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Static Ankle Joint Stiffness Estimation with Relaxed Muscles Through Customized Device

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10462))

Abstract

Human Ankle joints play significant role in physical activity. Studying on biomechanical characteristic of ankle joint helps to know the movement of human body. This paper reports a procedure to measure static ankle mechanical impedance with relaxed muscles. An experimental protocol using a self-made mechanical device makes it reliable to obtain torque and angle data. The machinery mainly consists of a multifunction controller, an encoder, key components to get torque and angle data, a supporting framework and a drive motor. A surface electromyographic (sEMG) system is used to determine whether ankle joint is static or not. In order to overcome the inertia and friction of the device, a calibration method based on error correcting was applied. Experiment with nine subjects keeping muscles of ankle as relaxed as possible shows that the static torque-angle relation presents a quasi-linear property and estimated the elastic parameter of ankle impedance form it. The static characterization of human ankle joint is important to understand human moving function during interaction with the environment and helps study more complex features of dynamic ankle mechanical impedance.

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Acknowledgments

This work was partly supported by National Natural Science Foundation of China (61603284 & 51575412).

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Correspondence to Cheng Sun .

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© 2017 Springer International Publishing AG

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Xiong, R., Sun, C., Pang, M., Xiang, K., Ju, Z. (2017). Static Ankle Joint Stiffness Estimation with Relaxed Muscles Through Customized Device. In: Huang, Y., Wu, H., Liu, H., Yin, Z. (eds) Intelligent Robotics and Applications. ICIRA 2017. Lecture Notes in Computer Science(), vol 10462. Springer, Cham. https://doi.org/10.1007/978-3-319-65289-4_46

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  • DOI: https://doi.org/10.1007/978-3-319-65289-4_46

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-65288-7

  • Online ISBN: 978-3-319-65289-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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