A review of detection techniques for depression and bipolar disorder

Abstract

Depression and bipolar disorder are mood disorders affecting millions of people worldwide that can have severe impacts on one’s quality of life. Our ability to detect these illnesses is directly tied to our ability to intervene; however, there has not yet been a systematic review of the technological aspects of the most studied mood disorder detection mechanisms. This survey summarizes detection methods from clinical sensing solutions, such as electroencephalograms and functional near infrared spectroscopy, to ubiquitous sensing solutions, such as scraping social media data and utilizing GPS data. We provide break downs of the algorithms and feature processing techniques of the state of the art methods across these various category and discuss the current challenges affecting mood disorder detection technology, setting the stage for further research.