Mayo Clinic Study finds wearable sleep data may improve COPD pulmonary rehabilitation participation

UAE—Mayo Clinic researchers have found that sleep data collected through wearable devices may help clinicians better personalize care for people living with chronic obstructive pulmonary disease (COPD), particularly those enrolled in remote pulmonary rehabilitation programs.

The findings were published in Mayo Clinic Proceedings: Digital Health.

The study suggests that tracking sleep patterns before rehabilitation begins could help healthcare teams identify patients who may need extra support to stay engaged throughout treatment.

Understanding COPD and rehabilitation challenges

COPD is a long-term lung condition that makes breathing difficult because the airways become inflamed and narrowed, while excess mucus can block airflow.

The disease often causes persistent coughing, fatigue, and reduced physical activity.

Many patients also experience poor sleep, which can lower energy levels and affect their ability to take part in treatment programs.

Pulmonary rehabilitation is a key part of COPD management.

It combines supervised exercise, education, breathing strategies, and emotional support to help patients improve lung function and quality of life.

However, some patients struggle to remain consistent, especially in home-based or remote programs where in-person guidance is limited.

How wearable sleep data was used

To better understand participation patterns, the Mayo Clinic team examined whether sleep quality could predict how actively patients would engage in a 12-week home pulmonary rehabilitation program.

Researchers collected one week of baseline sleep data using wrist-worn activity monitors before the rehabilitation program started.

They then used that information to create a Composite Sleep Health Score.

This score was analyzed alongside standard clinical indicators through machine learning models.

According to the study, combining wearable sleep data with clinical information improved predictions of how consistently patients would participate during the three-month program.

Stephanie Zawada, Ph.D., M.S., research associate at Mayo Clinic and first author of the study, said she wanted to explore how wearable technology could help reduce dropout rates in remote pulmonary rehabilitation.

She explained that understanding a patient’s daily routines and sleep habits may allow clinicians to recommend more personalized and effective care plans.

More personalized remote care

Emma Fortune Ngufor, Ph.D., senior author of the study and researcher at Mayo Clinic’s Kern Center for the Science of Health Care Delivery, said wearable data offers a broader picture of a patient’s everyday patterns.

She noted that sleep information should be considered alongside clinical evaluations and patient-reported outcomes rather than used alone.

The researchers believe these insights could help clinicians adjust rehabilitation programs earlier, provide additional coaching where needed, and improve patient engagement in remote care settings.

Next steps for research

The team emphasized that more studies are needed to validate and refine the predictive model across larger and more diverse patient populations before it is adopted more widely in clinical practice.