![]() The support system will receive the level of depression from the detection system. The detection system of the model will detect different levels of depression by periodically collecting following data of users: a) heart rate interval through sensors in the smart-watch, b) sleeping pattern through monitoring activities during night, c) movement pattern through GPS location information, and d) communication pattern through monitoring phone calls, email, and social network usage. In this thesis, a model of depression detection and support system has been designed using extensive user survey on different symptoms and effects of depression that measures different levels of depression based on individuals’ physical state, behavior, and social interaction. It has also been studied that isolation from social activities increases risk of depression while social interaction and support helps greatly in fighting out the problem. Recent study reveals that, depression is reflected in behavioral fluctuation of certain day-to-day activities and physical parameters. Psychologists use standard scales to detect depression but for that the depressed person needs to be present before the psychologist. However, diagnosis and treatment of depression is difficult due to varied severity, frequency, and duration of symptoms in depressed individuals. Untreated depression carries a high cost in terms of relationship problems, family suffering, and loss of work productivity. ![]() ![]() Depression is a familiar psychological disorder caused by a combination of genetic, biological, environmental, and psychological factors.
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