Skip to main content

A Multi-channel EMG-Driven FES Solution for Stroke Rehabilitation

  • Conference paper
  • First Online:
Intelligent Robotics and Applications (ICIRA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10984))

Included in the following conference series:

Abstract

Functional electrical stimulation (FES) has been applied to stroke rehabilitation for many years. However, users are usually involved in open-loop fixed cycle FES systems in clinical, which is easy to cause muscle fatigue and reduce rehabilitation efficacy. This paper proposes a multi-surface EMG-driven FES integration solution for enhancing upper-limb stroke rehabilitation. This wireless portable system consists of sEMG data acquisition module and FES module, the former is used to capture sEMG signals, the latter of multi-channel FES output can be driven by the sEMG. Preliminary experiments proved that the system has outperformed existing similar systems and that sEMG can be effectively employed to achieve different FES intensity, demonstrating the potential for active stroke rehabilitation.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Lynch, C.L., Popovic, M.R.: Functional electrical stimulation. IEEE Control Syst. 28(2), 40–50 (2008)

    Article  MathSciNet  Google Scholar 

  2. Liberson, W.: Functional electrotherapy: stimulation of the peroneal nerve synchronized with the swing phase of the gait of hemiplegic patients. Arch. Phys. Med. Rehabil. 42, 101 (1961)

    Google Scholar 

  3. Popović, D.B.: Advances in functional electrical stimulation (FES). J. Electromyogr. Kinesiol. 24(6), 795–802 (2014)

    Article  Google Scholar 

  4. Lyons, G.M., Sinkjær, T., Burridge, J.H., Wilcox, D.J.: A review of portable FES-based neural orthoses for the correction of drop foot. IEEE Trans. Neural Syst. Rehabil. Eng. 10(4), 260–279 (2002)

    Article  Google Scholar 

  5. Edgerton, V.R., Roy, R.R.: Robotic training and spinal cord plasticity. Brain Res. Bull. 78(1), 4–12 (2009)

    Article  Google Scholar 

  6. Lotze, M., Braun, C., Birbaumer, N., Anders, S., Cohen, L.G.: Motor learning elicited by voluntary drive. Brain 126(4), 866–872 (2003)

    Article  Google Scholar 

  7. Quandt, F., Hummel, F.C.: The influence of functional electrical stimulation on hand motor recovery in stroke patients: a review. Exp. Trans. Stroke Med. 6(1), 9 (2014)

    Article  Google Scholar 

  8. Hong, I.K., Choi, J.B., Lee, J.H.: Cortical changes after mental imagery training combined with electromyography-triggered electrical stimulation in patients with chronic stroke. Stroke 43(9), 2506–2509 (2012)

    Article  Google Scholar 

  9. Fujiwara, T.: Motor improvement and corticospinal modulation induced by hybrid assistive neuromuscular dynamic stimulation (hands) therapy in patients with chronic stroke. Neurorehabilitation Neural Repair 23(2), 125–132 (2009)

    Article  Google Scholar 

  10. Fang, Y., Zhu, X., Liu, H.: Development of a surface EMG acquisition system with novel electrodes configuration and signal representation. In: Lee, J., Lee, M.C., Liu, H., Ryu, J.-H. (eds.) ICIRA 2013. LNCS (LNAI), vol. 8102, pp. 405–414. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-40852-6_41

    Chapter  Google Scholar 

  11. Forvi, E., et al.: Preliminary technological assessment of microneedles-based dry electrodes for biopotential monitoring in clinical examinations. Sens. Actuators A Phys. 180, 177–186 (2012)

    Article  Google Scholar 

Download references

Acknowledgments

This work is supported by the National Natural Science Foundation of China (No. 51575338, 51575407, 51475427) and the Fundamental Research Funds for the Central Universities (17JCYB03).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yu Zhou .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Zhou, Y., Fang, Y., Zeng, J., Li, K., Liu, H. (2018). A Multi-channel EMG-Driven FES Solution for Stroke Rehabilitation. In: Chen, Z., Mendes, A., Yan, Y., Chen, S. (eds) Intelligent Robotics and Applications. ICIRA 2018. Lecture Notes in Computer Science(), vol 10984. Springer, Cham. https://doi.org/10.1007/978-3-319-97586-3_21

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-97586-3_21

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-97585-6

  • Online ISBN: 978-3-319-97586-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics