¹College of Information Science and Technology, Beijing Normal University, Engineering Research Center of Virtual Reality Application, Ministry of Education (MOE), P.R. C, Beijing, China.
²School of Computer and Control Engineering, Chinese Academy of Sciences, Beijing, China.
³School of Computer Science and Technology, Bejing University of Posts & Telecommunication, Bejing, China.
⁴School of Mathematics, Bejing Normal University, Bejing, China.

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Abstract—In Human, the lower limb joints attained more importance during the locomotor system, they play a valuable role during different styles of movement. The study of the 3D biomechanics of these joints have significance important for recording the morphological changes allied with the acquisition of a habitual bipedal gait in humans. Human body on any joint has important inference in joint stability and performance. In this paper, we measure the performance of human lower limb joints (hip, knee and ankle) during running based on statistical techniques. The data of joints acquisition from the motion captured system. This data provides plentiful information in human running. For instance, we can determine which joint has more variation in human running gait based on mocap of each joint. Our experimental results indicate that among these joints, the knee joint has a dominant influence in human running gait.

Index Terms—Joint movement, gait analysis, joints estimation, variation influence.

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Cite: Sajid Ali, Mingquan Zhou, Zhongke Wu, Usman Muhammad, M. Azam Zai, Murad Ali Shah, "Estimation of Joints Performance in Human Running through Mocap Data," Journal of Computers vol. 11, no. 4, pp. 289-299, 2016.