No abstract

Mental wellbeing is an epitome of success for human beings. Recently, a lot of mental diseases that include anxiety, suicidal tendency, depression, bipolar disorder, obsessive compulsive disorder (OCD), etc. have deep-seated among all age groups. This is due to the fact that the social complexity has increased at work, in relationships, at home and in majorly all aspects of human life. Early detection of these problems can help in treating and if possible, eradicating this illness from a person's life. Researchers have proposed different techniques that can be put into action to effectively identify these diseases. These techniques utilize different activities of normal day-to-day human behaviour, like speech analysis, social media behavioural patterns, visual-activity pattern analysis, etc. Due to a large variety of available techniques, researchers find it difficult to standardize techniques for detection and evaluation of such diseases. Thus, in this paper we have performed an in-depth study about the state-of-the art methods to identify mental health issues. Readers will be able to get a bird's eye view of these methods and will be able to identify the best practices involved in mental health analysis. Moreover, this survey also recommends some possible improvements in the existing methods, in order to further improve the system's performance.