Predicting Healthy Human and Amputee Walking Gait using Ideas from Underactuated Robot Control

The ability to predict human gait, particularly impaired human gait, has the potential to improve rehabilitation/training outcomes and to reduce prosthesis/orthosis development costs. This work presents a walking model of moderate complexity that accurately captures both sagittal plane joint kinematics and whole body energetics for healthy human walking. The six-link, left-right symmetric model with hips, knees, ankles, and rigid circular feet accurately predicts normal human walking over a wide range of speeds using a torque-squared objective function. For unilateral transtibial amputee gait, one ankle joint is eliminated, yielding a fivelink, asymmetric model that is used to quantify the differences between amputee gaits optimized for symmetry and efficiency.