Markerless Motion Capture Overestimates Knee Flexion During Walk and Run Tasks

Low-cost markerless motion capture systems, such as OpenCap, have shown recent promise for accurate kinematic analysis of human motion during several activities, including walking, squatting, and drop landing. Although this technology has shown promise within a controlled laboratory space, its ability to accurately quantify kinematics in less controlled environments, like a recreational run, is unknown. The focus of this study was to determine if markerless motion capture, OpenCap, could accurately quantify knee kinematics during both a walk and run trial with body-borne load and over an uneven surface. Thus, 18 participants had their knee kinematics quantified during a walk (1.5 m/s) and run (4.5 m/s) over a flat and uneven surface with (15 kg) and without (0 kg) body-borne load. Both marker-based and markerless time-series knee kinematic data were aligned to heel strike of the same step and clipped to a common time window (stance phase of dominant limb). Then, knee flexion angle at heel strike and peak of stance were calculated from marker-based and markerless data. Our results indicated markerless motion capture consistently overestimated knee flexion during both a walk and run task.