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Wearable Trackers May Detect Relapse Early

Wearable Trackers May Detect Relapse Early

February 16, 2026 discoverhiddenusacom Health

A new study suggests that wearable technology, like smartwatches and fitness trackers, may offer a novel way to monitor mental health. Researchers at McMaster University have found that changes in sleep and daily activity patterns, detectable by these devices, could signal an increased risk of relapse in individuals who have recovered from major depressive disorder (MDD).

Detecting Relapse Before It Happens

MDD, often referred to as “clinical depression,” is a common condition characterized by persistent sadness and a loss of interest in activities. The study, published in JAMA Psychiatry, indicates that wearable trackers could potentially detect the probability of a relapse weeks or even months before symptoms fully return.

Did You Know? Up to around 60% of people with MDD will experience at least one relapse episode in their lifetime.

According to Benicio Frey, MD, professor in the Department of Psychiatry and Behavioural Neurosciences at McMaster, “Advances in digital technology and AI algorithms have a great potential for relapse prevention in mental health.” He envisions a future where smartwatches could proactively alert individuals at risk, prompting them to seek care.

How the Study Worked

The research involved 93 adults from across Canada who had previously recovered from depression. Participants wore a research-grade actigraphy device – similar to a Fitbit or Apple Watch – for one to two years, generating over 32,000 days of sleep and activity data.

The analysis revealed several key indicators of potential relapse. Participants with the most irregular sleep profiles had nearly double the risk of relapse. The strongest predictor was a diminished difference between daytime activity and nighttime rest. The amount of time spent awake after initially falling asleep was also linked to increased risk.

Expert Insight: Tracking with wearables over longer periods of time can begin to expose patterns which would otherwise be hard to detect, as our biology, especially mental health-related, is often quite a fuzzy signal.

This study highlights the potential of wearable technology to provide continuous, passive data collection for individuals recovering from MDD, offering insights between clinical appointments.

The Link Between Sleep and Depression

Research consistently demonstrates a strong connection between sleep and depression. Insomnia is a common complaint among those with depression, affecting 80% to 90% of individuals. Insomnia can increase a person’s risk of developing depression twofold. Treating sleep disturbances and tracking sleep patterns may therefore be a valuable component of both preventing and managing depression.

Understanding Major Depressive Disorder

MDD manifests in various ways, and not everyone experiences the same symptoms. Common symptoms include persistent sadness, feelings of hopelessness, loss of interest in activities, irritability, difficulty concentrating, fatigue, and changes in appetite or sleep. In some cases, individuals may experience thoughts of death or suicide.

A diagnosis of depression requires experiencing symptoms most of the day, nearly every day, for at least two weeks. If you are experiencing persistent symptoms, It’s important to consult with a mental health or healthcare professional.

Frequently Asked Questions

What did the study measure?

The study measured sleep and activity patterns using a research-grade actigraphy device, similar to a Fitbit or Apple Watch, worn by participants for one to two years.

What was the strongest predictor of relapse?

The strongest predictor of relapse was when less of a difference between daytime activity and nighttime rest was detected.

How could this technology be used in the future?

Researchers suggest that wearable-derived alerts could help clinicians target care to those most at risk of relapse, potentially improving outcomes and reducing the burden of recurrent episodes.

As wearable technology becomes more sophisticated, could it revolutionize the way we approach mental health care and preventative treatment?

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