A Bibliometric Literature Review on International Trends in Robotic Technology Research in the Field of Dementia

Abstract

Purpose Dementia is one of the seven leading causes of death and a primary factor for requiring long-term care. The number of dementia patients worldwide exceeds 55 million, with approximately 10 million new cases occurring annually. In this context, the utilization of robots is advancing to address the increasing number of dementia patients. This study focuses on the application of robotic technology in dementia care and aims to identify the most influential authors, educational and research institutions, countries, regions, and references internationally through a quantitative literature review. Literature review is a crucial method for analyzing trends in academic development. Investigating published academic literature reveals the current state and trends of a particular field, providing significant insight for future research directions. Bibliometrics, a method for quantitatively analyzing literature, is essential for objectively understanding research trends.

Method This study uses network visualization analysis based on science knowledge mapping in bibliometrics to elucidate international trends in research related to application in the field of dementia. To ensure representative literature, the Web of Science Core Collection (WoSCC) provided by Clarivate Analytics was used. WoSCC. The literature for analysis was selected based on the following inclusion and exclusion criteria. Inclusion criteria: (1) papers related to robotic technology in dementia, (2) peer-reviewed papers published as of May 31, 2024, (3) papers obtained from WoSCC. Exclusion criteria: (1) unpublished papers, (2) conference proceedings and summaries, book chapters, prefaces, (3) duplicate papers, (4) literature unrelated to robotic technology in dementia. The search resulted in 290 papers, with 195 original research papers meeting the criteria for analysis. The search was conducted on May 31, 2024, and the period for the target papers was from 2011, when the first paper was published in WoSCC, to 2024. About ethical considerations, this study performed statistical analysis using bibliographic information from prior literature published as of May 31, 2024. Therefore, ethical review for human subjects was deemed unnecessary.

Results and Discussion The most frequently occurring author in the overall network was Stephen Scott (frequency: 4, centrality: 0.01). Cluster analysis revealed a single cluster primarily related to Transcatheter Aortic Valve Implantation (TAVI). Among educational and research institutions, the highest frequency of four was found in Hospital Universitaire Broca et al. Clustering identified a single cluster mainly related to Socially Assistive Robots. In the analysis of countries and regions, Japan had the highest frequency at eight, while England had the highest centrality at 0.17. Clustering revealed two main clusters: “robotics” and “Socially Assistive Robots.” Keyword analysis showed that “dementia” had the highest frequency at 18. Centrality was highest for “cognitive impairment” at 0.44. The largest clusters identified were related to “assistive robotics” (size: 26) and “socially assistive robots” (size: 26). In the study focused on authors, it was found that TAVI research plays a central role, indicating that research is primarily advancing in the application of robotic technology in cerebrovascular dementia, such as in stroke patients. Additionally, the references indicate that studies on robotic technology for social support are being frequently cited. This suggests that the application of robotic technology is gaining attention in both neuroscientific research on stroke patients and in social support for elderly care.