Abstract
OBJECTIVE: Despite its demonstrated effectiveness at improving outcomes, pulmonary rehabilitation (PR) for chronic obstructive pulmonary disease (COPD) is underutilized. Sensor-generated data from wearable devices have the potential to mitigate this challenge by generating digital endpoints that provide insights into patient behaviors at home; however, there is no consensus on how to measure home-based PR (HBPR) outcomes with these tools. This review aims to describe (1) the most frequent digital endpoints used in HBPR studies and (2) the devices used to capture these endpoints, summarizing gaps in their applications to HBPR for COPD patients. METHODS: We completed a scoping review using the PRISMA checklist across databases (Web of Science, Scopus, and OVID) from January 2005 to June 20, 2025. We included peer-reviewed articles on HBPR for COPD, excluding reviews, commentaries/editorials, poster abstracts, and conference proceedings. Eligible articles included cohort studies and clinical trials of adult patients (age > 18 years) with COPD participating in HBPR that include one or more digital endpoints. RESULTS: Among eligible articles (n = 218), 13 (6.0%) met inclusion criteria, the majority of which were published after 2020 (61.5%). Most studies enrolled fewer than 100 COPD patients (76.9%) for an average monitoring period of 12.5 weeks. Activity trackers were the most commonly used device (46.2%) to capture data. The most frequently used digital endpoints were step count (84.6%), time spent active (38.5%), and time spent sedentary (30.8%). Two study designs were used: randomized controlled trial (76.9%) and observational cohort. Study designs were heterogenous with more than one-third (38.5%) presenting a lack of statistically significant results. CONCLUSIONS: Although we identified analogous digital endpoints in some studies, dissimilar methods and study designs remain barriers to synthesizing results generated from HBPR programs for COPD. Wearable devices have the potential to build novel PR models, but more work is needed to translate real-world data into clinically meaningful measures. Future research should elucidate which participants would benefit most from and complete HBPR to build an evidence base for the validation of HBPR-relevant digital endpoints, particularly those derived from less common sources like cardiovascular and sleep measures. CLINICAL IMPLICATIONS: While wearable devices can augment HBPR programs, caution must be exercised when interpreting remotely collected data and requires clinicians to engage patients via traditional monitoring means, such as video telehealth and in-person visits, to ensure accurate screening and severity grading. Combining multiple sensors can capture a range of physiologic markers relevant to understanding patient-specific COPD exacerbations, from medication use to sedentary behavior, potentially informing personalized rehabilitation plans. Considering the heterogeneity of randomized controlled trials with digital endpoints in HBPR programs, little is known about optimal COPD patient sampling frequencies, or which populations would benefit most from integrating specific sensors in home-based programs.