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Mayo Clinic Study Uses Wearables and Machine Learning to Predict COPD Rehab Participation

Mayo Clinic researchers published a study in Mayo Clinic Proceedings: Digital Health showing that wearable‑derived sleep metrics can forecast patient participation in remote COPD pulmonary rehabilitation. Participants wore wrist activity monitors for a week before a 12‑week home‑based program, generating a Composite Sleep Health Score. When combined with standard clinical variables in a machine‑learning algorithm, the model achieved markedly higher predictive accuracy for engagement over the subsequent three months. The findings point to a data‑driven approach to curb high dropout rates in COPD rehab.