
Psychological State Diagnosis using Deep Learning Techniques
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.b1046.1292s19
Subject(s) - silence , depression (economics) , psychology , looming , mental health , state (computer science) , subject (documents) , applied psychology , social psychology , cognitive psychology , computer science , psychiatry , aesthetics , philosophy , algorithm , economics , macroeconomics , library science
Psychological State or Depression is a looming mental health problem in the society. This, negatively affects many families, relationships, jobs. But to provide effective treatment, there is no awareness about this. Most people do not give much thought to this as they do to physical problems due to reasons which include that they are shy, afraid or negligent about this. A feasible solution to this is to create awareness about this so that people can actively seek out help and just not choose to suffer in silence. This paper proposes an approach to detect psychological state or depression in people using mainly non-verbal and involuntary cues with the help of a standard questionnaire. The subject wears the MindWave device by NeuroSky and pairs it with a smartphone. Then a standard questionnaire is answered during which the data on brain waves and emotions are collected simultaneously by MindWave and the smartphone camera respectively. The data collected is then used to train a model that will give a score pertaining to the severity of depression in a person, thus aiming to give a better accuracy compared to all the devices present