Could a Simple Wrist-Worn Device Transform Mental Health Care?
Advances in wearable technology are transforming healthcare by providing new ways to monitor sleep and activity in real-world settings. A recent study from the CAN-BIND Wellness Monitoring in Major Depressive Disorder project explores how actigraphy can be used to track sleep and activity patterns in people with depression. The research highlights how continuous monitoring may help predict depressive relapses and support more personalized treatment strategies.
What is Actigraphy?
Actigraphy is a non-invasive method used to monitor sleep and activity patterns by tracking movement. A small device, resembling a wristwatch, is worn on the wrist or ankle to record physical activity. This device helps researchers and clinicians assess sleep quality, duration, and disturbances over extended periods, often ranging from several days to weeks. Unlike traditional sleep studies that require overnight stays in a clinic, actigraphy allows individuals to go about their daily routines while data is collected.
“Relapse rates in major depressive disorder (MDD) remain high even after treatment to remission. Identifying predictors of relapse is, therefore, crucial for improving maintenance strategies and preventing future episodes. Remote data collection and sensing technologies may allow for more comprehensive and longitudinal assessment of potential predictors.”
How Does Actigraphy Work?
The actigraph contains sensors that detect movement. It records data continuously, capturing periods of activity and rest. This information is then analyzed to determine sleep patterns, such as when a person falls asleep, wakes up, and the quality of their sleep. Some advanced actigraphy devices also measure light exposure, which can influence sleep-wake cycles.
Applications in Mental Health
In the context of mental health, actigraphy is particularly useful for monitoring conditions like depression. For instance, the CAN-BIND study utilized actigraphy to track sleep and activity patterns in individuals undergoing treatment for major depressive disorder. By analyzing this data, researchers aim to predict potential relapses and adjust treatment plans accordingly. This approach offers a more personalized and timely intervention strategy.
“Understanding the mechanisms underlying MDD relapse is critical, as this would allow for enhanced prediction of such events, creating opportunities for the development of more targeted treatments and improved preventative interventions.”
Advantages of Actigraphy
- Objective Measurement: Provides quantifiable data on sleep and activity, reducing reliance on self-reported information.
- Extended Monitoring: Allows for assessment over long periods, capturing variations that might be missed in short-term studies.
- Convenience: Enables individuals to maintain their normal routines while data is collected, offering a more accurate representation of real-life behavior.
- Cost-Effective: Less expensive than some traditional sleep studies, making it accessible for broader use.
Limitations to Consider
While actigraphy is a valuable tool, it’s not without its limitations. The accuracy of the data can be influenced by factors such as device placement, movement during sleep, and the presence of other conditions. Therefore, actigraphy is often used in conjunction with other assessment methods to provide a comprehensive understanding of an individual’s sleep and activity patterns.
Final Takeaway
Actigraphy offers a powerful window into sleep and activity patterns that can help researchers and clinicians better understand mental health. By tracking real-world behaviour continuously, it has the potential to predict depressive relapses, personalize treatment, and improve overall well-being if used thoughtfully alongside other clinical assessments.
Citation: Lam, R. W., Rnic, K., Nunez, J. J., Ho, K., LeMoult, J., Nunes, A., Chakrabarty, T., Foster, J. A., Frey, B. N., Harkness, K. L., Hassel, S., Kennedy, S. H., Li, Q. S., Milev, R. V., Quilty, L. C., Rotzinger, S., Soares, C. N., Taylor, V. H., Turecki, G., & Uher, R. (2025). Predicting Relapse of Depressive Episodes During Maintenance Treatment: The Canadian Biomarker Integration Network in Depression (CAN-BIND) Wellness Monitoring in Major Depressive Disorder Study. Canadian journal of psychiatry. 70(7), 565–573. https://doi.org/10.1177/07067437251337603.