Validity of an artificial intelligence, human pose estimation model for measuring single-leg squat kinematics

Abstract

Few studies have investigated the validity of 2D pose estimation models to evaluate kinematics throughout a motion and none have included adolescents. Adolescent athletes completed single-leg squats while 3D kinematic data and 2D sagittal and frontal plane videos were recorded. Sagittal and frontal plane joint motion throughout the single-leg squats and angles at peak knee flexion were compared among 2D pose estimation, 3D motion analysis, and traditional 2D motion analysis techniques. Statistical parametric mapping compared waveforms while Pearson’s correlation compared the relationships of joint angles at peak knee flexion among techniques, respectively. We observed significant waveform differences between 2D pose estimation and 3D motion analysis at the beginning and end of the squat for sagittal plane hip and knee motion, for most of the squat for frontal plane hip motion, and throughout the entire squat for sagittal plane ankle motion and frontal plane pelvic motion. We observed moderate-to-strong relationships (r = 0.68-0.94) for sagittal plane joint angles between 2D pose estimation and 3D techniques. We observed fair correlations (r = 0.53-0.54) for frontal plane pelvic and hip joint angles between 2D pose estimation and 3D motion analysis. We observed poor relationships for the frontal plane knee angle between 3D motion analysis with 2D pose estimation (r = 0.20) and traditional 2D motion analysis (r = 0.05), respectively, but observed a strong relationship (r = 0.95) between the 2D techniques. 2D pose estimation is a valid alternative to 3D motion analysis and traditional 2D motion analysis for evaluating most sagittal and frontal plane angles during a single-leg squatting task.