kargarandehkordi, Yinan Sun, Christopher Slade, Aditi Jaiswal, Roberto M. Benzo, Kristina T. Phillips, Peter Washington
Формат:	Artigo
Язык:	Inglês
Опубликовано:	MDPI AG 2024-12-01
Серии:	AI
Предметы:	wearables Fitbit substance use self-supervised learning personalized models remote monitoring
Online-ссылка:	https://www.mdpi.com/2673-2688/5/4/131
Метки:	Добавить метку Нет меток, Требуется 1-ая метка записи!