Global Insights: A Bibliometric Analysis of Artificial Intelligence Applications in Rehabilitation Worldwide

Abstract

Abstract Background: Rehabilitation plays a vital role in helping patients recover functionality after illness or injury. However, challenges remain in providing customized, accessible rehabilitation services. Artificial intelligence (AI) techniques like machine learning are emerging as promising tools to enhance rehabilitation. This study aimed to conduct a bibliometric analysis to synthesize global growth trends, research foci, and collaborative patterns in AI rehabilitation research. Methods: A systematic literature search was performed in Scopus and Web of Science databases to retrieve peer-reviewed publications on AI in rehabilitation from 2000-2022. Articles were analyzed using ScientoPy, VOSViewer and Biblioshiny to extract publication volume, citations, authorship, journals, conceptual themes, and country networks. Results: The search yielded 315 articles with exponential growth since 2016. Machine learning and deep learning were dominant techniques applied in rehabilitation contexts like stroke. China led research productivity, but contributions came globally including the US, Italy, India and others. Core journals were IEEE Access and IEEE Transactions in neural engineering and informatics. Citation trends highlighted pioneering AI system studies as most impactful. Conclusions: This bibliometric analysis provides the first detailed mapping of global AI rehabilitation research, revealing rapid advances primarily in algorithm development rather than clinical translation. Findings can guide future growth through: (1) increasing focus on real-world implementation, (2) expanding applications to more health conditions and populations, (3) fostering cross-country and cross-sector collaboration, and (4) promoting commercialization. Sustained international effort is key to realizing AI's potential in enhancing rehabilitation outcomes. This study offers an evidence base to track evolution and set priorities in this emerging interdisciplinary domain.

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