Depression is a silent killer and a serious threat to mental health, often people pretend to hide their inner turmoil. It is important to detect the early symptoms of depression so that it can be treated in time. A study has shown that this may actually be possible with the use of smartphones. Researchers at Stevens Institute of Technology have conceptualized two smartphone apps that could soon help identify depression by analyzing your face and eyes.
This is a pioneering and unprecedented moment, led by Professor Sang Won Bae and doctoral candidate Rahul Islam. This represents a significant advancement in early detection of mental health using AI. Turning smartphones, which are widely accessible, into diagnostic tools to detect depression is a step forward in effective and convenient mental health screening and treatment. Researchers have developed two AI-powered apps to identify symptoms of depression.
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PupilSense detects depression through changes in the eyes. This is done by making a comparison between the size of the pupil and the iris. Previous research has also replicated the association of the pupillary reflex with depression episodes. The app works by capturing 10-second snapshots of your eyes when you open or use your phone.
The study involved 25 volunteers over four weeks and the app evaluated approximately 16,000 interactions over four weeks. Initial results of the app were encouraging as the app accurately identified depression episodes in 76% of cases. It outperformed existing smartphone-based systems. This is unprecedented because this method of detection does not require any special device or equipment.
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