JMIR Publications

ABSTRACT

Background:

Cardiac rehabilitation is a multidisciplinary intervention encompassing therapeutic exercise, education, nutrition, pharmacological treatment, and psychological support, with proven benefits in reducing mortality and improving quality of life. However, its implementation faces persistent challenges, including limited accessibility, high dropout rates, and inequities between urban and rural settings. Conventional models rely heavily on in-person supervision, restricting opportunities for continuous monitoring and long-term adherence. In parallel, cardiovascular prevention requires scalable strategies to identify at-risk individuals, promote lifestyle modification, and ensure sustained risk factor management. Emerging eHealth solutions, particularly wearable devices and artificial intelligence (AI), offer innovative opportunities to address these gaps. Wearables enable remote monitoring of physiological and behavioral variables, early detection of adverse events, and delivery of tailored interventions. AI complements these capabilities by processing large volumes of clinical data, predicting adherence and disease trajectories, and supporting personalized treatment planning. Despite growing interest, the evidence remains fragmented, heterogeneous, and rapidly evolving, warranting a comprehensive synthesis to map current knowledge, trends, and gaps in this field.

Objective:

This scoping review aims to systematically explore the application of AI and wearable technologies in cardiovascular prevention and rehabilitation, identifying current trends, research clusters, and knowledge gaps.

Methods:

The review will follow the Joanna Briggs Institute (JBI) methodology for scoping reviews and adhere to the PRISMA-ScR guidelines. The inclusion criteria are structured according to the Population, Concept, and Context (PCC) framework. A thesaurus has been developed iteratively to guide a structured search in PubMed, WOSCC, IEEE Xplore, CINHAL. Titles and abstracts will be screened by two reviewers, followed by full-text review and data charting. Extracted data will be synthesized narratively and using structured tables.

Results:

A preliminary search in PubMed retrieved 1255 records. As additional databases will be searched (WOSCC, IEEE Xplore, CINAHL), the total number of initial records is expected to be considerably higher. This is consistent with the nature of scoping reviews, which aim to capture a broad range of evidence. The literature search is scheduled to begin in January 2026 and is expected to be completed by March 2026. Study selection, data extraction, and thematic analysis will be conducted between March 2025 and May 2026. At the time of manuscript submission, data collection has not yet started. Results are expected to be available for publication in Summer 2026.

Conclusions:

This review will be the first to comprehensively map the evidence on the integration of AI and wearable technologies in cardiovascular care. By synthesizing current knowledge, it will provide a solid foundation for advancing future research and for shaping digital health strategies aimed at improving patient outcomes. In addition, it will serve as a practical reference for researchers and healthcare practitioners, supporting the design and implementation of innovative tools and programs in cardiovascular prevention and rehabilitation.