Metaverse for Digital Anti-Aging Healthcare: An Overview of Potential Use Cases Based on Artificial Intelligence, Blockchain, IoT Technologies, Its Challenges, and Future Directions
Source abstract
Abstract
Metaverse is the buzz technology of the moment raising attention both from academia and industry. Many stakeholders are considering an extension of their existing applications into the metaverse environment for more usability. The healthcare industry is gradually making use of the metaverse to improve quality of service and enhance living conditions. In this paper, we focus on the potential of digital anti-aging healthcare in the metaverse environment. We show how we can use metaverse environment to enhance healthcare service quality and increase the life expectancy of patients through more confident processes, such as chronic disease management, fitness, and mental health control, in the metaverse. The convergence of artificial intelligence (AI), blockchain (BC), Internet of Things (IoT), immersive technologies, and digital twin in the metaverse environment presents new scopes for the healthcare industry. By leveraging these technologies, healthcare providers can improve patient outcomes, reduce healthcare costs, and create new healthcare experiences for a better life, thus facilitating the anti-aging process. AI can be used to analyze large-scale medical data and make personalized treatment plans, while blockchain can create a secure and transparent healthcare data ecosystem. As for IoT devices, they collect real-time data from patients, which is necessary for treatment. Together, these technologies can transform the healthcare industry and improve the lives of patients worldwide. The suggestions highlighted in this paper are worthy to undergo implementation and create more benefits that will promote a digital anti-aging process for its users for a longer life experience.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: IoT and Edge/Fog Computing · Blockchain Technology Applications and Security · Virtual Reality Applications and Impacts
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Institute of Digital Anti-Aging Healthcare, Inje University, Gimhae 50834, Republic of Korea
Funding
MSIT (Ministry of Science ICT), Korea
References (100+)
Show source-provided references
1. MetaHealth-How will the Metaverse Change Health Care?
2. Lee, C.W. (2022). Application of Metaverse Service to Healthcare Industry: A Strategic Perspective. Int. J. Environ. Res. Public Health, 19.10.3390/ijerph192013038 ↗
3. Mejia, J.M.R., and Rawat, D.B. (2022, January 5–8). Recent Advances in a Medical Domain Metaverse: Status, Challenges, and Perspective. Proceedings of the 2022 Thirteenth International Conference on Ubiquitous and Future Networks (ICUFN), Barcelona, Spain.
4. Hopkins, J. (2021, February 16). Performs Its First Augmented Reality Surgeries in Patients. Available online: https://www.hopkinsmedicine.org/news/articles/johns-hopkins-performs-its-first-augmented-reality-surgeries-in-patients/.
5. Mozumder, M.A.I., Athar, A., Armand, T.P.T., Sheeraz, M.M., Uddin, S.M.I., and Kim, H.-C. (2023, January 19–22). Technological Roadmap of the Future Trend of Metaverse based on IoT, Blockchain, and AI Techniques in Metaverse Education. Proceedings of the 2023 25th International Conference on Advanced Communication Technology (ICACT), Pyeongchang, Republic of Korea.
6. Smart health intelligent healthcare systems in the metaverse, artificial intelligence, and data science era
7. Expert consensus on the metaverse in medicine10.1016/j.ceh.2022.02.001 ↗
8. What the Literature on Medicine, Nursing, Public Health, Midwifery, and Dentistry Reveals: An Overview of the Rapidly Approaching Metaverse10.57019/jmv.1132962 ↗
9. Metaverse phenomenon and its impact on health: A scoping review10.1016/j.imu.2022.101029 ↗
10. Athar, A., Ali, S.M., Mozumder, M.A.I., Ali, S., and Kim, H.-C. (2023, January 19–22). Applications and Possible Challenges of Healthcare Metaverse. Proceedings of the 2023 25th International Conference on Advanced Communication Technology (ICACT), Pyeongchang, Republic of Korea.10.23919/ICACT56868.2023.10079314 ↗
11. Prediction of User’s Intention to Use Metaverse System in Medical Education: A Hybrid SEM-ML Learning Approach10.1109/ACCESS.2022.3169285 ↗
12. The metaverse in education: Definition, framework, features, potential applications, challenges, and future research topics10.3389/fpsyg.2022.1016300 ↗
13. The metaverse in current digital medicine10.1016/j.ceh.2022.07.002 ↗
14. Bhattacharya, P., Obaidat, M.S., Savaliya, D., Sanghavi, S., Tanwar, S., and Sadaun, B. (2022, January 13–15). Metaverse assisted Telesurgery in Healthcare 5.0: An interplay of Blockchain and Explainable AI. Proceedings of the 2022 International Conference on Computer, Information and Telecommunication Systems (CITS), Piraeus, Greece.10.1109/CITS55221.2022.9832978 ↗
15. Yu, X., Owens, D., and Khazanchi, D. (2012, January 8–10). Building Socioemotional Environments in Metaverses for Virtual Teams in Healthcare: A Conceptual Exploration. Proceedings of the Health Information Science: First International Conference, HIS 2012, Beijing, China. Proceedings 1.10.1007/978-3-642-29361-0_3 ↗
16. Orchard, A., O’Gorman, M., La Vecchia, C., and Augmented, J.L. (May, January 29). Augmented reality smart glasses in focus: A user group report. Proceedings of the CHI Conference on Human Factors in Computing Systems Extended Abstracts, Orleans, LA, USA.
17. Metaverse: The future of immersive training10.1108/SHR-02-2022-0009 ↗
18. Integration of Artificial Intelligence, Blockchain, and Wearable Technology for Chronic Disease Management: A New Paradigm in Smart Healthcare10.1007/s11596-021-2485-0 ↗
19. A study on smart aging system for the elderly based on metaverse
20. Metaverse games: A game changer for healthcare?10.1089/cyber.2022.29246.editorial ↗
21. The Social Shaping of the Metaverse as an Alternative to the Imaginaries of Data-Driven Smart Cities: A Study in Science, Technology, and Society10.3390/smartcities5030043 ↗
22. Construction of an artificial intelligence system in dermatology: Effectiveness and consideration of Chinese Skin Image Database (CSID)10.1016/j.imed.2021.04.003 ↗
23. Utilization exercise rehabilitation using metaverse (vr·ar·mr·xr)
24. Ali, S., Armand, T.P.T., Athar, A., Hussain, A., Ali, M., Yaseen, M., Joo, M.-I., and Kim, H.-C. (2023). Metaverse in Healthcare Integrated with Explainable AI and Blockchain: Enabling Immersiveness, Ensuring Trust, and Providing Patient Data Security. Sensors, 23.10.3390/s23020565 ↗
25. The Best Predictor of the Future—The Metaverse, Mental Health, and Lessons Learned From Current Technologies10.2196/40410 ↗
26. The metaverse in cancer care: Applications and challenges10.1016/j.apjon.2022.100111 ↗
27. Moon, I., An, Y., Min, S., and Park, C. (2023). Therapeutic Effects of Metaverse Rehabilitation for Cerebral Palsy: A Randomized Controlled Trial. Int. J. Environ. Res. Public Health, 20.10.3390/ijerph20021578 ↗
28. Token Economies, and Chronic Diseases
29. (2022, September 01). Chronic Diseases, Available online: https://www.cdc.gov/chronicdisease/about/index.htm/.
30. Acute Exacerbation of a Chronic Obstructive Pulmonary Disease Prediction System Using Wearable Device Data, Machine Learning, and Deep Learning: Development and Cohort Study10.2196/22591 ↗
31. Fernández-Caramés, T.M., Froiz-Míguez, I., Blanco-Novoa, O., and Fraga-Lamas, P. (2019). Enabling the Internet of Mobile Crowdsourcing Health Things: A Mobile Fog Computing, Blockchain and IoT Based Continuous Glucose Monitoring System for Diabetes Mellitus Research and Care. Sensors, 19.10.3390/s19153319 ↗
32. Jourdan, T., Debs, N., and Frindel, C. (2021). The Contribution of Machine Learning in the Validation of Commercial Wearable Sensors for Gait Monitoring in Patients: A Systematic Review. Sensors, 21.10.3390/s21144808 ↗
33. Retinal photograph-based deep learning algorithms for myopia and a blockchain platform to facilitate artificial intelligence medical research: A retrospective multicohort study10.1016/S2589-7500(21)00055-8 ↗
34. Theodore, T.P., Mozumder, M.A.I., Ali, S., Amaechi, A.O., and Kim, H.-C. (2023). Developing a Low-Cost IoT-Based Remote Cardiovascular Patient Monitoring System in Cameroon. Healthcare, 11.10.3390/healthcare11020199 ↗
35. Rahman, A., Rashid, M., Barnes, S., Hossain, M.S., Hassanain, E., and Guizani, M. (2019, January 24–28). An IoT and Blockchain-Based Multi-Sensory In-Home Quality of Life Framework for Cancer Patients. Proceedings of the 2019 15th International Wireless Communications & Mobile Computing Conference (IWCMC), Tangier, Morocco.10.1109/IWCMC.2019.8766496 ↗
36. Patro, S.P., Padhy, N., and Sah, R.D. (2022). The Role of IoT and Blockchain: Techniques and Applications, Apple Academic Press.
37. Giannakopoulou, K.-M., Roussaki, I., and Demestichas, K. (2022). Internet of Things Technologies and Machine Learning Methods for Parkinson’s Disease Diagnosis, Monitoring and Management: A Systematic Review. Sensors, 22.10.3390/s22051799 ↗
38. Yu, J., Park, S., Kwon, S.-H., Ho, C.M.B., Pyo, C.-S., and Lee, H. (2020). AI-Based Stroke Disease Prediction System Using Real-Time Electromyography Signals. Appl. Sci., 10.10.3390/app10196791 ↗
39. (2022, February 04). Cancer Care in India. Available online: https://health.economictimes.indiatimes.com/news/industry/ai-blockchain-and-iot-can-transform-cancer-care-in-india/89339690.
40. (2022, May 23). Top Predictions for How Healthcare Will Evolve in the Metaverse in the Next Decade. Available online: https://wi4.org/blog/top-predictions-for-how-healthcare-will-evolve-in-the-metaverse-in-the-next-decade/.
41. (2022, February 06). Build the Fitness Metaverse. Available online: https://fitness-metaverse.com/metaverse/.
42. Augmented reality as an aid in maxillofacial surgery: Validation of a wearable system allowing maxillary repositioning10.1016/j.jcms.2014.09.001 ↗
43. Ali, S., Aich, S., Athar, A., and Kim, H. (2023, January 19–22). Medical Education, Training and Treatment Using XR in Healthcare. Proceedings of the 2023 25th International Conference on Advanced Communication Technology (ICACT), Pyeongchang, Republic of Korea.10.23919/ICACT56868.2023.10079321 ↗
44. (2022, July 10). VR Therapy: The Metaverse Will Reshape Mental Health Therapy. Available online: https://www.01remote.com/vr-therapy-the-metaverse-will-reshape-mental-health-therapy/.
45. Future of mental health in the metaverse10.1136/gpsych-2022-100825 ↗
46. Building Digital Twins of Cyber Physical Systems With Metaverse for Industry 5.0 and Beyond10.1109/MITP.2022.3225064 ↗
47. Artificial Intelligence for Metaverse: A Framework10.26599/AIR.2022.9150004 ↗
48. Mozumder, M.A.I., Sheeraz, M., Athar, A., Aich, S., and Kim, H.-C. (2022, January 13–16). Overview: Technology roadmap of the future trend of metaverse based on iot, blockchain, ai technique, and medical domain metaverse activity. Proceedings of the 2022 24th International Conference on Advanced Communication Technology (ICACT), Pyeongchang, Republic of Korea.10.23919/ICACT53585.2022.9728808 ↗
49. Artificial intelligence for the metaverse: A survey10.1016/j.engappai.2022.105581 ↗
50. Schmitt, M. (2023, March 24). Big Data Analytics in the Metaverse: Business Value Creation with Artificial Intelligence and Data-Driven Decision Making. Available online: https://dx.doi.org/10.2139/ssrn.4385347.10.2139/ssrn.4385347 ↗
51. Liu, B., and Yin, G. (2020, January 25–30). Chinese document classification with bi-directional convolutional language model. Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event.10.1145/3397271.3401248 ↗
52. Athiwaratkun, B., and Stokes, J.W. (2017, January 5–9). Malware classification with LSTM and GRU language models and a character-level CNN. Proceedings of the 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), New Orleans, LA, USA.10.1109/ICASSP.2017.7952603 ↗
53. A deep neural network-based model for named entity recognition for Hindi language10.1007/s00521-020-04881-z ↗
54. Multi-task learning model based on multi-scale CNN and LSTM for sentiment classi-fication10.1109/ACCESS.2020.2989428 ↗
55. BFGAN: Backward and Forward Generative Adversarial Networks for Lexically Constrained Sentence Generation10.1109/TASLP.2019.2943018 ↗
56. FixationNet: Forecasting Eye Fixations in Task-Oriented Virtual Environments10.1109/TVCG.2021.3067779 ↗
57. Wu, P., Ding, W., You, Z., and An, P. (2019, January 22–25). Virtual Reality Video Quality Assessment Based on 3d Convolutional Neural Networks. Proceedings of the 2019 IEEE International Conference on Image Processing (ICIP), Taipei, Taiwan.10.1109/ICIP.2019.8803023 ↗
58. Subjective and Objective Quality Assessment of 2D and 3D Foveated Video Compression in Virtual Reality10.1109/TIP.2021.3087322 ↗
59. DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs10.1109/TPAMI.2017.2699184 ↗
60. Cross-Attentional Bracket-shaped Convolutional Network for semantic image segmentation10.1016/j.ins.2020.06.023 ↗
61. PiCANet: Pixel-Wise Contextual Attention Learning for Accurate Saliency Detection10.1109/TIP.2020.2988568 ↗
62. Visual and semantic knowledge transfer for large scale semisupervised object detection10.1109/TPAMI.2017.2771779 ↗
63. Multi-Scale Deep Residual Learning-Based Single Image Haze Removal via Image Decomposition10.1109/TIP.2019.2957929 ↗
64. An Improved Enhancement Algorithm Based on CNN Applicable for Weak Contrast Images10.1109/ACCESS.2019.2963478 ↗
65. Spatial and Spectral Joint Super-Resolution Using Convolutional Neural Network10.1109/TGRS.2020.2964288 ↗
66. Chen, K., Gong, S., and Xiang, T. (2011, January 6–13). Human pose estimation using structural support vector machines. Proceedings of the 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops), Barcelona, Spain.
67. LCR-Net++: Multi-person 2D and 3D Pose Detection in Natural Images
68. Machine Learning Adoption in Blockchain-Based Smart Applications: The Challenges, and a Way Forward10.1109/ACCESS.2019.2961372 ↗
69. A Machine Learning Approach for Blockchain-Based Smart Home Networks Security10.1109/MNET.011.2000514 ↗
70. Hybrid Blockchain-Based Resource Trading System for Federated Learning in Edge Computing10.1109/JIOT.2020.3028101 ↗
71. Blockchain and federated learning for collaborative in-trusion detection in vehicular edge computing10.1109/TVT.2021.3076780 ↗
72. Maheswari, D., Ndruru, F.B.F., Rejeki, D.S., Moniaga, J.V., and Jabar, B.A. (2022, January 24–25). Systematic Literature Review on The Usage of IoT in The Metaverse to Support The Education System. Proceedings of the 2022 5th International Conference on Information and Communications Technology (ICOIACT), Yogyakarta, Indonesia.10.1109/ICOIACT55506.2022.9971816 ↗
73. Lee, L.-H., Braud, T., Zhou, P., Wang, L., Xu, D., Lin, Z., Kumar, A., Bermejo, C., and Hui, P. (2021). All one needs to know about metaverse: A complete survey on technological singularity, virtual ecosystem, and research agenda. arXiv.
74. Warke, V., Kumar, S., Bongale, A., and Kotecha, K. (2021). Sustainable Development of Smart Manufacturing Driven by the Digital Twin Framework: A Statistical Analysis. Sustainability, 13.10.3390/su131810139 ↗
75. Ning, H., Wang, H., Lin, Y., Wang, W., Dhelim, S., Farha, F., Ding, J., and Daneshmand, M. (2021). A Survey on Metaverse: The State-of-the-art, Technologies, Applications, and Challenges. arXiv.
76. Dhelim, S., Kechadi, T., Chen, L., Aung, N., Ning, H., and Atzori, L. (2022). Edge-enabled metaverse: The convergence of metaverse and mobile edge computing. arXiv.10.36227/techrxiv.19606954 ↗
77. (2022, October 04). How Edge Computing Will Support the Metaverse. Available online: http://www.techrepublic.com/article/edge-computing-supports-metaverse/.
78. Siniarski, B., De Alwis, C., Yenduri, G., Huynh-The, T., GÜr, G., Gadekallu, T.R., and Liyanage, M. (2022). Need of 6G for the Metaverse Realization. arXiv.
79. Channel State Information Prediction for 5G Wireless Communications: A Deep Learning Approach10.1109/TNSE.2018.2848960 ↗
80. Abdelmaged, M.A.M. (2023, March 24). Implementation of Virtual Reality in Healthcare, Entertainment, Tourism, Education, and Retail Sectors. Available online: https://mpra.ub.uni-muenchen.de/110491/.
81. Review of Innovative Immersive Technologies for Healthcare Applications10.36401/IDDB-21-04 ↗
82. Virtual Commerce in a Decentralized Blockchain-based Metaverse: Immersive Technologies, Computer Vision Algorithms, and Retail Business Analytics10.22381/lpi21202213 ↗
83. (2022, June 26). Metaverse in Operating Room is Changing Medicine Rapidly. Available online: http://www.koreabiomed.com/news/articleView.html?idxno=11477.
84. Erol, T., Mendi, A.F., and Doğan, D. (2020, January 22–24). The digital twin revolution in healthcare. Proceedings of the 2020 4th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), Istanbul, Turkey.10.1109/ISMSIT50672.2020.9255249 ↗
85. Boulos, M.N.K., and Zhang, P. (2021). Digital Twins: From Personalised Medicine to Precision Public Health. J. Pers. Med., 11.10.3390/jpm11080745 ↗
86. Sensor-Fault Detection, Isolation and Accommodation for Digital Twins via Modular Data-Driven Architecture10.1109/JSEN.2020.3029459 ↗
87. Digital Twin for Intelligent Context-Aware IoT Healthcare Systems10.1109/JIOT.2021.3051158 ↗
88. Adaptive federated learning and digital twin for industrial internet of things10.1109/TII.2020.3034674 ↗
89. HCI for health and wellbeing: Challenges and opportunities10.1016/j.ijhcs.2019.06.007 ↗
90. (2023, March 03). Quantum Computing and Healthcare: Learn More about These Applications. Available online: https://www.hitechnectar.com/blogs/quantum-computing-and-healthcare/.
91. Application of 3D reconstruction for surgical treatment of hepatic alveolar echinococcosis10.3748/wjg.v21.i35.10200 ↗
92. Quan, H., Dong, J., and Qian, X. (2021, January 9–12). Med-3d: 3d reconstruction of medical images based on struc-ture-from-motion via transfer learning. Proceedings of the 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Houston, TX, USA.10.1109/BIBM52615.2021.9669599 ↗
93. A revolution in health: Opportunities and chal-lenges of the Metaverse
94. Polona, C., André, M., and Maria, N. (2023, March 19). Metaverse: Opportunities, Risks and Policy Implications, EPRS: European Parliamentary Research Service. Belgium. Available online: https://policycommons.net/artifacts/2476871/metaverse/3498933/.
95. The Trend of Metaverse and Augmented & Virtual Reality Extending to the Healthcare System
96. A Survey on Metaverse: Fundamentals, Security, and Privacy10.1109/COMST.2022.3202047 ↗
97. (2022, April 17). Accessing the Growing Involvement of Metaverse in Healthcare. Available online: https://www.delveinsight.com/blog/metaverse-in-healthcare#PrivacyandSecurityintheMetaverse.
98. The potential impact of 5G telecommunication technology on ophthalmology10.1038/s41433-021-01450-z ↗
99. Artificial Intelligence in Ophthalmology in 2020: A Technology on the Cusp for Translation and Implementation10.1097/01.APO.0000656984.56467.2c ↗
100. Beede, E., Baylor, E., Hersch, F., Iurchenko, A., Wilcox, L., Ruamviboonsuk, P., and Vardoulakis, L.M. (2020, January 25–30). A Human-Centered Evaluation of a Deep Learning System Deployed in Clinics for the Detection of Diabetic Retinopathy. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems: Asso-ciation for Computing Machinery, Honolulu, HI, USA.10.1145/3313831.3376718 ↗