Research

Smart phones used to monitor and predict mental health episodes

University of Melbourne researchers are using smart phones to track the lives of patients with bipolar disorder to understand, monitor and even predict sudden swings between their manic and depressive episodes.

The research is part of the University of Melbourne Complex Human Data Hub, which is being officially launched on February 21, 2018.

Researchers at the hub are applying big data approaches and new sensing technology to better understand mental health and how our minds work.

University of Melbourne Complex Human Data Hub Director Professor Simon Dennis said: “There has never been a better time to be a psychological scientist. We can now start to capture people’s objective experiences in a real way.”

Psychologists have long relied on people telling them what they can remember, but new technology embedded in mobile phones can now provide psychologists with objective information about human activities and experiences, both at the individual level and at the population level.

Professor Dennis developed a phone app that, with participants’ cooperation, can collect data on what people are doing and experiencing – from short snatches of audio and digital vision and information from activity trackers and global positioning data to telephone calls and emails.

The content of such data is scrambled so researchers cannot know the content of conversations or emails, but can build a picture of how a person is behaving.

University of Melbourne Complex Human Data Hub Deputy Director Associate Professor Amy Perfors said: “By knowing what an individual’s actual experience is, we will be able to model how people interact, what makes them decide to talk to someone, what they decide to share with someone, what they learn from each other, what social structures lead to knowledge exchange. We can delve into some deep questions.”

Information gathered from the app can indicate whether somebody is heading into a manic or depressive phase of their condition.

The technology is also being used in experiments to better understand how memory works.

Source: The University of Melbourne

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