A Novel Medical Cyber-Physical Systems Based on Digital Twin-Driven Platform

工作流程 信息物理系统 计算机科学 医疗保健 系统集成 服务(商务) 数据库 经济增长 操作系统 经济 经济
作者
Leyao Zhang,Guangqian Yang,J. Li,Jeng-Min Liang
出处
期刊:International Journal of High Speed Electronics and Systems [World Scientific]
被引量:6
标识
DOI:10.1142/s0129156425401299
摘要

A Medical Cyber-Physical System (MCPS) represents a sophisticated healthcare framework seamlessly integrating cyber and physical elements to enhance medical processes, diagnostics, and patients. The integration of Artificial Intelligence (AI) into the healthcare system has been pivotal in advancing intelligent MCPS and ushering in an era of advanced healthcare solutions. The paradigm of smart hospitals aspires to implement intelligent solutions seamlessly integrating hardware and software to control, supervise, and monitor patients while assisting healthcare professionals. Such solution is essential for smart decision-making and enhancing healthcare services. However, complete utilization of this intelligent MCPS relies on an effective framework that should facilitate the interaction among patients, medical devices, AI services and hospital staff. This paper introduces a Digital Twin (DT)-based Smart Medical Cyber-Physical System (DT-MCPS) designed to enhance smart hospitals. Leveraging DT technology, DT-MCPS constructs a virtual replica of the hospital, facilitating precise control and supervision of patient care, coupled with service optimization through comprehensive data integration. DT-MCPS promotes personalized decision-making by seamlessly integrating medical records and real-time monitoring of physiological data, enabling predictive insights into disease progression. Moreover, DT-MCPS employs a model-based platform founded on web services to monitor the patient’s state in real-time while accurately simulating the hospital medical systems workflows and contributing to long-term health management. Experimental results showcase the efficacy of DT-MCPS in enhancing hospitalization services, streamlining real-time control, and achieving highly precise personalized patient diagnostics.
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