Personalized Cardiac Rehabilitation: Integrating Biomarker-Guided, Technology-Enabled, and Population-Specific...

Cardiovascular diseases remain the leading global cause of mortality and morbidity, necessitating continuous advancement in secondary prevention strategies. Cardiac rehabilitation (CR), a cornerstone of comprehensive cardiovascular care, has been significantly enhanced by innovations in exercise medicine, evolving towards more personalized and accessible paradigms. This review synthesizes the current frontiers in exercise-based CR, focusing on the synergistic integration of three transformative domains: technological innovation, precision medicine, and population-specific strategies. We first delineate the established physiological benefits and evidence-based efficacy of exercise therapy within CR frameworks. Subsequently, we examine the application of digital and intelligent technologies-including wearable devices, remote monitoring, artificial intelligence (AI), and big data analytics-which enable dynamic, data-driven patient management and remote care delivery. The paper further explores the paradigm of precision exercise prescription, guided by biomarkers, genetic profiling, and other individual biological data, to tailor interventions for optimal safety and therapeutic yield. Special emphasis is placed on addressing the heterogeneous needs of key patient populations, such as the elderly, women, and those with specific comorbidities like heart failure or arrhythmias, by outlining individualized strategies that improve engagement and effectiveness. Finally, we discuss future directions, highlighting multimodal technology platforms and in-depth precision medicine applications as key drivers for the next generation of CR, while critically evaluating the evidence readiness of emerging technologies and addressing implementation barriers. This review aims to inform clinical practice and guide future research towards developing more personalized, technology-enabled, and equitable cardiac rehabilitation models.