Human motion capturing techniques are used in various fields such as surveillance, healthcare, and sports to analyze, understand, and synthesize kinematic and kinetic data. Among the mentioned application areas of motion recognition techniques, sport is an essential sector in which it is extensively used. The dynamic and kinematic performance of the three joints of the lower limbs in lunge movement is the main factor affecting the lunge speed of the fencers. Fencing is an open-skill combat sport in which complicated body movements and effective game techniques are required. The extremely nonlinear human movements, muscle dynamics, and foot-ground contact make athletic gait analysis a difficult topic in biomechanics. At present, there are no comprehensive and systematic research results on the impact of the dynamic and kinematic performance of the ankle, knee, and hip joints of lower limbs on the lunge speed. Based on the gait tracking algorithm, this study compares and analyzes the dynamic and kinematic performance of lower limbs ankle, knee, and hip joints in the lunge of fencing athletes at different levels and discusses the influence of the dynamic and kinematic performance of the three lower limbs joints of fencing athletes on the lunge speed. This study mainly focuses on, (1) exploring the dynamic and kinematic influencing factors of the peak horizontal speed of the center of gravity of fencing athletes’ lunge movement, (2) to verify whether there is a difference in the lunge speed of fencing athletes at different levels and analyzes the reasons for the differences, (3) to explore the ankle, knee, and the differences of hip joint dynamics and kinematics, the causes of the differences, and to analyze the influence of the differences on the lunge speed. In this paper, we have used a gait tracking algorithm that evaluates the fencing athletes’ strength distribution characteristics. With the help of gait recognition algorithm based on artificial intelligence (AI) technology, the movement posture and gait of fencers can be recognized automatically in real time which is helpful to realize the automatic evaluation of power distribution. The experimental results prove the significance of the proposed model.
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