Abstract
This paper presents a Human-Machine Interface (HMI) for controlling lower limb exoskeleton robot intelligently with the joint torque estimated by a new biomechanical model of skeletal muscle. Based on the Microscopic working Mechanism of Molecular Motor (4M) in sacromere, this 4M model is established to reveal the relation between the characteristics of sEMG signal and active contraction force of muscle fiber. We discuss the interaction mechanism between human body and exoskeleton via analyzing the dynamics of exoskeleton robot and knee joint respectively. The knee joint torque that generated by skeletal muscle can be predicted accurately with the 4M model via measuring the sEMG signals on muscle surface. An active strategy for controlling exoskeleton robot has been proposed to train the lower limb on human intention. Experimental results show that the operator can exercise harmoniously with the exoskeleton, which prove the validity of this theoretical biomechanical model.
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References
Adam, B.Z., Kazerooni, H., Chu, A.: Biomechanical design of the Berkeley Lower Extremity Exoskeleton (BLEEX). IEEE/ASME Trans. Mechatron. 11, 128–138 (2006)
Kawamoto, H., Sankai, Y.: Power assist method based on phase sequence and muscle force condition for HAL. Adv. Robot. 19, 717–734 (2005)
Veneman, J., Kruidhof, R., Hekman, E., Ekkelenkamp, R., Van Asseldonk, E., van der Kooij, H.: Design and evaluation of the LOPES exoskeleton robot for interactive gait rehabilitation. IEEE Trans. Neural. Syst. Rehabil. Eng. 15, 379–386 (2007)
Banala, S., Kim, S., Agrawal, S., Scholz, J.: Robot assisted gait training with active leg exoskeleton (ALEX). IEEE Trans. Neural Syst. Rehabil. Eng. 17, 2–8 (2009)
Riener, R., Lunenburger, L., Jezernik, S., Anderschitz, M., Colombo, G.: Patient-Cooperative Strategies for Robot-Aided Treadmill Training: First Experimental Results. IEEE Trans. Neural. Syst. Rehabil. Eng. 13, 380–394 (2005)
Fleischer, C., Hommel, G.: A Human–Exoskeleton Interface Utilizing Electromyography. IEEE Trans. Robot. 24, 872–882 (2008)
Fan, Y.J., Guo, Z., Yin, Y.H.: sEMG-Based neuro-fuzzy controller for a parallel ankle exoskeleton with proprioception. Int. J. Robot. Autom. 26, 450–460 (2011)
Buchanan, T.S., Lloyd, D.G., Manal, K., et al.: Neuromusculoskeletal Modeling: Estimation of Muscle Forces and Joint Moments and Movements From Measurements of Neural Command. J. Appl. Biomech. 20, 367–395 (2004)
Lloyd, D., Besier, T.: An EMG-driven musculoskeletal model to estimate muscle forces and knee joint moments in vivo. J. Biomech. 36, 765–776 (2003)
Yin, Y.H., Guo, Z., Chen, X., Fan, Y.J.: Study on biomechanics of skeletal muscle based on working mechanism of myosin motors: An overview. Chin. Sci. Bull. (in press, 2012)
Rosen, J., Brand, M., Fuchs, M.B., Arcan, M.: A Myosignal-Based Powered Exoskeleton System. IEEE Trans. Syst., Man, Cybern. 31, 210–222 (2001)
Guo, Z., Yin, Y.H.: Coupling mechanism of multi-force interactions in the myosin molecular motor. Chin. Sci. Bull. 55, 3538–3544 (2010)
Yin, Y.H., Guo, Z.: Collective mechanism of molecular motors and a dynamic mechanical model for sarcomere. Sci. China-Technol. Sci. 54, 2130–2137 (2011)
Guo, Z., Yin, Y.H.: A dynamic model of skeletal muscle based on collective behavior of myosin motors—Biomechanics of skeletal muscle based on working mechanism of myosin motors (I). Sci. China-Technol. Sci. 55, 1589–1595 (2012)
Yin, Y.H., Chen, X.: Bioelectrochemical control mechanism with variable-frequency regulation for skeletal muscle contraction-Biomechanics of skeletal muscle based on the working mechanism of myosin motors (II). Sci. China-Technol. Sci. 55, 2115–2125 (2012)
Yin, Y.H., Fan, Y.J., Xu, L.D.: EMG & EPP-Integrated Human-machine Interface between the Paralyzed and Rehabilitation Exoskeleton. IEEE T. Inf. Technol. B. 3, 542–549 (2012)
Zhang, J.J., Yin, Y.H.: SMA-based bionic integration design of self-sensor–actuator-structure for artificial skeletal muscle. Sens. Actuators A: Phys. 181, 94–102 (2012)
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Guo, Z., Fan, Y., Zhang, J., Yu, H., Yin, Y. (2012). A New 4M Model-Based Human-Machine Interface for Lower Extremity Exoskeleton Robot. In: Su, CY., Rakheja, S., Liu, H. (eds) Intelligent Robotics and Applications. ICIRA 2012. Lecture Notes in Computer Science(), vol 7506. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33509-9_55
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DOI: https://doi.org/10.1007/978-3-642-33509-9_55
Publisher Name: Springer, Berlin, Heidelberg
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