Despite the recent advances of digital twin technology and extended reality (XR) in the realm of virtual healthcare, there remain significant gaps, especially in developing patient-centered technologies. Patients continue to struggle with the complexity of medical information, who are often compounded by the physical and mental burdens of illness. The technical jargon and complex imaging data in standard medical reports remain largely inaccessible to patients, obscuring their understanding of their own medical conditions.

Simultaneously, traditional medical education methods primarily rely on static textbooks and anatomical models, which are significantly inadequate in conveying the dynamic characteristics of human physiological activities and disease progression [Narayanan and Ramakrishnan, 2024]. This shortcoming is particularly pronounced in the training of medical interns and novice doctors. Due to limited time and case exposure, they struggle to observe the full progression of diseases, resulting in a gap between theoretical knowledge and practical application. Additionally, the high-pressure clinical environment limits their confidence and decision-making skills in handling complex cases. These challenges leave them ill-prepared to manage intricate cases and hinder their ability to make critical decisions. Therefore, there is an urgent need to develop dynamic and interactive medical education tools to bridge the gap between theoretical learning and practical clinical experience, providing more comprehensive and efficient support for the training of medical professionals.

To address these gaps, in this dissertation, we investigate the innovative application of 3D digital twin technology combined with extended reality for smart cardiology – involving patients and cardiovascular specialists in heart health management, which can support both patient-faced cardiovascular problem visualization and medical training, as well as assist in cardiologists for their immersive management of cardiovascular conditions. To make complex cardiovascular information more accessible, understandable, and engaging for patients, we develop an interactive 3D heart model that allows users to visualize the progression of cardiovascular diseases and explore potential treatment outcomes in an immersive and patient accessible manner. By incorporating key medical principles such as Poiseuille’s Law, the Cardiac Output Equation, and Laplace’s Law, the model simplifies the interpretation of medical data and bridges the gap between complex physiological concepts and patient comprehension. The platform aims to not only
empower patients by providing clearer insights into their health conditions but also to serve as a valuable educational tool for healthcare professionals. Medical trainees
can utilize the system to gain a deep understanding of cardiovascular mechanics, aiding in medical training and preoperative simulations.

The model is limited by the current technology and the lack of sufficient medical data, the details of the human body cannot be comparable to the current market mainstream, resulting in certain challenges. But this dual-purpose model could significantly increase patient engagement and improve clinical training for novice physicians, which could facilitate more informed medical decisions and ultimately contribute to more personalized and effective treatment strategies for cardiovascular care.