Machine Learning based Mood Disorder Detection System

Abstract

Mood disorder is often overlooked and there are people who think that mood disorder is "all in your head". As per the record of World Health Organization (WHO), 5% of the adults are suffering from it. If one has Mood disorder, the general emotional state or mood is distorted or inconsistent with various circumstances and interferes with one’s ability to function. Mental illness is still a taboo. People hesitate to consult a health specialist; hence a system is required as an early detection. The primary objective is to improve this situation by designing a user friendly application. In proposed application, condition of the people will be analyzed with the help of standard Mood Disorder Questionnaire (MDQ), Emotion analysis using face detection with the help of image processing in Python and EEG signals. The results received from above mentioned analysis will determine the severity level of mood disorder using machine learning algorithm. Depending on the severity several activities will be given. These activities will include some yoga, games, meditation and exercise. User is suggested to take the above three tests every week to check the progress. In case of high severity, according to user’s location, suggested list of health specialists will be recommended.