Multimodal analysis of depression in unconstrained environments - Kusumam, Keerthy (2023)
Mental health disorders, such as depression and anxiety, are a significant global problem affecting millions of people, leading to disability, increased mortality from suicide, and reduced quality of life. Traditional diagnostic and evaluation methods rely on subjective approaches and are limited by resource availability, driving the need for more accessible and efficient methods using technology. Digital mental health, a rapidly growing field, merges digital technologies into mental health care, utilizing the Internet and mobile phone software to deliver mental health services. The use of mobile health technologies, such as Ecological Momentary Assessments and digital phenotyping, can improve depression diagnostics by generating objectively measurable markers in natural environments. Technological progress in computer vision, natural language processing, and affective computing has also led to the emergence of automated behavior analysis methods, improving depression assessment and understanding.