A team led by Lee Eui-jin, a professor of computer science at KAIST, announced that it will be possible to accurately track an individual's mental health status by using data from the Internet of Things sensor at home. The more depressed you are, the more irregular your life pattern The more you open your refrigerator, or the less active your activity decreases.
The researchers conducted a four-week empirical study of 20 households with young people and found that Internet of Things data captures mental health changes more accurately than conventional methods. In the demonstration, sensors were attached to home appliances and sleeping mats to analyze the movement. Their mental health status and movement data were closely related. Sleep time decreased as depression, anxiety, and stress levels increased.
Behavioral patterns when stressed varied from person to person, but life patterns became irregular in common. There were "binge eating types" that increased the use of refrigerators and "weapon types" that decreased their activity sharply, but they changed their daily life patterns. This study shows that Internet of Things data at home can be a major clue to understanding mental health in an individual's life, adding, We plan to predict individual life patterns with artificial intelligence (AI) in the future and develop a telemedicine system.
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