Key Takeaways & Executive Findings
- •• The United States leads in publication volume and centrality in upper-limb rehabilitation robotics research. • Northeast University and Univ Shanghai Sci&Technol are the most prolific institutions in this field. • Research in upper-limb rehabilitation robotics shows an overall upward trend but with limited collaboration among researchers and institutions. • Key research directions include core technical methods, robot design, control strategies, clinical applications, and emerging technologies.
Abstract
BACKGROUND: Upper limb rehabilitation robots have emerged as an indispensable component in global healthcare systems. Despite the extensive body of research in this field, which primarily focuses on areas such as development and application, there remains a significant need for comprehensive, systematic literature analysis to thoroughly examine the current research landscape, identify emerging hotspots, and predict future trends in this domain. OBJECTIVE: To conduct a visual analysis of research status, hotspots, and trends in the field of upper limb rehabilitation robots over the past decade using CiteSpace software, with the aim of identifying key research directions and providing intuitive references for researchers. METHODS: This study systematically retrieved literature related to upper-limb rehabilitation robotics from CNKI and the Web of Science Core Collection published between January 1, 2015, and March 13, 2025. CiteSpace 6.1.R1 software was employed for visualized analysis of included literature, covering key dimensions such as publication volume, authors, institutions, keywords, clusters, and bursts. RESULTS AND CONCLUSION: (1) A total of 1 054 articles were included, involving 659 authors. The United States held the highest overall ranking in terms of both research publication volume and centrality in this field. Among the contributing institutions, Northeast University and Univ Shanghai Sci&Technol ranked the highest in publication volume. Visualization analysis indicated an overall upward trend in upper limb rehabilitation robotics research, yet revealed limited collaboration among researchers and institutions. Main research directions included core technical methods, robot design and optimization, control strategies and algorithms, clinical application and evaluation, and emerging technologies and interdisciplinary integration. (2) Future research could focus on technological integration and intelligent upgrading, interdisciplinary collaborative innovation, and improvement of clinical applications to promote the continuous development and refinement of the upper limb rehabilitation robot field.
1. Introduction
Upper limb dysfunction is a common sequela of diseases such as stroke, spinal cord injury, traumatic brain injury, neurodegenerative diseases, and musculoskeletal injuries, manifesting as decreased muscle strength, loss of motor coordination, restricted joint range of motion, sensory abnormalities, or even complete paralysis, severely impairing patients' daily living abilities and social participation [1-7]. The continuous expansion of the upper limb dysfunction patient population has correspondingly increased the demand for rehabilitation therapists [8-10]. However, therapists performing prolonged, repetitive movements are prone to physical fatigue, which not only reduces the standardization and consistency of therapeutic actions but may also weaken treatment efficacy [11]. More critically, manual operation modes are difficult to quantify training volume, thereby prolonging the rehabilitation cycle [12]. To assist, enhance, and quantify neurological rehabilitation therapy, upper limb rehabilitation robots have emerged [13-15].
With continuous technological advancement, medical devices have been optimized and upgraded, and the role of upper limb rehabilitation robots in daily rehabilitation training has become increasingly prominent: they not only provide high-frequency, high-intensity training to promote neural remodeling [16], help patients rebuild motor function and enhance their motor abilities [17-18], but also precisely strengthen upper limb muscle strength and execute diverse functional training [19-21]. Importantly, upper limb rehabilitation robot technology significantly reduces the workload of therapists, liberating human resources through automation, saving resources, and greatly alleviating the pressure on rehabilitation medical services [22-26].
In recent years, publications related to upper limb rehabilitation robots have increased substantially [27]. Despite the flourishing academic research in this field, systematic reviews specifically focusing on upper limb rehabilitation robots are scarce. Bibliometric analysis has been widely used by researchers to evaluate academic research in specific fields, exploring knowledge structures and development trends [28-31]. CiteSpace, as a commonly used bibliometric software, provides researchers with effective and convenient methods to objectively and comprehensively analyze the structure of specific research fields and supports visual exploration of knowledge discovery through bibliographic databases [27,32-33]. This study aims to establish an in-depth picture of the research status and development process of upper limb rehabilitation robots over the past decade using CiteSpace 6.1.R1 software, draw knowledge maps, and thereby predict future trends in upper limb rehabilitation robots.
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Wang Feifei, Wang Zhennan (2026). Scientometric deconstruction of developmental dynamics in upper-limb rehabilitation robotics: evidence network analysis via CiteSpace. Chinese Journal of Tissue Engineering Research. https://doi.org/10.12307/2026.21309
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Frequently Asked Questions
What is the main objective of this study?
The main objective is to conduct a visual analysis of research status, hotspots, and trends in the field of upper limb rehabilitation robots over the past decade using CiteSpace software, aiming to identify key research directions and provide intuitive references for researchers.
Which databases were searched in this study?
The study systematically retrieved literature from CNKI (China National Knowledge Infrastructure) and the Web of Science Core Collection.
How many articles were included in the analysis?
A total of 1,054 articles were included in the analysis, comprising 717 Chinese and 337 English articles.
What are the main research directions identified in the field?
The main research directions include core technical methods, robot design and optimization, control strategies and algorithms, clinical application and evaluation, and emerging technologies and interdisciplinary integration.
What are the future research directions suggested by the study?
Future research could focus on technological integration and intelligent upgrading, interdisciplinary collaborative innovation, and improvement of clinical applications to promote the continuous development and refinement of the upper limb rehabilitation robot field.
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