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

Abstract

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.

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

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.

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.

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.