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Volume 23, Issue 3 (7-2026)
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Sheikhhoseini R. Artificial Intelligence and Body Alignment: A Bibliometric Analysis Mapping the Boundaries from 2015 to 2025. Mod Care J 2026; 23 (3) :56-68
URL: http://mcj.bums.ac.ir/article-1-625-en.html
URL: http://mcj.bums.ac.ir/article-1-625-en.html
Associated professor, PhD, Department of Corrective Exercise & Sports Injury, Allameh Tabataba'i University, Tehran, Iran , rahman.pt82@gmail.com
Abstract: (169 Views)
Introduction: The assessment of human body alignment (the position of body segments relative to each other) and body posture has long been a cornerstone of health sciences. Among these traditional approaches, the use of artificial intelligence (AI) is being touted as a powerful tool in various assessments of clients and the delivery of healthcare.
Objectives: This study aimed to examine and analyze the bibliometrics of AI and body alignment.
Methods: Bibliometric data were retrieved up to August 2025 from the Scopus database using the keywords "Artificial Intelligence" and "Body Alignment." After screening for relevance, including publication type and completeness of bibliographic information, 586 studies were included. The selected records were imported into the RStudio software. The installed Bibliometrix R package (version 4.0.0) for Windows 10 (64-bit) was used to draft an appropriate network analysis, visual display, and structural information.
Results: A total of 586 studies were analyzed in this bibliometric study. These studies were published in 333 independent sources from 2015 to 2025 and were written by 3710 authors. The annual publication rate of articles was 49.74%, and their average document age was 1.87 years. The top ten relevant journals, most relevant authors, most relevant affiliations, countries' scientific production, keyword analysis, and trend topics were extracted and reported for this study.
Conclusion: Research on AI applications in body alignment has grown steadily over the past decade, revealing emerging topics and potential clinical applications. Continued interdisciplinary collaboration and real-world evaluations are required to advance this field responsibly.
Objectives: This study aimed to examine and analyze the bibliometrics of AI and body alignment.
Methods: Bibliometric data were retrieved up to August 2025 from the Scopus database using the keywords "Artificial Intelligence" and "Body Alignment." After screening for relevance, including publication type and completeness of bibliographic information, 586 studies were included. The selected records were imported into the RStudio software. The installed Bibliometrix R package (version 4.0.0) for Windows 10 (64-bit) was used to draft an appropriate network analysis, visual display, and structural information.
Results: A total of 586 studies were analyzed in this bibliometric study. These studies were published in 333 independent sources from 2015 to 2025 and were written by 3710 authors. The annual publication rate of articles was 49.74%, and their average document age was 1.87 years. The top ten relevant journals, most relevant authors, most relevant affiliations, countries' scientific production, keyword analysis, and trend topics were extracted and reported for this study.
Conclusion: Research on AI applications in body alignment has grown steadily over the past decade, revealing emerging topics and potential clinical applications. Continued interdisciplinary collaboration and real-world evaluations are required to advance this field responsibly.
Article Types: Review Article |
Subject:
Critical Care
Received: 2025/11/23 | Accepted: 2026/06/20 | Published: 2026/08/1
Received: 2025/11/23 | Accepted: 2026/06/20 | Published: 2026/08/1
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