Abstract：When a human is walking or running, the coordinated relationship between the movements of the thigh and shank are controlled by the motor nerve system. This relationship between the parts of the lower limb is the result of evolution and experience, which makes human movement more flexible and efficient. Research on the coordination of the lower limbs for healthy people facilitates rehabilitation of stroke patients, robot gait planning, and human-machine collaboration of assistive equipment such as exoskeletons. At present, the research on the coordination of human lower limb motion is still relatively basic, mostly focusing on observations and theoretical analyses, with few practical models. This study used a wearable motion capture system to measure and model the motion relationships of the lower limbs for human walking and running. A neural network model was then developed to characterize the coordination of the thigh and shank. This model accurately predicts the motion of the thigh and the knee joint from the shank movement information. This motion model can be used for rehabilitation, robot gait planning, intelligent assisting equipment and other related fields.
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