Enhancing Emotional Well-Being with IoT Data Solutions for Depression: A Systematic Review

Abstract

Effectively caring for adults with depression is challenging. While technology offers potential improvements in emotional well-being through better monitoring, standardised methods to gather and analyse relevant data are highly fragmented. This Systematic Literature Review (SLR) explores using Internet of Things (IoT) based data collection and analysis to enhance emotional well-being and manage depression effectively. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework, we report in-depth findings from 42 studies, which were selected from an initial set of 559 published works. We find that current literature extensively covers important topics like IoT for detecting, analysing, and monitoring emotions, therapeutic interventions for emotional well-being, and predicting, detecting, and managing depression. IoT-based data collection and analysis solutions predominantly employ sensors and AI, respectively. The literature review identifies a gap in prioritising active systems that engage users, highlighting the need to address key aspects such as privacy and security.