A Survey of Machine Learning Approaches for Detecting Depression Using Smartphone Data

Abstract

Depression is one of the most common mental health issues worldwide and has only become more widespread after the emergence of the Covid-19 pandemic. Although depression can be treated through various methods, it often goes undiagnosed and therefore untreated, forcing individuals to go through life with a condition that is nothing short of debilitating. With mobile phones being an integral part of people’s lives, they can provide valuable information about a person’s habits and behaviors, which can then be used to detect depressive tendencies. This paper provides a review of several studies conducted in recent years on the possibility of using machine learning and smartphone data to detect depression.