Skip to main content
Springer Nature Link
Log in

A Hybrid FES Rehabilitation System Based on CPG and BCI Technology for Locomotion: A Preliminary Study

  • Conference paper
Intelligent Robotics and Applications (ICIRA 2009)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5928))

Included in the following conference series:

  • 3754 Accesses

Abstract

A hybrid functional electrical stimulation (FES) rehabilitation system for locomotion is proposed in this paper. It has a hierarchical structure. In upper level, brain-computer technology (BCI) is used to acquire the subject’s intention. In middle level, central pattern generator (CPG) is designed to generate appropriate rhythmic motor patterns. CPG is triggered by BCI command, and send control patterns to lower level. In lower level, FES technique is used to activate the muscles, and drive the lower limbs to achieve the expected movements (i.e. locomotion). The whole system is developed according to the general nervous structure of human being. The hybrid system aims at developing a neuroprosthetic bridge for the impaired nervous system of paralyzed patients. Some preliminary results on BCI are given.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Bentley, A.S.J., Andrew, C.M., John, L.R.: An offline auditory P300 brain-computer interface using principal and independent component analysis techniques for functional electrical stimulation application. In: Proceeding of 30th EMBC, pp. 4660–4663 (2008)

    Google Scholar 

  2. Birbaumer, N.: Breaking the silence: Brain-computer interfaces (BCI) for communication and motor control. Psychophysiology 43, 517–531 (2006)

    Article  Google Scholar 

  3. Boord, P., Barriskill, A., Craig, A., Nguyen, H.: Brain-computer interface-FES integration: Towards a hands-free neuroprosthesis command system. Neuromodulation 7(4), 267–276 (2004)

    Article  Google Scholar 

  4. Grillner, S.: Neurobiological bases of rhythmic motor acts in vertebrates. Science 228, 143–149 (1985)

    Article  Google Scholar 

  5. Ijspeert, A.J.: Central pattern generators for locomotion control in animals and robots: a review. Neural Networks 21, 642–653 (2008)

    Article  Google Scholar 

  6. Izhikevich, E.M.: Which model to use for cortical spiking neurons? IEEE Trans. Neural Networks 15, 1063–1070 (2004)

    Article  Google Scholar 

  7. Lotte, F., Congedo, M., Lecuyer, A., Lamarche, F., Arnaldi, B.: A review of classification algorithms for EEG-based brain-computer interfaces. J. Neural Engineering 4, R1–R13 (2003)

    Article  Google Scholar 

  8. Meng, F., Tong, K.Y., Chan, S.T., Wong, W.W., Liu, K.H., Tang, K.W., Gao, X.R., Gao, S.K.: BCI-FES training system design and implementation for rehabilitation of stroke patients. In: Proceed. IEEE IJCNN conference, pp. 4103–4106 (2008)

    Google Scholar 

  9. Nicolelis, M.A., Chapin, J.K.: Controlling robots with the mind. Scientific American 287(4), 46 (2002)

    Article  Google Scholar 

  10. Peckham, P.H., Knutson, J.S.: Functional electrical stimulation for neuromuscular applications. Annu. Rev. Biomed. Eng. 7, 327–360 (2005)

    Article  Google Scholar 

  11. Pfurtscheller, G., Mueller, G.R., Pfurtscheller, J., Gerner, H.J., Rupp, R.: Thought’ - control of functional electrical stimulation to restore hand grasp in a patient with tetraplegia. Neuroscience Letter 351, 33–36 (2003)

    Article  Google Scholar 

  12. Pfurtscheller, G., Mueller-Putz, G.R., Pfurtscheller, J., Rupp, R.: EEG-based asynchronous BCI controls functional electrical stimulation in a tetraplegic patient. EURASIP Journal on Applied Signal Processing 19, 3152–3155 (2005)

    Google Scholar 

  13. Tan, H.G., Zhang, H.H., Wang, C.C., Zhang, D.G., Shee, C.Y., Ang, W.T., Guan, C.T.: A step towards discretized motion control of the upper limb using brain-computer interface and electrical stimulation. In: Proc. 13th IFESS conference (2008)

    Google Scholar 

  14. Velliste, M., Perel, S., Spalding, M.C., Whitford, A.S., Schwartz, A.B.: Cortical control of a prosthetic arm for self-feeding. Nature (2008) doi:10.1038/nature06996

    Google Scholar 

  15. Wolpaw, J.R., Birbaumer, N., McFarland, D.J., Pfurtscheller, G., Vaughan, T.M.: Brain-computer interfaces for communication and control. Clinical Neurophysiology 113, 767–791 (2002)

    Article  Google Scholar 

  16. Zhang, D.G., Zhu, K.Y.: Computer simulation study on central pattern generator: From biology to engineering. Intern. J. Neural Systems 16, 405–422 (2006)

    Article  Google Scholar 

  17. Zhang, D.G., Zhu, K.Y.: Theoretical analysis on neural oscillator toward bio-mimic robot control. Intern. J. Humanoid Robotics 4, 697–715 (2007)

    Article  Google Scholar 

  18. Zhang, D.G., Tan, H.G., Ferdinan, W., Ang, W.T.: Functional electrical stimulation in rehabilitation engineering: A survey. In: Proceed. Intern. Conf. Rehab. Eng. & Assist. Tech., Singapore, pp. 221–226 (2007)

    Google Scholar 

  19. Zhang, D.G., Zhu, K.Y.: Modeling biological motor control for human locomotion with functional electrical stimulation. Biol. Cybern. 96, 79–97 (2007)

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Robotics, School of Mechanical Engineering,  

    Dingguo Zhang, Guangquan Liu, Gan Huan & Xiangyang Zhu

  2. Institute of Neurology, Ruijin Hospital Shanghai Jiao Tong University, China

    Jianrong Liu

Authors
  1. Dingguo Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Guangquan Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Gan Huan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jianrong Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Xiangyang Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. School of Mechanical and Aerospace Engineering, Nanyang Technological University, 639798, Singapore

    Ming Xie

  2. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, 430074, Wuhan, P. R. China

    Youlun Xiong

  3. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, 430074, Wuhan, P.R. China

    Caihua Xiong

  4. Institute of Industrial Research, University of Portsmouth, PO1 3QL, Portsmouth, UK

    Honghai Liu

  5. Department of Computer Science and Electrical Engineering, Kumamoto University, 860-8555, Kumamoto, Japan

    Zhencheng Hu

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Zhang, D., Liu, G., Huan, G., Liu, J., Zhu, X. (2009). A Hybrid FES Rehabilitation System Based on CPG and BCI Technology for Locomotion: A Preliminary Study. In: Xie, M., Xiong, Y., Xiong, C., Liu, H., Hu, Z. (eds) Intelligent Robotics and Applications. ICIRA 2009. Lecture Notes in Computer Science(), vol 5928. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10817-4_105

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-10817-4_105

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10816-7

  • Online ISBN: 978-3-642-10817-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation