Treating and diagnosing mental health could get easier because researchers at Washington University in St. Louis have found that data recorded by Fitbit monitors can detect mental health disorders.
Chenyang Lu is the Fullgraf Professor at the McKelvey School of Engineering and a professor of medicine at the School of Medicine.
“You don’t need to see a doctor,” he told Missourinet. “You don’t need to do anything in terms of filling out a questionnaire. It’s just a system that analyzes passively detected data and detects mental disorders. And then, you can detect these much more effectively and in a timely fashion.”
He developed a deep-learning model called WearNet, which studies 60 days’ worth of variables collected by popular wearable fitness monitors to consider these factors.
“So what we’re looking at is basically daily summaries of a set of variables that’s derived from the combination of step counts and heart rate such as, for example, your total daily steps. Right? Or your sedentary patterns,” he explained.
Lu said that anxiety and depression are turning into a societal problem.
“This is where the combination of wearable and AI really have a good opportunity to help,” he stated.
Lu said WearNet did a better job at discovering mental health disorders than state-of-the-art machine learning models, adding that he hopes major hospitals in Missouri will implement his approach to treat disorders in the future.
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