Abstract

AbstractDepression is a disorder impacting people of all ages globally. If depression is detected at early stage, then it can be diagnosed. According to research, depression affects heart rate of an individual. By observing heart rate, depression can be predicted. In this paper, heart rate is calculated using facial videos as input. To calculate heart rate from facial video, algorithm used is Eulerian video magnification. Heart rate of person suffering from depression is not in normal range. Hence, estimated heart rate is used to train the model using algorithms of machine learning and proved that visual heart rate is key biomarker to diagnose depressive disorder. Performance of three machine learning algorithms is compared by varying test-train ratio.KeywordsDepressionEulerian video magnificationHeart rateMachine learning

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