A Smartphone App to Detect Bipolar Disorder

There’s an app for everything – and now, there’s even one that can detect early signs of mood changes in people with bipolar disorder and other conditions.

The app, developed by researchers from the University of Michigan, still needs much more testing before it can be widely used. But, the researchers said, a study of a small group of patients indicated its potential. The six participants all had Type 1 bipolar disorder and a history of manic and depressive episode.

It could also help people with other conditions such as post-traumatic stress disorder.

The U-M team, led by computer scientists Zahi Karam, Ph.D. and Emily Mower Provost, Ph.D., and psychiatrist Melvin McInnis, M.D., presented its findings at the International Conference on Acoustics, Speech and Signal Processing.

“These pilot study results give us preliminary proof of the concept that we can detect mood states in regular phone calls by analyzing broad features and properties of speech, without violating the privacy of those conversations,” Karam said. “As we collect more data the model will become better, and our ultimate goal is to be able to anticipate swings, so that it may be possible to intervene early.”

The app runs in the background on an ordinary smartphone, and automatically monitors the patients’ voice patterns during any calls made as well as during weekly conversations with a member of the patient’s care team.

The app allows speech features to be recorded and analyzed securely, making it possible to detect changes in mood. Eventually, it will include a feedback loop to the patient and his or her care team and even a chosen family member.

The recordings themselves are encrypted and kept off-limits to the research team. They can see only the results of computer analysis of the recordings, which are stored in secure servers that comply with patient privacy laws.

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