Engineering and Technology
| Open Access | Advanced AI-Driven Human Digital Twin Architectures Combining Smart Iot Networks And Cyber-Physical Intelligence For Personalized Medicine And Adaptive Rehabilitation Analytics
Dr. Suresh Koirala , Department of Information Technology Kathmandu Valley Science University Kathmandu, Nepal Dr. Anisha Rai , Faculty of Applied Engineering Everest National Institute of Technology Pokhara, NepalAbstract
The rapid evolution of healthcare digitalization has accelerated the development of intelligent human digital twin ecosystems that integrate artificial intelligence, Internet of Things (IoT) infrastructures, and cyber-physical healthcare systems. Human digital twin architectures represent virtual replicas of human physiological, behavioral, and clinical conditions capable of supporting predictive analytics, adaptive treatment planning, rehabilitation optimization, and personalized medicine. This research investigates advanced AI-driven human digital twin architectures that combine smart IoT networks with cyber-physical intelligence to enhance healthcare monitoring, clinical decision-making, and adaptive rehabilitation systems. The study critically synthesizes existing research related to digital twin healthcare infrastructures, sensor-enabled medical environments, AI-assisted medical modeling, and cyber-physical healthcare engineering. A research-oriented methodological framework is proposed to explain the interaction among data acquisition layers, AI processing engines, edge-cloud coordination, and adaptive rehabilitation analytics modules. The paper further evaluates the operational capabilities, limitations, and implementation barriers of intelligent digital twin healthcare ecosystems. Findings indicate that the integration of generative artificial intelligence, sensor fusion, cloud-edge orchestration, and cyber-physical intelligence significantly improves predictive treatment accuracy, remote rehabilitation monitoring, patient-specific simulation, and healthcare system responsiveness. However, challenges related to data interoperability, cybersecurity, privacy governance, computational scalability, and ethical accountability remain major concerns for practical implementation. The study contributes a comprehensive conceptual and analytical framework for future healthcare digital twin systems while emphasizing the need for secure, scalable, and intelligent architectures capable of supporting next-generation precision medicine and adaptive rehabilitation environments.
Keywords
Human Digital Twin, Personalized Medicine, Cyber-Physical Systems, Smart Healthcare
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Copyright (c) 2026 Dr. Suresh Koirala, Dr. Anisha Rai
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