Wearable Data May Predict COPD Rehab Engagement

Sleep data could help identify patients needing more support for pulmonary rehab programs.

Mar. 27, 2026 at 4:02am

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New research published in Mayo Clinic Proceedings: Digital Health found that sleep data captured with a wearable device could help clinicians better tailor care for patients with chronic obstructive pulmonary disease (COPD) by identifying those who may need additional support to participate in pulmonary rehabilitation programs.

Why it matters

COPD can make sleeping more difficult, affecting a patient's energy levels and overall health, which can influence their participation in pulmonary rehabilitation. Using wearable data to predict engagement in these programs could lead to more personalized and effective care plans.

The details

Researchers collected sleep measures for one week from COPD patients to generate a Composite Sleep Health Score before a 12-week home-based pulmonary rehabilitation program. Analysis showed that including the health score improved prediction of patient engagement over the study period. This information can help clinicians better tailor rehabilitation programs and identify patients who may benefit from additional support.

  • The study was published on March 27, 2026.

The players

Stephanie Zawada

A Mayo Clinic research associate and first author of the study, committed to finding ways to use data to personalize care through her work on the team at the Kern Center for the Science of Health Care Delivery.

Emma Fortune Ngufor

A Mayo Clinic researcher in the Kern Center and senior author of the study, noting that sleep data is one of several inputs that can help inform care decisions, alongside clinical assessments and patient-reported information.

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What they’re saying

“As a scientist and engineer, I wanted to explore how wearable data could improve the drop-out rates of remote pulmonary rehabilitation programs. By better understanding a patient's day-to-day life, we can make more personalized and potentially more effective care plan recommendations.”

— Stephanie Zawada, Research Associate

“Adding wearable data provides a more comprehensive view of a patient's daily pattern.”

— Emma Fortune Ngufor, Researcher

What’s next

Researchers note that additional investigation is needed to validate and refine the model in broader patient populations before broader clinical application.

The takeaway

Using wearable sleep data to predict engagement in pulmonary rehabilitation programs could lead to more personalized and effective care plans for COPD patients, helping to improve outcomes and reduce dropout rates.