A comprehensive survey on gait analysis: History, parameters, approaches, pose estimation, and future work

Human gait is a periodic motion of body segments—the analysis of motion and related studies is termed gait analysis. Gait Analysis has gained much popularity because of its applications in clinical diagnosis, rehabilitation methods, gait biometrics, robotics, sports, and biomechanics. Traditionally, subjective assessment of the gait was conducted by health experts; however, with the advancement in technology, gait analysis can now be performed objectively and empirically for better and more reliable assessment. State-of-the-art semi-subjective and objective techniques for gait analysis have limitations that can be mitigated using advanced machine learning-based approaches. This paper aims to provide a narrative and a comprehensive analysis of cutting-edge gait analysis techniques and insight into clinical gait analysis. The literature of the previous surveys during the last decade is discussed. This paper presents an elaborated schema, including gait analysis history, parameters, machine learning approaches for marker-based and marker-less analysis, applications, and performance measures. This paper also explores the pose estimation techniques for clinical gait analysis that open future research directions in this area. •Review on gait analysis including history, parameters, applications, performance measures, traditional and latest approaches•Comparative analysis of previous reviews•Discussion on Marker-Based and Marker-less approaches for gait analysis•Discussion on clinical gait analysis using latest technologies, specifically Pose Estimation•Future directions and open issues discussion in various application areas of gait analysis