Chapter 14
6G for Healthcare
Chamitha de Alwis,
Quoc-Viet Pham, Madhusanka Liyanage,
Chamitha de Alwis
University of Bedfordshire, Luton, United Kingdom
Search for more papers by this authorBook Author(s):Chamitha de Alwis,
Quoc-Viet Pham, Madhusanka Liyanage,
Chamitha de Alwis
University of Bedfordshire, Luton, United Kingdom
Search for more papers by this authorFirst published: 25 November 2022
Summary
Sixth-generation (6G) is envisaged to play a key role in emerging healthcare applications. This chapter discusses the evolution of telehealth toward intelligent healthcare applications. It details emerging trends of intelligent healthcare applications. The chapter also focuses on security and privacy aspects of future healthcare applications. The emergence of fifth-generation networks have boosted the development of telehealth and smart healthcare applications. Artificial Intelligence-driven intelligent healthcare will be developed based on various new methodologies including Quality of Life, Intelligent Wearable Devices, Intelligent Internet of Medical Things, Hospital-to-Home, and new business models. Many studies have considered 6G as a key enabler of intelligent healthcare. Body Area Networks with integrated mobile Health systems are advancing toward the personalized health monitoring and management. Extended Reality is an emerging immersive technology with the fusion of physical and virtual worlds where wearables and computers generate human–machine interactions.
References
- W. Saad , M. Bennis , and M. Chen , “ A vision of 6G wireless systems: Applications, trends, technologies, and open research problems ,” IEEE Network , vol. 34 , no. 3 , pp. 134 – 142 , 2019 .
- L. Mucchi , S. Jayousi , S. Caputo , E. Paoletti , P. Zoppi , S. Geli , and P. Dioniso , “ How 6G technology can change the future wireless healthcare ,” in 2020 2nd 6G Wireless Summit (6G SUMMIT) IEEE, 2020 , pp. 1 – 6 .
- F. Tariq , M. R. Khandaker , K.-K. Wong , M. A. Imran , M. Bennis , and M. Debbah , “ A speculative study on 6G ,” IEEE Wireless Communications , vol. 27 , no. 4 , pp. 118 – 125 , 2020 .
- I. F. Akyildiz , A. Kak , and S. Nie , “ 6G and beyond: The future of wireless communications systems ,” IEEE Access , vol. 8 , pp. 133 995 – 134 030 , 2020 .
-
A. Mahajan
,
G. Pottie
, and
W. Kais er
, “
Transformation in healthcare by wearable devices for diagnostics and guidance of treatment
,”
ACM Transactions on Computing for Healthcare
, vol.
1
, no.
1
, pp.
1
–
12
,
2020
.
10.1145/3361561 Google Scholar
- 3GPP , “ Study on Communication Services for Critical Medical Applications ,” Technical Report, November 2018. [Online]. Available: https://www.3gpp.org/ftp/Specs/archive/22_series/22.826/ .
- 3GPP , “ Study on Communication for Automation in Vertical Domains (CAV) ,” Technical Report, December 2018. [Online]. Available: https://portal.3gpp.org/desktopmodules/Specifications/SpecificationDetails.aspx?specificationId=3187 .
- X. Ge , R. Zhou , and Q. Li , “ 5G NFV-based tactile internet for mission-critical IoT services ,” IEEE Internet of Things Journal , vol. 7 , no. 7 , pp. 6150 – 6163 , 2020 .
- A. Valkanis , P. Nicopolitidis , G. Papadimitriou , D. Kallergis , C. Douligeris , and P. D. Bamidis , “ Efficient resource allocation in tactile-capable ethernet passive optical healthcare LANs ,” IEEE Access , vol. 8 , pp. 52 981 – 52 995 , 2020 .
- K. Paranjape , M. Schinkel , and P. Nanayakkara , “ Short keynote paper: Mainstreaming personalized healthcare–transforming healthcare through new era of artificial intelligence ,” IEEE Journal of Biomedical and Health Informatics , vol. 24 , no. 7 , pp. 1860 – 1863 , 2020 .
- Y. Chen , X. Qin , J. Wang , C. Yu , and W. Gao , “ FedHealth: A federated transfer learning framework for wearable healthcare ,” IEEE Intelligent Systems , vol. 35 , no. 4 , pp. 83 – 93 , 2020 .
- N. Deepa , Q.-V. Pham , D. C. Nguyen , S. Bhattacharya , B. Prabadevi , T. R. Gadekallu , P. K. R. Maddikunta , F. Fang , and P. N. Pathirana , “ A survey on blockchain for big data: Approaches, opportunities, and future directions ,” Future Generation Computer Systems , vol. 131 , pp. 209 – 226 , 2022 .
- D. P. Isravel , S. Silas , and E. B. Rajsingh , “ SDN-based traffic management for personalized ambient assisted living healthcare system ,” in Intelligence in Big Data Technologies–Beyond the Hype . Springer , 2020 , pp. 379 – 388 .
- S. Movassaghi , M. Abolhasan , J. Lipman , D. Smith , and A. Jamalipour , “ Wireless body area networks: A survey ,” IEEE Communication surveys and tutorials , vol. 16 , no. 3 , pp. 1658 – 1686 , 2014 .
- I. F. Akyildiz , M. Pierobon , S. Balasubramaniam , and Y. Koucheryavy , “ The internet of bio-nano things ,” IEEE Communications Magazine , vol. 53 , no. 3 , pp. 32 – 40 , 2015 .
- M. S̆is̆kins , M. Lee , D. Wehenkel , R. van Rijn , T. W. de Jong , J. R. Renshof , B. C. Hopman , W. S. Peters , D. Davidovikj , H. S. van der Zant et al ., “ Sensitive capacitive pressure sensors based on graphene membrane arrays ,” Microsystems & Nanoengineering , vol. 6 , no. 1 , pp. 1 – 9 , 2020 .
- N. A. Abbasi and O. B. Akan , “ An informati on theoretical analysis of human insulin-glucose system toward the internet of bio-nano things ,” IEEE Transactions on Nanobioscience , vol. 16 , no. 8 , pp. 783 – 791 , 2017 .
- J. Wang , M. Peng , Y. Liu , X. Liu , and M. Daneshmand , “ Performance analysis of signal detection for amplify-and-forward relay in diffusion-based molecular communication systems ,” IEEE Internet of Things Journal , vol. 7 , no. 2 , pp. 1401 – 1412 , 2020 .
- M. Kuscu , E. Dinc , B. A. Bilgin , H. Ramezani , and O. B. Akan , “ Transmitter and receiver architectures for molecular communications: A survey on physical design with modulation, coding, and detection techniques ,” Proceedings of the IEEE , vol. 107 , no. 7 , pp. 1302 – 1341 , 2019 .
- T. Hewa , A. Kalla , A. Nag , M. Ylianttila , and M. Liyanage , “ Blockchain for 5G and IoT: Opportunities and challenges .”
-
N. M. Kumar
and
P. K. Mallick
, “
Blockchain technology for security issues and challenges in iot
,”
Procedia Computer Science
, vol.
132
, pp.
1815
–
1823
,
2018
.
10.1016/j.procs.2018.05.140 Google Scholar
- EC The High-Level Expert Group on Artificial Intelligence (AI HLEG) , “Ethics guidelines for trustworthy ai,” 2019 . [Online]. Available: https://digital-strategy.ec.europa.eu/en/library/ethics-guidelines-trustworthy-ai .
