The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
Service Robots in the Healthcare Sector
Open accessAbstract
Traditionally, advances in robotic technology have been in the manufacturing industry due to the need for collaborative robots. However, this is not the case in the service sectors, especially in the healthcare sector. The lack of emphasis put on the healthcare sector has led to new opportunities in developing service robots that aid patients with illnesses, cognition challenges and disabilities. Furthermore, the COVID-19 pandemic has acted as a catalyst for the development of service robots in the healthcare sector in an attempt to overcome the difficulties and hardships caused by this virus. The use of service robots are advantageous as they not only prevent the spread of infection, and reduce human error but they also allow front-line staff to reduce direct contact, focusing their attention on higher priority tasks and creating separation from direct exposure to infection. This paper presents a review of various types of robotic technologies and their uses in the healthcare sector. The reviewed technologies are a collaboration between academia and the healthcare industry, demonstrating the research and testing needed in the creation of service robots before they can be deployed in real-world applications and use cases. We focus on how robots can provide benefits to patients, healthcare workers, customers, and organisations during the COVID-19 pandemic. Furthermore, we investigate the emerging focal issues of effective cleaning, logistics of patients and supplies, reduction of human errors, and remote monitoring of patients to increase system capacity, efficiency, resource equality in hospitals, and related healthcare environments.
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Cites
The Psychological Impact of Quarantine and How to Reduce It: Rapid Review of the Evidence
Brooks, S. K., Webster, R. K., Smith, L. E., Woodland, L., Wessely, S., Greenberg, N., & Rubin, G. J. (2020) · doi:10.2139/ssrn.3532534 · Cited by 16,394
The psychological impact of quarantine and how to reduce it: Rapid review of the evidence
Brooks, S. K., Webster, R. K., Smith, L. E., Woodland, L., Wessely, S., Greenberg, N., & Rubin, G. J. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30460-8 · Cited by 16,378
Mende, M., Scott, M. L., van Doorn, J., Grewal, D., & Shanks, I. (2019) · Journal of Marketing Research · doi:10.1177/0022243718822827 · Cited by 1,197
The grand challenges of Science Robotics
Yang, G.-Z., Bellingham, J., Dupont, P. E., Fischer, P., Floridi, L., Full, R., Jacobstein, N., Kumar, V., McNutt, M., Merrifield, R., et al. (2018) · Science Robotics · doi:10.1126/scirobotics.aar7650 · Cited by 1,177
Tuckson, R. V., Edmunds, M., & Hodgkins, M. L. (2017) · New England Journal of Medicine · doi:10.1056/nejmsr1503323 · Cited by 907
Human–Robot Interaction: Status and Challenges
Sheridan, T. B. (2016) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720816644364 · Cited by 786
Health care robotics: qualitative exploration of key challenges and future directions
Cresswell, K., Cunningham-Burley, S., & Sheikh, A. (2018) · Journal of Medical Internet Research · doi:10.2196/10410 · Cited by 220 · cited 2×
“A solution to this is to design humanoid robots with a visible demarcation between human and robotic features; for instance, designing the robot to have wheels instead of legs [12].”
BackgroundOdekerken-Schröder, G., Mele, C., Russo-Spena, T., Mahr, D., & Ruggiero, A. (2020) · Journal of Service Management · doi:10.1108/josm-05-2020-0148 · Cited by 212
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Sillice, M. A., Morokoff, P. J., Ferszt, G., Bickmore, T., Bock, B. C., Lantini, R., & Velicer, W. F. (2018) · Journal of Medical Internet Research · doi:10.2196/jmir.7640 · Cited by 56 · cited 1×
“All things considered, personal assistant robots that have support functions have been shown to not only assist older people, but to also better the quality of life for users, improving behaviour through physical and mental exercises [140,145].”
Background
Cited by
Data science, artificial intelligence and the third wave of digital era governance
Dunleavy, P., & Margetts, H. (2023) · doi:10.31219/osf.io/f3rza · Cited by 186
Data science, artificial intelligence and the third wave of digital era governance
Dunleavy, P., & Margetts, H. (2025) · Public Policy and Administration · doi:10.1177/09520767231198737 · Cited by 186
VLATest: Testing and Evaluating Vision-Language-Action Models for Robotic Manipulation
Wang, Z., Zhou, Z., Song, J., Huang, Y., Shu, Z., & Ma, L. (2025) · Proceedings of the ACM on Software Engineering · doi:10.1145/3729343 · Cited by 14
Metadata
- Authors
- Holland, J., Kingston, L., McCarthy, C., Armstrong, E., O’Dwyer, P., Merz, F., & McConnell, M.
- Venue
- Robotics
- Publisher
- MDPI AG
- Published
- 2021-03-11
- Volume
- 10
- Issue
- 1
- Pages
- 47
- ISSN
- 2218-6581 (ISSN-L)
- OpenAlex
- W3134399564
- Cited by
- 322
- References
- 10
- FWCI
- 19.98
- Type
- journal article
- Language
- en
- Open access
- gold
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
