Passive Sensing for Mental Health Monitoring Using Machine Learning With Wearables and Smartphones: Scoping Review.

ABSTRACT:

Background

Mental health issues have become a significant global public health challenge. Traditional assessments rely on subjective methods with limited ecological validity. Passive sensing via wearable devices and smartphones, combined with machine learning (ML), enables objective, continuous, and noninvasive mental health monitoring.

Objective

This study aimed to provide a comprehensive review of the current state of passive sensing-based and ML technologies for mental health monitoring. We summarized the technical approaches, revealed the association patterns between behavioral features and mental disorders, and explored potential directions for future advancements.

Methods

This scoping review adhered to the PRISMA-ScR (Preferred Reporting Items for Systematic Rev

SUBMITTER: Shen S 

PROVIDER: S-EPMC12395114 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature