Skip to main content
Springer Nature Link
Log in

Brain-Computer Interface Controlling Cyborg: A Functional Brain-to-Brain Interface Between Human and Cockroach

  • Chapter
  • First Online:
Brain-Computer Interface Research

Part of the book series: SpringerBriefs in Electrical and Computer Engineering ((BRIEFSELECTRIC))

Abstract

A kind of cyborg was developed by surgically linking a portable microstimulator with the nerves of antennas of a live cockroach. Through applying specific micro electrical stimulation, the cyborg could be remotely controlled to make left and right turns. The motion intention could be retrieved from the human brain via brain-computer interface (BCI). Steady-state visual evoked potential (SSVEP) based-electroencephalography (EEG), as a robust BCI, was used to translate human intention. By merging the technologies of cyborg and BCI, it was possible to guide a live cockroach with human brain. Experiments with different paradigms were designed and conducted to verify the performance of the proposed system. The experimental results showed that the average success rates of both human BCI and cyborg reactions in a single decision were over 85%. The cyborg could be steered successfully via the human brain to complete walking along pre-set tracks with a 20% success rate.

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

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
€32.70 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
EUR 29.95
Price includes VAT (France)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
EUR 42.79
Price includes VAT (France)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
EUR 52.74
Price includes VAT (France)
  • 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

Similar content being viewed by others

References

  1. A. Bozkurt, R. Gilmour, D. Stern, A. Lal, MEMS based bioelectronic neuromuscular interfaces for insect cyborg flight control (IEEE, 2008), pp. 160–163

    Google Scholar 

  2. H. Sato, C. Berry, Y. Peeri, E. Baghoomian, B. Casey et al., Remote radio control of insect flight. Frontiers in integrative neuroscience 3, 24 (2008)

    Google Scholar 

  3. H. Sato, C.W. Berry, B.E. Casey, G. Lavella, Y. Yao et al., A cyborg beetle: insect flight control through an implantable, tetherless microsystem (IEEE, 2008), pp. 164–167

    Google Scholar 

  4. H. Sato, Y. Peeri, E. Baghoomian, C. Berry, M. Maharbiz, Radio-controlled cyborg beetles: a radio-frequency system for insect neural flight control (IEEE, 2009), pp. 216–219

    Google Scholar 

  5. S.K. Talwar, S. Xu, E.S. Hawley, S.A. Weiss, K.A. Moxon et al., Behavioural neuroscience: rat navigation guided by remote control. Nature 417, 37–38 (2002)

    Article  Google Scholar 

  6. E.S. Krames, P.H. Peckham, A. Rezai, F. Aboelsaad, chapter 1—What is neuromodulation? in Neuromodulation, ed. by E.S.K.H.P.R. Rezai (San Diego, Academic Press, 2009), pp. 3–8

    Google Scholar 

  7. J. Okada, Cockroach antennae. Scholarpedia 4, 6842 (2009)

    Article  Google Scholar 

  8. C. Comer, Y. Baba, Active touch in orthopteroid insects: behaviours, multisensory substrates and evolution. Philos. Trans. Royal Soc. B: Biol. Sci. 366, 3006–3015 (2011)

    Article  Google Scholar 

  9. C. Comer, L. Parks, M. Halvorsen, A. Breese-Terteling, The antennal system and cockroach evasive behavior. II. Stimulus identification and localization are separable antennal functions. J. Comp. Physiol. A. 189, 97–103 (2003)

    Google Scholar 

  10. S. Ye, C.M. Comer, Correspondence of escape-turning behavior with activity of descending mechanosensory interneurons in the cockroach, Periplaneta americana. J. Neurosci. 16, 5844–5853 (1996)

    Google Scholar 

  11. J.R. Wolpaw, N. Birbaumer, D.J. McFarland, G. Pfurtscheller, T.M. Vaughan, Brain–computer interfaces for communication and control. Clin. Neurophysiol. 113, 767–791 (2002)

    Article  Google Scholar 

  12. B. Graimann, B. Allison, G. Pfurtscheller, Brain–computer interfaces: A gentle introduction (Springer, Brain-Computer Interfaces, 2010), pp. 1–27

    Google Scholar 

  13. J.J. Shih, D.J. Krusienski, J.R. Wolpaw, in Brain-Computer Interfaces in Medicine (Elsevier, 2012), pp. 268–279

    Google Scholar 

  14. B.Z. Allison, E.W. Wolpaw, J.R. Wolpaw, Brain–computer interface systems: progress and prospects. Expert Rev. Med. Devices 4, 463–474 (2007)

    Article  Google Scholar 

  15. G. Bin, X. Gao, Z. Yan, B. Hong, S. Gao, An online multi-channel SSVEP-based brain–computer interface using a canonical correlation analysis method. J. Neural Eng. 6, 046002 (2009)

    Article  Google Scholar 

  16. X. Gao, D. Xu, M. Cheng, S. Gao, A BCI-based environmental controller for the motion-disabled. IEEE Trans. Neural Syst. Rehabil. Eng. 11, 137–140 (2003)

    Article  Google Scholar 

  17. T. Latif, A. Bozkurt, Line following terrestrial insect biobots (2011), pp. 972–975

    Google Scholar 

  18. M. Pais-Vieira, M. Lebedev, C. Kunicki, J. Wang, M. Nicolelis, A brain-to-brain interface for real-time sharing of sensorimotor information. Sci. Rep. 3, 1319 (2012)

    Article  Google Scholar 

  19. R.P. Rao, A. Stocco, M. Bryan, D. Sarma, T.M. Youngquist et al., A direct brain-to-brain interface in humans. PLoS ONE 9, e111332 (2014)

    Article  Google Scholar 

  20. S.-S. Yoo, H. Kim, E. Filandrianos, S.J. Taghados, S. Park, Non-invasive brain-to-brain interface (BBI): establishing functional links between two brains. PLoS ONE 8, e60410 (2013)

    Article  Google Scholar 

Download references

Acknowledgements

We wish to acknowledge the human and cockroach subjects from our laboratory, both past and present. In particular, we thank Jinming Zhang for assisting us in the experiments and preparing some of the figures.

Author information

Authors and Affiliations

  1. Robotics Institute, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China

    Guangye Li & Dingguo Zhang

Authors
  1. Guangye Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dingguo Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Dingguo Zhang .

Editor information

Editors and Affiliations

  1. g.tec Guger Technologies OG , 4521 Schiedlberg, Austria

    Christoph Guger

  2. g.tec Guger Technologies OG, 4521 Schiedlberg, Austria

    Brendan Allison

  3. Biosciences and Informatics, Keio University Biosciences and Informatics, 223-8522 Yokohama, Kazagawa, Japan

    Junichi Ushiba

Rights and permissions

Reprints and permissions

Copyright information

© 2017 The Author(s)

About this chapter

Cite this chapter

Li, G., Zhang, D. (2017). Brain-Computer Interface Controlling Cyborg: A Functional Brain-to-Brain Interface Between Human and Cockroach. In: Guger, C., Allison, B., Ushiba, J. (eds) Brain-Computer Interface Research. SpringerBriefs in Electrical and Computer Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-57132-4_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-57132-4_6

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-57131-7

  • Online ISBN: 978-3-319-57132-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation