Evaluation of the Ability of Machine Learning-Models to Assess Postural Orientation Errors During a Single-Leg Squat
OBJECTIVES: To reach agreement among experts on visual assessments of postural orientation errors (POEs) during the single-leg squat (SLS), and to use expert agreement assessments as ground truth for machine learning (ML) models to evaluate their ability to classify POEs.DESIGN: Methodological study with mixed-methods design.METHODS: POEs of the lower extremity and trunk were assessed from videos
