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Review
. 2023 Apr 26;13(5):724.
doi: 10.3390/brainsci13050724.

Sensor-Based Rehabilitation in Neurological Diseases: A Bibliometric Analysis of Research Trends

Salvatore Facciorusso  1   2 , Stefania Spina  2 , Rajiv Reebye  3 , Andrea Turolla  4 , Rocco Salvatore Calabrò  5 , Pietro Fiore  6 , Andrea Santamato  2
Affiliations
Review

Sensor-Based Rehabilitation in Neurological Diseases: A Bibliometric Analysis of Research Trends

Salvatore Facciorusso et al. Brain Sci. .

Abstract

Background: As the field of sensor-based rehabilitation continues to expand, it is important to gain a comprehensive understanding of its current research landscape. This study aimed to conduct a bibliometric analysis to identify the most influential authors, institutions, journals, and research areas in this field.

Methods: A search of the Web of Science Core Collection was performed using keywords related to sensor-based rehabilitation in neurological diseases. The search results were analyzed with CiteSpace software using bibliometric techniques, including co-authorship analysis, citation analysis, and keyword co-occurrence analysis.

Results: Between 2002 and 2022, 1103 papers were published on the topic, with slow growth from 2002 to 2017, followed by a rapid increase from 2018 to 2022. The United States was the most active country, while the Swiss Federal Institute of Technology had the highest number of publications among institutions. Sensors published the most papers. The top keywords included rehabilitation, stroke, and recovery. The clusters of keywords comprised machine learning, specific neurological conditions, and sensor-based rehabilitation technologies.

Conclusions: This study provides a comprehensive overview of the current state of sensor-based rehabilitation research in neurological diseases, highlighting the most influential authors, journals, and research themes. The findings can help researchers and practitioners to identify emerging trends and opportunities for collaboration and can inform the development of future research directions in this field.

Keywords: CiteSpace; bibliometric; neurorehabilitation; sensor-based.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Flowchart of study identification and selection.TS: topic search; (*): any group of characters, including no character.
Figure 2
Figure 2
Annual publication trend from 2002 to 2022.
Figure 3
Figure 3
Research hotspot distribution.
Figure 4
Figure 4
Country network visualization: co-occurrence analysis of countries.
Figure 5
Figure 5
The network cooperation map of institutions.
Figure 6
Figure 6
Collaboration network of authors.
Figure 7
Figure 7
Reference co-citation analysis [31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49]. (a) Cluster map; (b) bursts.
Figure 8
Figure 8
Keywords analysis. (a) Co-occurrence counts; (b) bursts.
See this image and copyright information in PMC

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