AI-Powered AR/VR for Augmenting Patient Education and Empowerment in Chronic Disease Management
DOI:
https://doi.org/10.63682/jns.v14i4.2438Keywords:
Artificial Intelligence, Augmented Reality, Virtual Reality, Patient Education, Chronic Disease Management, AI in Healthcare, Digital Health LiteracyAbstract
Chronic diseases such as diabetes, cardiovascular disorders, and neurodegenerative conditions present significant challenges in patient education and long-term management. Traditional patient education methods, including pamphlets, face-to-face counseling, and static digital resources, often fail to engage patients effectively. Emerging technologies such as Artificial Intelligence (AI), Augmented Reality (AR), and Virtual Reality (VR) offer a transformative approach to chronic disease education, improving patient engagement, comprehension, and self-management capabilities. AI-powered AR/VR applications create immersive learning experiences, allowing patients to visualize disease progression, simulate treatment options, and receive personalized guidance. This paper explores the core technologies underpinning AI-driven AR/VR, their integration for patient education, and the empowerment of individuals in chronic disease self-management. Additionally, the paper discusses the technical, ethical, and scalability challenges while proposing future research directions for optimizing these technologies for real-world deployment.
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American Diabetes Association. (2025). Diabetes care and patient education strategies: Integrating technology for better outcomes. Diabetes Care Journal, 48(2), 223-238.
Bhattacharya, S., & Gupta, R. (2025). Artificial intelligence in healthcare: Applications, challenges, and future prospects. Journal of Medical Informatics, 62(3), 321-345.
European Society of Cardiology. (2025). Hypertension and cardiovascular risks: The role of patient awareness and education in disease management. Cardiovascular Research, 58(4), 556-574.
Global Health Technology Report. (2025). Barriers to AR/VR adoption in healthcare: Cost, privacy, and implementation challenges. Health Tech Review, 14(1), 89-107.
Patel, K., & Zhang, L. (2025). Comparative analysis of AR/VR-based education versus traditional methods in patient engagement. AI in Healthcare Journal, 37(2), 205-222.
PWC Health Research Institute. (2025). The future of AI in patient engagement: Ethical challenges and industry trends. Healthcare Policy Review, 12(2), 193-210.
World Health Organization (WHO). (2025). The global burden of chronic diseases: Trends, challenges, and technological interventions. WHO Technical Report Series, 785, 1-68.
Zhang, X., Lee, M., & Chen, H. (2025). AI-powered virtual reality simulations in medical education and chronic disease management. Journal of Medical Simulations, 29(1), 145-163.
Ali, S., Abdullah, N., Armand, T. P. T., Athar, A., Hussain, A., Ali, M., Yaseen, M., Joo, M., & Kim, H. (2023). Metaverse in Healthcare Integrated with Explainable AI and Blockchain: Enabling Immersiveness, Ensuring Trust, and Providing Patient Data Security. Sensors, 23(2), 565. https://doi.org/10.3390/s23020565
Chengoden, R., Victor, N., Huynh-The, T., Yenduri, G., Jhaveri, R. H., Alazab, M., Bhattacharya, S., Hegde, P., Maddikunta, P. K. R., & Gadekallu, T. R. (2023). Metaverse for Healthcare: A survey on potential applications, challenges and future directions. IEEE Access, 11, 12765–12795. https://doi.org/10.1109/access.2023.3241628
Familoni, N. B. T., & Babatunde, N. S. O. (2024). USER EXPERIENCE (UX) DESIGN IN MEDICAL PRODUCTS: THEORETICAL FOUNDATIONS AND DEVELOPMENT BEST PRACTICES. Engineering Science & Technology Journal, 5(3), 1125–1148. https://doi.org/10.51594/estj.v5i3.975
Gleiss, A., Kohlhagen, M., & Pousttchi, K. (2021). An apple a day – how the platform economy impacts value creation in the healthcare market. Electronic Markets, 31(4), 849–876. https://doi.org/10.1007/s12525-021-00467-2
Kuru, K. (2023). MetaOmniCity: Toward Immersive urban Metaverse Cyberspaces using smart City digital twins. IEEE Access, 11, 43844–43868. https://doi.org/10.1109/access.2023.3272890
Marston, H. R., Shore, L., & White, P. (2020). How does a (Smart) Age-Friendly Ecosystem Look in a Post-Pandemic Society? International Journal of Environmental Research and Public Health, 17(21), 8276. https://doi.org/10.3390/ijerph17218276
Martins, N. R. B., Angelica, A., Chakravarthy, K., Svidinenko, Y., Boehm, F. J., Opris, I., Lebedev, M. A., Swan, M., Garan, S. A., Rosenfeld, J. V., Hogg, T., & Freitas, R. A. (2019). Human Brain/Cloud Interface. Frontiers in Neuroscience, 13. https://doi.org/10.3389/fnins.2019.00112
Naqishbandi, T. A., Mohamed, E. S., & Veronese, G. (2023). Metaverse! International Journal of E-Adoption, 15(2), 1–21. https://doi.org/10.4018/ijea.316537
Navaz, A. N., Serhani, M. A., Kassabi, H. T. E., Al-Qirim, N., & Ismail, H. (2021). Trends, technologies, and key challenges in smart and connected healthcare. IEEE Access, 9, 74044–74067. https://doi.org/10.1109/access.2021.3079217
Nowak, T. W., Sepczuk, M., Kotulski, Z., Niewolski, W., Artych, R., Bocianiak, K., Osko, T., & Wary, J. (2021). Verticals in 5G MEC-Use cases and security challenges. IEEE Access, 9, 87251–87298. https://doi.org/10.1109/access.2021.3088374
Patel, V., Chesmore, A., Legner, C. M., & Pandey, S. (2021). Trends in workplace wearable technologies and Connected‐Worker solutions for Next‐Generation occupational safety, health, and productivity. Advanced Intelligent Systems, 4(1). https://doi.org/10.1002/aisy.202100099
Reddy, P., Sharma, B., & Chaudhary, K. (2020). Digital Literacy. International Journal of Technoethics, 11(2), 65–94. https://doi.org/10.4018/ijt.20200701.oa1
Sai, S., Gaur, A., Sai, R., Chamola, V., Guizani, M., & Rodrigues, J. J. P. C. (2024). Generative AI for Transformative Healthcare: A Comprehensive study of emerging models, applications, case studies, and limitations. IEEE Access, 12, 31078–31106. https://doi.org/10.1109/access.2024.3367715
Sasidhar, D. (2023). Data Integrity as a Code (DIAC). Trends in Computer Science and Information Technology, 001–120. https://doi.org/10.17352/ebook10121
Sobnath, D., Rehman, I. U., & Nasralla, M. M. (2019). Smart cities to improve mobility and quality of life of the visually impaired. In EAI/Springer Innovations in Communication and Computing (pp. 3–28). https://doi.org/10.1007/978-3-030-16450-8_1
Turab, M., & Jamil, S. (2023). A comprehensive survey of digital twins in healthcare in the era of Metaverse. BioMedInformatics, 3(3), 563–584. https://doi.org/10.3390/biomedinformatics3030039
Ullah, H., Manickam, S., Obaidat, M., Laghari, S. U. A., & Uddin, M. (2023). Exploring the potential of metaverse technology in healthcare: applications, challenges, and future directions. IEEE Access, 11, 69686–69707. https://doi.org/10.1109/access.2023.3286696
Vermesan, O., & Bacquet, J. (2017). Cognitive Hyperconnected Digital Transformation. In AI-Powered AR/VR for Augmenting Patient Education and Empowerment in Chronic Disease Management (pp. 1–310). https://doi.org/10.13052/rp-9788793609105
Vermesan, O., Eisenhauer, M., Sundmaeker, H., Guillemin, P., Serrano, M., Tragos, E. Z., Valiño, J., Van derWees, A., Gluhak, A., & Bahr, R. (2022). Internet of Things Cognitive Transformation Technology Research Trends and applications. In River Publishers eBooks (pp. 17–95). https://doi.org/10.1201/9781003337584-3
Yang, D., Zhou, J., Chen, R., Song, Y., Song, Z., Zhang, X., Wang, Q., Wang, K., Zhou, C., Sun, J., Zhang, L., Bai, L., Wang, Y., Wang, X., Lu, Y., Xin, H., Powell, C. A., Thüemmler, C., Chavannes, N. H., . . . Bai, C. (2022). Expert consensus on the metaverse in medicine. Clinical eHealth, 5, 1–9. https://doi.org/10.1016/j.ceh.2022.02.001
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