Mental issues such as depression and anxiety aren’t only linked to adults, as kids can suffer from them too. In order to know if kids are suffering from these illnesses, researchers have created a wearable sensor that can detect such problems in the child.
Researchers from University of Vermont and University of Michigan combined a sensor and an algorithm for an AI-enabled wearable tool to detect children for internalizing disorders early and accurately through their movements.
For the study, children aged between three and seven were fitted with wearable movement sensors in a dimly-lit room were told to anticipate something to look in a covered glass box, which turned out to be a fake snake. The researchers then scored their responses aromatically through a wearable motion sensor and the machine learning algorithm, as per Xinhua.
The tool identified differences between children with internalizing disorders and those without them. They tool turned out to be 81% accurate, which was better than the traditional parent questionnaire, as per the study published in the journal PLOS One.
The algorithm figured out that children’s movement before the snake was revealed was most indicative since those with internalizing disorders tended to turn away from the potential threat. This in turn showed that those children anticipated more anxiety, and the turning-away behavior was a negative reaction.
The 20 seconds of data from the anticipation phase provided by the sensors and algorithm was enough to make a decision while the traditional video coding method may take numerous months. This research opens up possibilities to large-scale screening for identifying children with psychological disorders.
Explaining the motivation behind the research, researcher Ryan McGinnis said, “Because of the scale of the problem, this begs for a screening technology to identify kids early enough so they can be directed to the care they need.”
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