Skip to main content
SpringerLink
Log in

Using EEG Based Brain-Computer Interface to Control Actions in Applications – The Way to Provide New Possibilities for Disabled People

  • Conference paper
  • First Online:
Control, Computer Engineering and Neuroscience (ICBCI 2021)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1362))

Abstract

Nowadays, many researches are focusing on finding new technologies which can lead to the revolution in all branches of science. A lot of institutes focus on the dormant potential of the human’s brain. The signals from the scalp through electroencephalography (EEG) are the key to obtain many new possibilities for example controlling actions in applications with human’s brain. An EEG based brain-computer interface can be used to enable the disabled people doing things equal to normal people, but by use of their brain potential.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
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. Irimia, D.C., Ortner, R., Krausz, G., Guger, C., Poboroniuc, M.S.: BCI application in robotics control. IFAC 45(6), 1869–1874 (2012)

    Google Scholar 

  2. Paszkiel, S., Szpulak, P.: Methods of acquisition, archiving and biomedical data analysis of brain functioning. In: Hunek, W.P., Paszkiel, S. (eds.) Biomedical Engineering and Neuroscience. Book Series: Advances in Intelligent Systems and Computing, vol. 720, pp. 158–171 (2018). https://doi.org/10.1007/978-3-319-75025-5_15

  3. Mokienko, O.A., Chernikova, L.A., Frolov, A.A., Bobrov, P.D.: Motor imagery and its practical application. Neurosci. Behav. Physiol. 44(5), 483–489 (2014)

    Article  Google Scholar 

  4. Irimia, D.C., Ortner, R., Poboroniuc, M.S., Ignat, B.E.: High classification accuracy of a motor imagery based brain-computer interface for stroke rehabilitation training. Front. Robot. AI 5, 130 (2018)

    Article  Google Scholar 

  5. Paszkiel, S., Sikora, M.: The use of brain-computer interface to control unmanned aerial vehicle. In: Szewczyk, R., Zielinski, C., Kaliczynska, M. (eds.) Automation 2019: Progress in Automation, Robotics And Measurement Techniques. Advances in Intelligent Systems and Computing, vol. 920, pp. 583–598 (2020). https://doi.org/10.1007/978-3-030-13273-6_54

  6. Paszkiel, S., Hunek, W.P., Shylenko, A.: Project and simulation of a portable device for measuring bioelectrical signals from the brain for states consciousness verification with visualization on LEDs. In: Szewczyk, R., Zielinski, C., Kaliczynska, M. (eds.) Challenges in Automation, Robotics and Measurement Techniques. Advances in Intelligent Systems and Computing, vol. 440, pp. 25–35 (2016). https://doi.org/10.1007/978-3-319-29357-8_3

  7. Paszkiel, S.: The use of facial expressions identified from the level of the EEG signal for controlling a mobile vehicle based on a state machine. In: Szewczyk, R., Zielinski, C., Kaliczynska, M. (eds.) Automation 2020: Towards Industry of the FutureBook Series. Advances in Intelligent Systems and Computing, vol. 1140, pp. 227–238 (2020). https://doi.org/10.1007/978-3-030-40971-5_21

  8. Paszkiel, S.: Data acquisition methods for human brain activity. In: Analysis and Classification of EEG Signals for Brain-Computer Interfaces. Studies in Computational Intelligence, vol. 852, pp. 3–9 (2020). https://doi.org/10.1007/978-3-030-30581-9_2

  9. Paszkiel, S.: Using the raspberry PI2 module and the brain-computer technology for controlling a mobile vehicle. In: Szewczyk, R., Zielinski, C., Kaliczynska, M. (eds.) Automation 2019: Progress in Automation, Robotics and Measurement Techniques. Advances in Intelligent Systems and Computing, vol. 920, pp. 356–366 (2020). https://doi.org/10.1007/978-3-030-13273-6_34

  10. Guy, V., Soriani, M.H., Bruno, M., et al.: Brain computer interface with the P300 speller: usability for disabled people with amyotrophic lateral sclerosis. Ann. Phys. Rehabil. Med. (2017)

    Google Scholar 

  11. Li, F., Tao, Q., Peng, W., Zhang, T., et al.: Inter-subject P300 variability relates to the efficiency of brain networks reconfigured from resting – to task-state: evidence from a simultaneous event-related EEG-fMRI study. NeuroImage 205, 116285 (2019)

    Article  Google Scholar 

  12. Won, K., Kwon, M., Jang, S., et al.: P300 speller performance predictor based on RSVP multi-feature. Front. Hum. Neurosci. 13, 261 (2019)

    Article  Google Scholar 

  13. Paszkiel, S.: Characteristics of question of blind source separation using moore-penrose pseudoinversion for reconstruction of EEG signal. In: Szewczyk, R., Zielinski, C., Kaliczynska, M. (eds.) Automation 2017: Innovations in Automation, Robotics and Measurement Techniques. Advances in Intelligent Systems and Computing, vol. 550, pp. 393–400 (2017). https://doi.org/10.1007/978-3-319-54042-9_36

  14. Speier, W., Deshpande, A., Cui, L., Chandravadia, N., Roberts, D., Pouratian, N.: A comparison of stimulus types in online classification of the P300 speller using language models. PLoS ONE 12(4), (2017)

    Article  Google Scholar 

  15. Researchgate. https://www.researchgate.net/figure/Screenshot-of-6-x-6-P300-Speller-and-experimental-environment_fig1_220366680. Accessed 10 Nov 2018

  16. George, J.A., Kluger, D.T., Davis, T.S., Wendelken, S.M., Okorokova, E.V., et al.: Biomimetic sensory feedback through peripheral nerve stimulation improves dexterous use of a bionic hand. Sci. Robot. (2019)

    Google Scholar 

  17. University of Utah: Motorized prosthetic arm can sense touch, move with your thoughts (2019)

    Google Scholar 

  18. Mobius bionics page. http://www.mobiusbionics.com/luke-arm/. Accessed 11 Nov 2018

  19. Fatherly page. https://www.fatherly.com/news/robotic-arm-inspired-by-luke-skywalker-gives-amputees-the-ability-to-touch-and-feel-again/. Accessed 11 Nov 2018

  20. Mobius bionics page. http://www.mobiusbionics.com/wpcontent/uploads/2019/09/Mobius-Bionics-LUKE-Product-Spec-Sheet.pdf. Accessed 11 Nov 2018

  21. Paszkiel, S., Dobrakowski, P., Lysiak, A.: The impact of different sounds on stress level in the context of EEG, cardiac measures and subjective stress level: a pilot study. Brain Sci. 10(10), 728 (2020). https://doi.org/10.3390/brainsci10100728

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, Prószkowska 76, 45-758, Opole, Poland

    Mateusz Adamczyk & Szczepan Paszkiel

Authors
  1. Mateusz Adamczyk
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Szczepan Paszkiel
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mateusz Adamczyk .

Editor information

Editors and Affiliations

  1. Faculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, Opole, Poland

    Szczepan Paszkiel

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Adamczyk, M., Paszkiel, S. (2021). Using EEG Based Brain-Computer Interface to Control Actions in Applications – The Way to Provide New Possibilities for Disabled People. In: Paszkiel, S. (eds) Control, Computer Engineering and Neuroscience. ICBCI 2021. Advances in Intelligent Systems and Computing, vol 1362. Springer, Cham. https://doi.org/10.1007/978-3-030-72254-8_13

Download citation

Publish with us

Policies and ethics

Search

Navigation