Data-driven human movement assessment

Abstract

Quality assessment of human movements has many applications in diagnosis and therapy of musculoskeletal insufficiencies and high-performance sport. We suggest five purely data-driven assessment methods for arbitrary human movements using inexpensive 3D sensor technology. We evaluate their accuracy by comparing them against a validated digitalization of a standardized human-expert-based assessment method for deep squats. We suggest the data-driven method that shows high agreement with this baseline method, requires little expertise in the human movement, and no expertise in the assessment method itself. It allows for an effective and efficient, automatic and quantitative assessment of arbitrary human movements.