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Can wearables predict mental illness?

A team at Michigan State University has developed a new wearable device which will enable doctors to more accurately treat a number of conditions by mining patients for data. HeadScan collects information relating to the user’s eating and social habits, offering physicians a fuller picture of their lifestyle, which then helps them to create care plans for illnesses such as asthma, diabetes, or obesity.

“HeadScan uses wireless radio signals to sense the targeted activities and provides a nonintrusive and privacy-preserving solution that overcomes the drawbacks of current wearable technologies,” says project head Mi Zhang. “For example, it can monitor how often a person eats… Dietary monitoring is important. However, humans are not good at tracking these sorts of things. Fortunately computers are.


Of course, diet has an influence on an individual’s mental health as well as physical, and it is hoped that HeadScan could be used to detect depression and anxiety by analysing eating and drinking habits, as well as the interactions that users share with other people.

This is a principle that has been in testing for a while now. Developers have already experimented with language processing applications which trawl user-generated content on social media platforms, looking for sentiments which might point to negative self-image or a risk that users pose a threat to themselves or others. HeadScan goes right to the source in the offline world.

While this might raise concerns about privacy, Zhang insists that the purpose of HeadScan is to be non-judgmental, and most importantly, private. And it could be a very real asset in the treatment of addiction and eating disorders, where patients are more likely to be deceptive. “In some cases, the patient may not want to reveal how much he or she has eaten,” says Zhang. “This will provide objective information on a continuous basis.”

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