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DEPRESSION DETECTION THROUGH EYE MOVEMENTS USING STATISTICAL ANALYSIS AND MACHINE LEARNING: A SURVEY
, Rashmi Padmawar, Mrunalini Kulkarni, Shweta Pagare
Published in MCM Publication Company
2018
Volume: 12.0
   
Issue: Special Issue
Pages: 1.0 - 6.0
Abstract
World Health Organization (WHO) survey asserts that 350 million people suffer from depression globally. Depression is prolonged sadness that persists for long durations causing interferences in the functioning of daily life. Depression is increasing at an alarming rate and it not only affects the depressed individual but also their relatives, society and economy. Chronic pains, loss of something desired, separation or death of someone close, drugs, postnatal phase or menopause may be some of the causes of depression. To monitor clinical depression, we analyze the eye movements of the subject to classify them as whether they are depressed or not. To extract the necessary features of eye movements eye tracking and image processing techniques are used. The distance between eyelids, blinking rate, distances when eye is open or closed are scrutinized to inspect whether a patient is depressed or not.
About the journal
JournalInternational Journal of Computer Engineering and Applications
PublisherMCM Publication Company
Open Access0