Abstract
With the popularity of the metaverse, researchers are turning to augmented reality and virtual reality to innovate their recent pain points, particularly healthcare issues during COVID-19. At the same time, social robots can be a great tool for alleviating many challenges during the pandemic. However, before the integrated technology’s possibilities for the metaverse and social robots can be suitably harnessed, certain recent developments for integration during the pandemic should be addressed. For this reason, this paper proposes a new systematic summary of pioneering social robotic systems using the metaverse through immersive experiences from an interdisciplinary healthcare perspective during the COVID-19 outbreak. We also highlight social robots to deal with medical healthcare issues during the virus outbreak both elderly adults and younger people. Moreover, we compare recent metaverse-driven social robotic works for dealing with assisted living and healthcare issues through telepresence and remote interaction during COVID-19. Ultimately, we provide a recommendation and forecast a future scenario for the integration between socially interactive robots and metaverse technology to improve and help the quality of life both in the current COVID-19 situation and in the post-COVID-19 society.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Khataee, H., Scheuring, I., Czirok, A., Neufeld, Z.: Effects of social distancing on the spreading of COVID-19 inferred from mobile phone data. Sci. Rep. 11, 1661 (2021)
Kim, H., et al.: Social distancing and mask-wearing could avoid recurrent stay-at-home restrictions during COVID-19 respiratory pandemic in New York City. Sci. Rep. 12, 10312 (2022)
MarroquÃna, B., Vine, V., Morgan, R.: Mental health during the COVID-19 pandemic: Effects of stay-at-home policies, social distancing behavior, and social resources. Psych. Res.293, 8555 (2020)
Brotto, D., et al.: How great is the negative impact of masking and social distancing and how can we enhance communication skills in the elderly people? Aging Clin. Exp. Res.33(5), 1157–1161 (2021). https://doi.org/10.1007/s40520-021-01830-1
Karl, K.A., Peluchette, J.V., Aghakhani, N.: Virtual Work Meetings During the COVID-19 Pandemic: The Good, Bad, and Ugly. SAGE Public Health Emergency Collection, Small Group Res. 53, 3 (2022)
Parsons, D., Gander, T., Baker, K., Vo, D.: The Post-COVID-19 Impact on Distance Learning for New Zealand Teachers. Int. J. Online Pedagog. Course Des. 12, 1 (2022)
Vogel, J., Ajoudani, A.: Virtual conferences in times of COVID-19: embracing the potential [Young Professionals]. IEEE Robotics Autom. Mag. 27(3), 19 (2020)
Kerdvibulvech, C., Dong, Z.Y.: Roles of artificial intelligence and extended reality development in the Post-COVID-19 Era. In: Stephanidis, C., et al. (eds.) HCII 2021. LNCS, vol. 13095, pp. 445–454. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-90963-5_34
Follmann, A., et al.:  Reducing Loneliness in Stationary Geriatric Care with Robots and Virtual Encounters—A Contribution to the COVID-19 Pandemic Int. J. Environ. Res. Public Health 18(9), 4846 (2021). https://doi.org/10.3390/ijerph18094846
Getson, C., Goldie N.: Socially assistive robots helping older adults through the pandemic and life after COVID-19. Robotics 10(3), 106 (2021). https://doi.org/10.3390/robotics10030106
Tang, R., Zheng, J., Wang, S.: Design of novel end-effectors for robot-assisted swab sampling to combat respiratory infectious diseases. In: Annual International Conference on IEEE Engineering Medicine and Biology Society, vol. 2021, pp. 4757–4760 (2021). https://doi.org/10.1109/EMBC46164.2021.9630889. PMID: 34892274
Getson, C., Nejat, G.: The adoption of socially assistive robots for long-term care: During COVID-19 and in a post-pandemic society. Healthc Manage Forum 17, 8404704221106406 (2022) doi: https://doi.org/10.1177/08404704221106406. Epub ahead of print. PMID: 35714374; PMCID: PMC9207582
Miller, J., McDaniel, T.: Social robotics to address isolation and depression among the aging during and after COVID-19. In: Stephanidis, C., Antona, M., Ntoa, S. (eds.) HCII 2021. CCIS, vol. 1420, pp. 164–171. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-78642-7_22
Courtney, P., Royall, P.G.: Using robotics in laboratories during the COVID-19 outbreak: a review. IEEE Robot. Autom. Mag. 28(1), 28–39 (2021). https://doi.org/10.1109/MRA.2020.3045067
Gao, A., et al.:Â Progress in robotics for combating infectious diseases. Sci Robot. Â 6(52), eabf1462 (2021). doi: https://doi.org/10.1126/scirobotics.abf1462. PMID: 34043552
Di Lallo, A., Murphy, R., Krieger, A., Zhu, J., Taylor, R.H., Su, H.: Medical robots for infectious diseases: lessons and challenges from the COVID-19 pandemic. IEEE Robot. Autom. Mag. 28(1), 18–27 (2021). https://doi.org/10.1109/MRA.2020.3045671
Badia, S.B., et al.: Virtual reality for safe testing and development in collaborative robotics: challenges and perspectives. Electronics 11(11), 1726 (2022). https://doi.org/10.3390/electronics11111726
Sobrepera, M.J., Lee, V.G., Garg, S., Mendonca, R., Johnson, M.J.: Perceived usefulness of a social robot augmented telehealth platform by therapists in the United States. IEEE Robot Autom Lett. 6(2), 2946–2953 (2021). Epub 2021 Feb 25. PMID: 33748417; PMCID: PMC7978113 doi: https://doi.org/10.1109/lra.2021.3062349
Huang, B., Timmons, N.G., Li.m Q.:. Augmented reality with multi-view merging for robot teleoperation. In: Companion of the 2020 ACM/IEEE International Conference on Human-Robot Interaction (HRI 2020). Association for Computing Machinery, New York, pp. 260–262 (2020). https://doi.org/10.1145/3371382.3378336
Jain, A., Sharma, A., Wang, J., Ram, M.: Use of AI, robotics, and modern tools to fight Covid-19. In: Use of AI, Robotics, and Modern Tools to Fight Covid-19. River Publishers (2021)
Sushma, M., Anamika, R.: 13 Virtual reality: solution to reduce the impact of COVID-19 on global economy. In: Use of AI, Robotics, and Modern Tools to Fight Covid-19, pp. 195–210. River Publishers, IEEE (2021)
Dos Reis Alves, S.F., Uribe-Quevedo, A., Chen, D., Morris, J., Radmard, S.: Leveraging simulation and virtual reality for a long term care facility service robot during COVID-19, SVR 2021: 187–191 (2021)
Motaharifar, M.: Applications of haptic technology, virtual reality, and artificial intelligence in medical training Dduring the COVID-19 pandemic. Front. Robot. AI 8,  612949 (2021)
Abdelaal, A.E., Avinash, A., Kalia, M., Hager, G.D., Salcudean, S.E.: A multi-camera, multi-view system for training and skill assessment for robot-assisted surgery. Int. J. Comput. Assist. Radiol. Surg. 15(8), 1369–1377 (2020). https://doi.org/10.1007/s11548-020-02176-1
Wei, D., Huang, B., Li, Q.: Multi-view merging for robot teleoperation with virtual reality. IEEE Robot. Autom. Lett 6(4), 8537–8544 (2021). https://doi.org/10.1109/LRA.2021.3109348
Siriborvornratanakul, T.: Human behavior in image-based Road Health Inspection Systems despite the emerging AutoML. J. Big Data 9, 96 (2022). https://doi.org/10.1186/s40537-022-00646-8
de Freitas,F.V., Gomes, M.V.M., Winkler, I.: Benefits and challenges of virtual-reality-Based industrial usability testing and design reviews: a patents landscape and literature review. Appli. Sci. 12(3), 1755 (2022). https://doi.org/10.3390/app12031755
Acknowledgments
This research presented herein was partially supported by a research grant from the Research Center, NIDA (National Institute of Development Administration).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Kerdvibulvech, C., Chang, CC. (2022). A New Study of Integration Between Social Robotic Systems and the Metaverse for Dealing with Healthcare in the Post-COVID-19 Situations. In: Cavallo, F., et al. Social Robotics. ICSR 2022. Lecture Notes in Computer Science(), vol 13818. Springer, Cham. https://doi.org/10.1007/978-3-031-24670-8_35
Download citation
DOI: https://doi.org/10.1007/978-3-031-24670-8_35
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-24669-2
Online ISBN: 978-3-031-24670-8
eBook Packages: Computer ScienceComputer Science (R0)