The purpose of this study is to identify the characteristics of the disease, diagnose the disease by computer and evaluate the rehabilitation based on gait touch information after ACL rupture and reconstruction, combined with the methods of multi-body dynamics, machine learning and biomechanics analysis. Methods: 55 healthy volunteers, 55 patients with ACL rupture were recruited. Three dimensional gait analysis and dynamic plantar pressure were used to test the kinematic and dynamic data of lower limbs and gait touch information when walking, jogging, stopping and jumping, and running side cutting.~Outcome evaluation indexes and statistical methods:~the following indexes were measured repeatedly by two factor ANOVA method, and the left and right sides and different rehabilitation time were used as the variables of repeated measurement: the biomechanics of the lower limb joint and the change of the biological characteristics of gait touch information were analyzed. To study the biomechanical status of different knee joints and the mechanism of the change of gait touch information. Finally, based on the information of gait touch, a biomechanical evaluation model of knee joint during walking or jogging is established, which provides the exact basis for quantifying and evaluating the biomechanical state of knee joint under the dynamic load-bearing state of gait touch information.
High incidence rate of knee osteoarthritis and gait analysis are important for early assessment of biomechanics. ACL injury is an ideal clinical model for studying knee osteoarthritis.~To clarify the mechanism between the biomechanical status of knee joint and the change of gait touch information, and to provide scientific basis for quantifying and evaluating the biomechanical status of knee joint in dynamic load-bearing state.