Identifying subgroups of patients and predicting relapse in bipolar disorder: a prospective longitudinal study

Bipolar disorder affects 2.2% of Canadians and profoundly impacts their quality of life, functioning, and overall health. There is a major unmet need of understanding the illness course and knowing which patients will present a higher risk to develop worse outcomes. This knowledge is important to develop new preventative treatments. This project is aiming to develop an analysis using information (including sleep, physical activity, mood self-records) collected from patients using a wrist-worn device and a smartphone application in order to recognize distinct forms of bipolar disorder and detect when patients will relapse. The digital tool proposed in this project will be developed by the Mindpax company in collaboration with McMaster University and has the potential to enable individualized predictions of mood relapse using easily obtainable patient data. This creates the potential for preventative interventions rather than attempts to remediate relapses, thus improving patient’s quality of life.

Faculty Supervisor:

Flavio Kapczinski


Bianca Pfaffenseller


Mindpax GmbH






McMaster University


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