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EMG-Based Control for Three-Dimensional Upper Limb Movement Assistance Using a Cable-Based Upper Limb Rehabilitation Robot

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Intelligent Robotics and Applications (ICIRA 2017)

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

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Abstract

Voluntary residual motor efforts to the affected limb of patients after stroke have not been involved enough in most rehabilitation robot control strategies. In this paper, a natural integration between human and machine is proposed by using the surface electromyography (EMG) signals from six muscles which mainly contribute to the upper limb movement. A linear state space model is trained, which can estimate the real-time movement intention by using EMG signals, to calculate the movement needed forces and then provided by a cable-based upper limb rehabilitation robot. Ten healthy subjects are recruited to complete the tasks with and without robot assistances. The performances of the subjects with the assistances are compared to that of the subjects without assistances. Results show that the forces from the model were real-time continuously estimated and accurate. Furthermore, there is no significant difference in the group mean root mean square error (RMSE) and muscle activations between the task without assistance and with assistance. These results show that the robot using the state space model could provide physiologically appreciate assistance to the subject, and the robot could conduct the rehabilitation training combined with the voluntary residual motor efforts. Clinical test will be carried out to validate the feasibility of the robot-aided rehabilitation using myoelectrical control.

Y. Huang and Y. Chen—Contributed equally to this work.

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References

  1. Riener, R., Nef, T., Colombo, G.: Robot-aided neurorehabilitation of the upper extremities. Med. Biol. Eng. Comput. 43(1), 2–10 (2005)

    Article  Google Scholar 

  2. Krebs, H., Volpe, B., Aisen, M., Hogan, N.: Increasing productivity and quality of care: robot-aided neuro-rehabilitation. J. Rehabil. Res. Dev. 37(6), 639–652 (2000)

    Google Scholar 

  3. Ferris, D., Sawicki, G., Domingo, A.: Powered lower limb orthoses for gait rehabilitation. Top. Spinal Cord Inj. Rehabil. 11(2), 34–49 (2005)

    Article  Google Scholar 

  4. Kong, K.: Proxy-based impedance control of a cable-driven assistive system. Mechatronics 23(1), 147–153 (2013)

    Article  Google Scholar 

  5. Dipietro, L., Ferraro, M., Palazzolo, J., Krebs, H., Volpe, B., Hogan, N.: Customized interactive robotic treatment for stroke: EMG-triggered therapy. IEEE Trans. Neural Syst. Rehabil. Eng. 13(3), 325–334 (2005)

    Article  Google Scholar 

  6. Song, R., Tong, K.-Y., Hu, X., Li, L.: Assistive control system using continuous myoelectric signal in robot-aided arm training for patients after stroke. IEEE Trans. Neural Syst. Rehabil. Eng. 16(4), 371–379 (2008)

    Article  Google Scholar 

  7. Potvin, J.R.: Mechanically corrected EMG for the continuous estimation of erector spinae muscle loading during repetitive lifting. Eur. J. Appl. Physiol. Occup. Physiol. 74(1–2), 119–132 (1996)

    Article  Google Scholar 

  8. Lloyd, D.G., Besier, T.F.: An EMG-driven musculoskeletal model to estimate muscle forces and knee joint moments in vivo. J. Biomech. 36(6), 765–776 (2003)

    Article  Google Scholar 

  9. Manal, K., Buchanan, T.S.: A one-parameter neural activation to muscle activation model: estimating isometric joint moments from electromyograms. J. Biomech. 36(8), 1197–1202 (2003)

    Article  Google Scholar 

  10. Artemiadis, P.K., Kyriakopoulos, K.J.: EMG-based control of a robot arm using low-dimensional embedding’s. IEEE Trans. Robot. 26(2), 393–398 (2010)

    Article  Google Scholar 

  11. Kwon, S., Kim, Y., Kim, J.: Movement stability analysis of surface electromyography-based elbow power assistance. IEEE Trans. Biomed. Eng. 61(4), 1134–1142 (2014)

    Article  Google Scholar 

  12. Suzuki, K., Mito, G., Kawamoto, H., Hasegawa, Y., Sankai, Y.: Intention-based walking support for paraplegia patients with Robot Suit HAL. Adv. Robot. 21(12), 1441–1469 (2007)

    Google Scholar 

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Acknowledgments

The project was supported by the National Natural Science foundation of China (Grant No. 61273359 and 91520201), the Guangdong Science and Technology Planning Project (Grant No. 2014B090901056 and 2015B020214003) and the Guangzhou Research Collaborative Innovation Projects (Grant No. 201604020108).

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Authors and Affiliations

  1. Key Laboratory of Sensing Technology and Biomedical Instrument of Guang Dong Province, School of Engineering, Sun Yat-sen University, Guangzhou, People’s Republic of China

    Yao Huang, Ying Chen, Jie Niu & Rong Song

  2. Guangdong Provincial Engineering and Technology Center of Advanced and Portable Medical Devices, School of Engineering, Sun Yat-sen University, Guangzhou, People’s Republic of China

    Yao Huang, Ying Chen, Jie Niu & Rong Song

Authors
  1. Yao Huang
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  2. Ying Chen
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  3. Jie Niu
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  4. Rong Song
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Corresponding author

Correspondence to Rong Song .

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Editors and Affiliations

  1. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China

    YongAn Huang

  2. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China

    Hao Wu

  3. Institute of Industrial Research, University of Portsmouth, Portsmouth, United Kingdom

    Honghai Liu

  4. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China

    Zhouping Yin

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Huang, Y., Chen, Y., Niu, J., Song, R. (2017). EMG-Based Control for Three-Dimensional Upper Limb Movement Assistance Using a Cable-Based Upper Limb Rehabilitation Robot. 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_26

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  • DOI: https://doi.org/10.1007/978-3-319-65289-4_26

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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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