Evidence map›Paper›PMID 34976569›Full record

ArticleIEEE access : practical innovations, open solutions2021

Robots Under COVID-19 Pandemic: A Comprehensive Survey.

Yang Shen, Dejun Guo, Fei Long, Luis A Mateos, Houzhu Ding, Zhen Xiu, Randall B Hellman, Adam King, Shixun Chen, Chengkun Zhang and 1 more

Abstract read
In one paragraph

Article in IEEE access : practical innovations, open solutions, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

39 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Mobile robots for isolation-room hospital settings: A scenario-based preliminary study.Computational and structural biotechnology journal · 2024
    Article
  6. Article
  7. Article
  8. Review
  9. Risks of Drone Use in Light of Literature Studies.Sensors (Basel, Switzerland) · 2024
    Review
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Evolution from Medical Imaging to Visualized Medicine.Advances in experimental medicine and biology · 2023
    Article
  18. Visualization in Anatomy Education.Advances in experimental medicine and biology · 2023
    Article
  19. Article
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Yang ShenUBTECH North America Research and Development Center Pasadena CA 91101 USA.ORCID https://orcid.org/0000-0003-1685-5583
Dejun GuoUBTECH North America Research and Development Center Pasadena CA 91101 USA.ORCID https://orcid.org/0000-0002-5331-4228
Fei LongUBTECH North America Research and Development Center Pasadena CA 91101 USA.ORCID https://orcid.org/0000-0001-7469-5579
Luis A MateosUBTECH North America Research and Development Center Pasadena CA 91101 USA.ORCID https://orcid.org/0000-0002-9595-9067
Houzhu DingUBTECH North America Research and Development Center Pasadena CA 91101 USA.ORCID https://orcid.org/0000-0002-2856-3599
Zhen XiuUBTECH North America Research and Development Center Pasadena CA 91101 USA.ORCID https://orcid.org/0000-0002-4952-6797
Randall B HellmanUBTECH North America Research and Development Center Pasadena CA 91101 USA.ORCID https://orcid.org/0000-0001-6287-1707
Adam KingUBTECH North America Research and Development Center Pasadena CA 91101 USA.ORCID https://orcid.org/0000-0003-0632-8317
Shixun ChenUBTECH North America Research and Development Center Pasadena CA 91101 USA.ORCID https://orcid.org/0000-0002-6270-7947
Chengkun ZhangUBTECH North America Research and Development Center Pasadena CA 91101 USA.ORCID https://orcid.org/0000-0001-9007-0106
Huan TanUBTECH North America Research and Development Center Pasadena CA 91101 USA.ORCID https://orcid.org/0000-0002-2451-9777

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As a result of the difficulties brought by COVID-19 and its associated lockdowns, many individuals and companies have turned to robots in order to overcome the challenges of the pandemic. Compared with traditional human labor, robotic and autonomous systems have advantages such as an intrinsic immunity to the virus and an inability for human-robot-human spread of any disease-causing pathogens, though there are still many technical hurdles for the robotics industry to overcome. This survey comprehensively reviews over 200 reports covering robotic systems which have emerged or have been repurposed during the past several months, to provide insights to both academia and industry. In each chapter, we cover both the advantages and the challenges for each robot, finding that robotics systems are overall apt solutions for dealing with many of the problems brought on by COVID-19, including: diagnosis, screening, disinfection, surgery, telehealth, care, logistics, manufacturing and broader interpersonal problems unique to the lockdowns of the pandemic. By discussing the potential new robot capabilities and fields they applied to, we expect the robotics industry to take a leap forward due to this unexpected pandemic.

Indexed as

autonomous systemsCOVID-19droneslearningpublic healthreviewrobotsSARS-CoV-2sensorssurvey

Identifiers

PMID34976569
PMCPMC8675561

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.