<![CDATA[Heart disease in all its forms remains a significant health threat. Arrhythmia is a type of heart disease whose diagnosis and treatment still primarily rely on conventional electrocardiogram-based diagnosis. However, this approach is limited, as it is reactive and captures cardiac conditions only at the time of electrocardiogram measurement, making it unable to continuously and individually monitor arrhythmia progression for each patient. This study explores digital twin technology and develops human digital twin models for the treatment of arrhythmia patients. The modeling framework integrates three core components: geometrical modeling, physical modeling, and data-driven modeling to represent the human heart and cardiovascular system in a digital environment. The output of this integrative process has been implemented in the initial prototype of the Human Digital Twin Cockpit, which is designed to treat arrhythmia. This prototype enhances the existing diagnosis and treatment, and also incorporates a proactive simulation system. Evaluation and system testing have successfully demonstrated their ability to integrate geometric data from medical imaging and physical data from electrophysiological sensors to predict arrhythmia in various scenarios]]>
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