Validation of a newly developed low-cost, high-accuracy, camera-based gait analysis system

Background Gait analysis is essential for evaluating locomotor function and fall risk, particularly in the elderly and in various musculoskeletal disorders. Traditional gait analysis systems face challenges such as technical difficulties, high cost, and complexity of use. Therefore, there is a need for a more accessible and cost-effective system with a wider clinical applicability. Research question This study aimed to validate the newly developed IB-gait (R) system (InBody, Republic of Korea), a camera-based gait analysis tool, by comparing it against the VICON system. Methods A total of 28 community-dwelling adults without gait abnormalities (mean age 24.9 years) were enrolled in this study. The participants underwent gait analysis at their self-selected speed using VICON and IB-gait (R) simultaneously. Nine spatiotemporal gait parameters, including stride length (m), step length (m), stride duration (s), double-limb duration (s), stance phase (s), swing phase (s), cadence (velocity x 120/stride length), and gait velocity (m/s) were measured. The agreement between the two systems was tested using Bland-Altman plots and intraclass correlation coefficients (ICC). Results The IB-gait (R) showed a high degree of agreement with the VICON system in most gait parameters. The ICC showed excellent reliability for stride length (0.97), step length (0.92), gait velocity (0.97), cadence (0.97), and stride duration (0.79). However, it showed lower reliability in time-based parameters, including double-limb duration (0.12), stance phase (0.54), swing phase (0.241), and stance/swing phase ratio (0.11). Significance The IB-gait (R) system appears to be a feasible and cost-effective alternative to VICON system for gait analysis, particularly showing a high level of agreement in the distance-based parameters. Its practicality in clinical settings makes it a valuable tool for widespread use in gait analysis. However, further refinement of time-based parameter measurements and validation in diverse patient populations are needed to enhance its applicability.