Use of Computer Vision with Conventional Video Recordings of Gait in Older Adults: A Scoping Review

Background/Objectives: This scoping review evaluates the use of computer vision (CV) for analyzing conventional video recordings of gait in older adults. In the rapidly evolving world of CV, methods that use conventional video recordings offer a practical and affordable solution to quantifying gait impairments, especially in resource-limited areas. In this review, we evaluate the aims, methods, variables, and validation of the literature utilizing videos of gait in older adults. Methods: Inclusion criteria were limited to journal articles and conference papers published between 2020 and 2025. Three reviewers extracted data from selected articles. Results: The search identified 46 studies that demonstrate a wide variety of clinical conditions, methodological approaches, and analyzed variables. Three main aims emerged, with 15 screening studies for clinical conditions, 14 studies classifying severity or mobility levels, 16 characterization studies of healthy and pathological gait, and one person-identification study. Methodological approaches ranged across 35 studies utilizing commercially available cameras, six studies utilizing conventional video from specialized cameras, two using surveillance-style cameras, and four that did not specify. Methods of validation were inconsistent, comparing either to lab-based biomechanical gold standards or broad clinical labels, with limited interdisciplinary validation through both methods. Conclusions: This scoping review demonstrates methodological growth and diversification in CV-based gait analysis using conventional video in older adults. The available evidence primarily supports technical feasibility and preliminary screening or classification performance rather than established clinical validity. Standardized methods and external, longitudinal, and real-world validation are needed before these approaches can reliably support routine clinical decision-making.