The rise of fitness-tracking and health-monitoring devices has made it easier for people to quantify and track important health metrics such as physical activity, heart rate, and blood-sugar levels, but easy quantification and monitoring of mental health has proven much more elusive.
Several teams are working on new ways of determining what elements of behavior or mannerisms could be tracked to monitor a person's mental health. For example, University of Maryland researchers, including computational linguistics professor Philip Resnik, are working to identify what vocal traits or behavioral cues might correlate with depression, with the goal of developing an app that could track them.
Meanwhile, Glen Coppersmith and others at Johns Hopkins University's Human Language Technology Center for Excellence are looking for hints to people's mental state's in their tweets. An upcoming hackathon sponsored by the group will task participants with sifting data from Twitter to identify patterns in Twitter use that could indicate conditions such as depression and bipolar disorder.
Meanwhile, Ginger.io has released an app that tracks smartphone usage for activity suggestive of behavioral changes such as decreased social interactions or disrupted sleep patterns that can indicate mental illness.
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