Digital Twins for Cyber-Physical Healthcare Systems: Architecture, Requirements, Systematic Analysis, and Future Prospects

Over the past few years, the demand for personalized and accurate healthcare solutions has significantly increased, aiming to enhance medical effectiveness. Digital Twins (DTs), a transformative technology in the evolution of Industry 4.0, have expanded their applications from traditional fields like manufacturing and automotive industries to revolutionizing healthcare. DTs offer a more advanced and precise method of healthcare delivery, enabling better patient-specific care by creating real-time digital replicas of patients’ health conditions. Despite these advancements, healthcare professionals still heavily rely on their expertise to make critical decisions, highlighting the importance of continuous refinement of knowledge and skills to navigate complex healthcare challenges. Personalized treatments and comprehensive healthcare support remain essential for optimizing patient outcomes, though they are still in the early phases of development. This paper introduces a reference architecture specifically designed for Digital Twins in cyber-physical healthcare systems, outlining the key requirements and challenges in developing digital frameworks for such systems. It explores the fundamental principles of Digital Twins in healthcare, focusing on their applications in product design, production processes, and system performance. It also provides a detailed review of current research on healthcare data management, personalized healthcare, and operational efficiency, along with the associated requirements, challenges, and application scenarios. Furthermore, the paper discusses major obstacles and outlines potential future research directions, offering a roadmap to advance healthcare data management, personalized medicine, and operational control within Digital Twin frameworks.