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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Sep 24, 2022
Open Peer Review Period: Sep 23, 2022 - Oct 3, 2022
Date Accepted: Feb 25, 2023
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Characteristics and Emerging Trends in Research on Rehabilitation Robots from 2001 to 2020: Bibliometric Study

Zhang Y, Liu X, Qiao X, Fan Y

Characteristics and Emerging Trends in Research on Rehabilitation Robots from 2001 to 2020: Bibliometric Study

J Med Internet Res 2023;25:e42901

DOI: 10.2196/42901

PMID: 37256670

PMCID: 10267796

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Intellectual Structure and Emerging Trend of Research on rehabilitation robots: A Bibliometric Study

  • Ying Zhang; 
  • Xiaoyu Liu; 
  • Xiaofeng Qiao; 
  • Yubo Fan

ABSTRACT

Background:

The past decades have seen rapid and vast developments of robots for the rehabilitation. Research on rehabilitation robots are involved in interdisciplinary fields, such as computer science, mechanical engineering, medicine, etc. It is a great challenge for researchers in a certain field to know an overall current situation and its developing trend.

Objective:

We performed a bibliometric study on the research of rehabilitation robots to characterize the intellectual structure and identify emerging trends in this field.

Methods:

Publication data were derived from the Web of Science Core Collection to form a database. We used scientometric open software, CiteSpace and VOSViewer to perform bibliometric analysis and visualization. The intellectual structure and emerging trends were examined through co-occurrence and co-citation network. Landmark publications in the research field of rehabilitation robots were identified using cluster metrics, such as betweenness centrality and burst.

Results:

Through data retrieval, cleaning and deduplication, we retrieved 9’287 publications and 110’619 cited references on rehabilitation robots between 2001 and 2020. A co-occurrence network was constructed to present prominent categories related to the research of rehabilitation robots, which is characterized by a multidisciplinary specialty. A co-citation network with 169 clusters was constructed to present the intellectual structure in this field. As the most prominent label, soft robotic technology became a great concern over rehabilitative recovery on both upper and lower limbs. Also, task-oriented upper-limb training, control strategies for robot-assisted lower limb rehabilitation, power in exoskeleton robots are of great concerns in the current research on rehabilitation robots.

Conclusions:

Our work provides insights on the intellectual structure and emerging trend on the research of rehabilitation robots in the last two decades. This study was expected to present an effective bibliometric approach to perform interdisciplinary survey on medicine fields.


 Citation

Please cite as:

Zhang Y, Liu X, Qiao X, Fan Y

Characteristics and Emerging Trends in Research on Rehabilitation Robots from 2001 to 2020: Bibliometric Study

J Med Internet Res 2023;25:e42901

DOI: 10.2196/42901

PMID: 37256670

PMCID: 10267796

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