Active Mental Health Psychology & Behaviour

Ambient and passive collection of sleep and circadian rhythm data in bipolar disorder to understand symptom trajectories and clinical outcomes (AMBIENT- BD).

Funder Wellcome Charity-funded
Associated organisations National University of Ireland, Maynooth · University of Edinburgh Europe PMC affiliations are not treated as award recipients or mapped locations.
Funding £3.1M
Period Jun 2023 — May 2028

In plain English

AI plain-English summary

People with bipolar disorder will wear sensors and use smartphone apps for 18 months straight, tracking their sleep, activity, and mood without needing to visit a clinic. This matters because existing studies only monitor people for a week or two—far too short to capture the weeks-long cycles of mood and energy that define bipolar disorder. Without long-term data, doctors cannot predict when a relapse is coming or understand what triggers it. The project will test whether passive, low-effort tools—like motion sensors and phone-based diaries—can reliably replace the expensive, intrusive lab equipment currently used to measure sleep and circadian rhythms. If the sensors work, researchers could finally map how sleep disruption leads to mood episodes over months, not days. That would let clinicians spot early warning signs and intervene before a crisis. The team is also building a data-sharing system so patients and their doctors can see the same sleep and mood patterns in real time, turning raw data into a practical tool for managing the condition. A lived experience panel ensures the outcomes measured—like time to relapse or quality of life—matter to people who actually live with bipolar disorder.

View original technical description
Bipolar disorder is defined by extreme variability in mood, activity, sleep and circadian timing recurring over weeks and months. To date, studies of sleep/circadian rhythms in bipolar disorder have been cross-sectional and based on only 1-2 weeks of monitoring: we urgently need new approaches that can assess longer-term individual-level changes in sleep, activity and mood, to better understand symptom trajectories and mechanisms of relapse. We will optimize innovative ambient and passive data collection methods over long time periods and test their feasibility and performance against gold standards. A lived experience advisory panel will help us to identify and prioritize clinical and functional outcome measures and develop ‘low intensity’ methods for collecting these outcomes. In parallel, we will develop a data collection and management system to support data collection and optimize data sharing with patients, clinicians and the research community. The core of this project is an 18-month prospective follow-up study of sleep, circadian rhythms and clinical/functional outcomes in people with bipolar disorder that primarily makes use of low intensity ambient and passive data collection methods. We will also work with Bipolar Scotland to co-produce an innovative programme of knowledge exchange on the theme of ‘Sleep, circadian rhythms and bipolar disorder'.

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Researchers

Andrew Coogan (EPMC Awardee)Andrew Millar (EPMC Awardee)Athanasios Tsanas (EPMC Awardee)

Related Research

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Original classification

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