Types of anomalies in two-dimensional video-based gait analysis in uncontrolled environments

Abstract

Two-dimensional video-based pose estimation is a technique that can estimate human skeletal coordinates from video data alone. It is also being applied to gait analysis and, particularly, due to its simplicity of measurement, it has the potential to be applied to the gait analysis of large populations. In contrast, it is considered difficult to completely homogenize the environment and settings during the measurement of large populations. Therefore, it is necessary to appropriately deal with technical errors that are not related to the biological factors of interest. In this study, by analyzing a large cohort database, we have identified four major types of anomalies that occur during gait analysis using OpenPose in uncontrolled environments: anatomical, biomechanical, and physical anomalies and errors due to estimation. We have also developed a workflow for identifying and correcting those anomalies and confirmed that the workflow is reproducible through simulation experiments. Our results will help obtain a comprehensive understanding of the anomalies to be addressed in a pre-processing for 2D video-based gait analysis of large populations.