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