Artificial Intelligence in Gait and Movement ...

Artificial Intelligence in Gait and Movement Analysis for Physiotherapy and Rehabilitation: A Bibliometric Study Protocol

Author Name : Dr. Smriti Madaik, Dr Kirti Anand, Dr Paras Negi

ABSTRACT Background: Quantitative movement assessment supports clinical decision-making, rehabilitation planning, and longitudinal monitoring. Artificial intelligence (AI), including machine learning, deep learning, and computer vision, is increasingly being combined with wearable sensors and video-based systems to estimate gait and movement features. However, the distribution, collaboration patterns, and thematic development of research with explicit relevance to physiotherapy and rehabilitation require focused mapping. Objective: To map the scientific development, publication performance, international collaboration, intellectual structure, and emerging themes of AI-assisted gait and movement analysis relevant to physiotherapy and rehabilitation. Methods: This protocol describes a Scopus-based bibliometric and science-mapping study from database inception to the date of the final search. The reproducible search will combine terms for AI/computational methods, gait/movement analysis, and physiotherapy/rehabilitation. Eligible peer-reviewed articles and review articles will be screened against prespecified criteria. Metadata will be exported, deduplicated, standardized, and analysed using bibliometrix/Biblioshiny in R and VOSviewer. Planned analyses include annual scientific production, source and author productivity, citation indicators, country and institutional collaboration, keyword co-occurrence, bibliographic coupling/co-citation where data permit, and thematic mapping.