A robust technique for optimal fitting of roll-over shapes of human locomotor systems.

The roll-over shape (ROS) effectively characterizes the lower limb's ability to roll forward during the single-limb support phase of human walking. ROS is modelled as an optimally fitted circular arc to the center of pressure (CoP) data transformed in the shank/leg-based local coordinate system. The commonly used method for optimal fitting of ROS is complex to implement and eliminates inherent individual variability in the ROS parameters during walking. We propose and validate a novel computerized method for optimal fitting of roll-over shapes of the lower limb during walking. Gait data of a healthy individual from Winter's book was used to generate ankle-foot and knee-ankle-foot roll-over shapes using the proposed method. The goodness of fit and form of both the roll-over shapes were validated with the literature. To test the robustness of the proposed technique, small random perturbations were introduced to the transformed CoP data and the effect of these small changes in the data on the ROS parameters was studied. The ROS parameters such as radius, arc length, subtended arc angle, and horizontal and vertical shift in the arc center did not change substantially with small changes in the CoP data. The proposed method is computationally efficient, and easy to implement for optimal fitting and characterization of ROS.