A Survey on Machine Learning-based Self-Monitoring of Bloom from Expert Perspectives and Student Experiences

Abstract

Self-tracking is very important for promoting mental health. Recent studies with populations of college students have examined the sustainability of capturing daily mood, activity, and social data. Mental health problems are a growing public health concern. The likelihood of having common psychological issues such as depression, anxiety, and stress increases during youth and early adulthood, making university students an especially vulnerable demographic, where people have difficulty fitting in and engaging with a varied assortment of new people. Many students often feel out of place which impacts their mental well-being and to avoid being seen as mentally ill by peers students are often afraid to get professional help With our project we aim to provide a self-reliable solution to their difficulties where they can try to understand their emotions better and get tasks  to which help them overcome their mental burden using machine learning.