Mapping global research on artificial intelligence in physical therapy: a bibliometric analysis from 1990 to 2023

The application of artificial intelligence (AI) in physical therapy has garnered increasing interest in recent years. We aimed to explore the current state of research on AI applications in physical therapy using bibliometric methods. A comprehensive literature search was conducted in Scopus (1990–2023). Two independent reviewers assessed titles, abstracts, and full documents. Inclusion criteria consisted of documents addressing AI applicability in physical therapy. Bibliometric analysis was conducted using VOSviewer and the R package Bibliometrix. A total of 805 studies were retrieved. After applying exclusion criteria and screening, 460 documents published across 317 journals were included, showing an annual growth rate of 16.7%. The average document age was 5.1 years. Contributions came from 1974 authors, with the University of Toronto being the most prolific institution. Research originated from 65 countries, led by the USA, followed by China, India, Germany, and Canada. Key themes included ‘machine learning’, ‘rehabilitation’, ‘physiotherapy’, ‘artificial intelligence’, ‘physical therapy’, and ‘deep learning’. The number of publications on AI in physical therapy has grown significantly. Despite this, there is a notable gap in international collaboration, with research primarily centred in high- and upper-middle-income countries. Findings provide valuable insights into underexplored topics representing potential areas.

近年来，人工智能（AI）在物理治疗领域的应用日益受到关注。本研究旨在通过文献计量学方法探究AI在物理治疗中应用的研究现状。我们在Scopus数据库（1990–2023年）中开展了全面的文献检索，由两名独立评审员对文献标题、摘要及全文进行评估。纳入标准为探讨AI在物理治疗中适用性的文献，使用VOSviewer工具及R语言包Bibliometrix进行文献计量分析。共检索到805项研究，经排除标准筛选后，最终纳入发表于317种期刊的460篇文献，其年增长率达16.7%。文献平均年限为5.1年，共有1974位作者参与研究，其中多伦多大学是产出最高的机构。研究来自65个国家，以美国为首，其次为中国、印度、德国及加拿大。核心主题包括机器学习（machine learning）、康复（rehabilitation）、物理治疗（physiotherapy）、人工智能（artificial intelligence）、物理治疗（physical therapy）及深度学习（deep learning）。AI在物理治疗领域的文献数量显著增长，尽管如此，国际合作仍存在明显差距，研究主要集中于高收入及中高收入国家。研究结果为尚未充分探索的潜在领域主题提供了有价值的见解。