International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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Human Digital Twin Technology Using IoT In Field Of Personalised Healthcare

Author(s) Mr. Anmol Kumar
Country India
Abstract IoT-integrated HDT represents a revolutionary methodology for personalized medicine, allowing for real-time, data-driven simulations of patient physiology, behavior, and treatment responses. This research was necessary because proactive, individual care is increasingly required in the face of growing chronic diseases and healthcare inefficiencies-a motivation intensified by the gaps in conventional systems and the promising role of IoT-empowered HDTs in strengthening predictive analytics and ensuring better patient outcomes.
The study conducted a review of 40 peer-reviewed papers from reputed sources like IEEE, Springer, and Elsevier on the applications of HDT-IoT in healthcare during 2023-2025, following a structured multi-phase methodology. The different phases included the collection and selection of the literature, mapping 8 high-severity challenges - cybersecurity, scalability, and ML accuracy among others - comparative mapping with severity scores and sector tags, specializing in 10 papers regarding personalized healthcare, and framework development. Key findings included commonly identified IoT use cases, such as wearables-based vitals monitoring and predictive analytics for chronic diseases, and AI/ML-driven personalization, while mapping challenges that clearly indicated deployment bottlenecks such as data privacy and interoperability.
It has also advocated for a challenge-centric framework, with a modular architecture of HDT (IoT Data Layer → Semantic Engine → ML Personalization → Dashboard Interface) to reduce barriers and drive ethical and scalable solutions. Deliverables will include comparison tables, academic presentations, and wireframes that can be used practically.
This work contributes a diagnostic tool to the HDT-IoT implementations that advance personalized healthcare and reduce health disparities and policymaking. Testing through empirical pilots to validate the framework is recommended for future research.
Keywords Human Digital Twin: Core Concept of Virtual Patient Models, Internet of Things: The enabling technology for data collection with real-time integration, Personalised Health Care: Medical interventions tailored to each individual, Predictive Analytics: Stronger focus on forecasting health outcomes using data, Challenge Centric Framework: The approach to identifying and addressing the deployment barriers, Modular HDT Architecture: A proposed design for scalability and ethics, IoT Applications in Healthcare: Specific uses include wearables and monitoring, Data Privacy and Interoperability: Key challenges in HDT-IoT systems, Real-Time Data Simulation
Field Medical / Pharmacy
Published In Volume 7, Issue 6, November-December 2025
Published On 2025-11-25
DOI https://doi.org/10.36948/ijfmr.2025.v07i06.61068
Short DOI https://doi.org/hbcnv6
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