Estimation of the ground reaction forces from a single video camera based on the spring-like center of mass dynamics of human walking.

In clinical studies, the ground reaction forces (GRFs) during walking have found being highly useful. Therefore, the force sensing shoes with small sensors and estimation methods based on kinematics from motion capture systems or inertial measurement units were proposed. Recent studies demonstrated methods of extracting GRFs from whole-body joint kinematics, which requires a significant computational load. In this study, we propose a vertical and anterior-posterior GRFs estimation method using a single camera based on the dynamic relationship between the center of mass (CoM) and the GRFs in terms of spring mechanics. The estimation method consisted of two steps: the extraction of the vertical CoM from the video clip and the conversion of the CoM information into GRFs using a walking model. From the image of the greater trochanter that is positioned near the pelvic joint, the vertical CoM was extracted. This was done after removing the artifacts by pelvic rotation and postural change of lower limbs. The parameters of a compliant bipedal walking model were tuned to best match the CoM trajectory coupled with GRFs by spring mechanics. A video camera was used to record the walking trials of five healthy young participants from the side. The walking trials was conducted at three different speeds on the instrumented treadmill; each lasted one minute long. The GRF prediction errors were approximately 9-11%, with the best matching trials found to be at a self-selected gait speed. The prediction of anterior-posterior GRF components showed a more consistent match than the vertical GRF. The results demonstrated the possibility of marker-less kinetics prediction from video images incorporating the mechanical characteristics of the CoM.