Skip to main content

Methods of Acquisition, Archiving and Biomedical Data Analysis of Brain Functioning

  • Conference paper
  • First Online:
Biomedical Engineering and Neuroscience (BCI 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 720))

Included in the following conference series:

Abstract

The following article sets out four acquisition methods of data obtained on the basis of brain signals: EEG, NIRS, fMRI as well as PET. Moreover, it provides the readout analysis of the signals occurring within the human brain and a possible manner of archiving and processing them. For an illustrative readout of the signals, a multi-channel encephalograph was applied. With the use of Emotiv Xavier TestBench application, time-varying EEG signals from individual electrodes were recorded in the .edf format which were subsequently subjected to Toolbox EEGLab for Matlab.

Szczepan Paszkiel, PhD. Eng., Assistant Professor; Piotr Szpulak, Msc. Eng.

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 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. Mathewson, K.E., Lleras, A., Beck, D.M., Fabiani, M., Ro, T., Gratton, G.: Pulsed out of awareness: EEG alpha oscillations represent a pulsed-inhibition of ongoing cortical processing. Front. Psychol., February 2011. https://doi.org/10.3389/fpsyg.2011.00099

  2. Ghaemi, A., Rashedi, E., Pourrahimi, A.M., Kamandar, M., Rahdari, F.: Automatic channel selection in EEG signals for classification of left or right hand movement in BCI using improved binary gravitation search algorithm. Biomed. Sig. Process. Control 33, 109–118 (2017). https://doi.org/10.1016/j.bspc.2016.11.018

    Article  Google Scholar 

  3. Ovaysikia, S., Tahir, K.A., Chan, J.L., DeSouza, J.F.X.: Word wins over face: emotional Stroop effect activates the frontal cortical network. Front. Hum. Neurosci., January 2011. https://doi.org/10.3389/fnhum.2010.00234

  4. Delorme, A., Makeig, S.: EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J. Neurosci. Methods 134(1), 9–21 (2004). https://doi.org/10.1016/j.jneumeth.2003.10.009

    Article  Google Scholar 

  5. Ghaemia, A., Rashedia, E., Mohammad, P.A., Kamandara, M., Rahdaric, F.: Automatic channel selection in EEG signals for classification of left or right hand movement in Brain Computer Interfaces using improved binary gravitation search algorithm. Biomed. Sig. Process. Control 33, 109–118 (2017). https://doi.org/10.1016/j.bspc.2016.11.018

    Article  Google Scholar 

  6. Paszkiel, S., Hunek, W., Shylenko, A.: Project and simulation of a portable proprietary device for measuring bioelectrical signals from the brain for verification states of consciousness with visualization on LEDs, Recent research in automation, robotics and measuring techniques. In: Szewczyk, R., Zielinski, C., Kaliczynska, M. (eds.) Challenges in Automation, Robotics and Measurement Techniques. Advances in Intelligent Systems and Computing, vol. 440, pp. 25–36. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-29357-8

  7. Wei-Yen, H.: Brain-computer interface connected to telemedicine and telecommunication in virtual reality applications. Telematics Inform. 34(4), 224–238 (2017). https://doi.org/10.1016/j.tele.2016.01.003

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Szczepan Paszkiel .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Paszkiel, S., Szpulak, P. (2018). Methods of Acquisition, Archiving and Biomedical Data Analysis of Brain Functioning. In: Hunek, W., Paszkiel, S. (eds) Biomedical Engineering and Neuroscience. BCI 2018. Advances in Intelligent Systems and Computing, vol 720. Springer, Cham. https://doi.org/10.1007/978-3-319-75025-5_15

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-75025-5_15

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-75024-8

  • Online ISBN: 978-3-319-75025-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics