Scanning and Locating Target Position with Minimal Training for Brain Computer Interface

Authors

  • M. S. Adha Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Malaysia.
  • N. Mat Safri Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Malaysia.
  • M. A. Othman Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Malaysia.
  • I. Ariffin Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Malaysia.

Keywords:

BCI, EEG, Single Channel, Training,

Abstract

Elicited brain signal recorded noninvasively from the human scalp has been shown sufficiently to control a mobile system to some degree. To further extend the existed human-robot control strategy, this study demonstrated real time target selection based on single channel Brain Computer Interface (BCI) with single trial and without subject training. Subjects were required to synchronously imagine a star rotating and mind relaxation at a specific time and direction. The imagination of a star would trigger a mobile robot suggesting that there was an object to be selected at certain direction in the environment bounded by the human field of vision. This study statistically verifies that there was a significant difference (p<0.001) between star rotation imagery and mental relaxation means. Results from the current study also demonstrate that 95% of subjects were capable of synchronizing the suppression of alpha rhthym at a specific time, which suggested feasibility of the proposed target selection based on scanning scheme. A total of 80% of subjects were capable of selecitng a predetermined target's direction at the first attempt by utilizing individual's optimum parameter. On the other hand, 15% of subjects failed at the first attempt were observed to have succeeded by consecutive trials. Target could not be identified for all trials and six parameters by only a subject. The majority of subjects who could control the proposed system suggest the feasibility of the proposed control strategy by using only F8-electroencephalographic channel and with minimal training.

References

J. D. R. Millán, F. Renkens, J. Mouriño, and W. Gerstner, “Noninvasive brain-actuated control of a mobile robot by human EEG,” IEEE Trans. Biomed. Eng., vol. 51, no. 6, pp. 1026–33, Jun. 2004.

V. Gandhi, G. Prasad, D. Coyle, L. Behera, and T. M. Mcginnity, “EEG-based mobile robot control through an adaptive brain–robot interface,” IEEE Trans. Human-Machine Syst., pp. 1–8, 2014.

R. Ron-Angevin, F. Velasco-Alvarez, S. Sancha-Ros, and L. da SilvaSauer, “A two-class self-paced BCI to control a robot in four directions,” IEEE Int. Conf. Rehabil. Robot., vol. 2011, p. 5975486, Jan. 2011.

C. R. Hema, M. P. Paulraj, S. Yaacob, H. Adom, and R. Nagarajan, “Robot Chair Control using an Asynchronous Brain Machine Interface,” 2010 6th International Colloquium on Signal Processing & its Applications, Mallaca City, 2010, pp. 1-4

R. Leeb, D. Friedman, G. R. Müller-Putz, R. Scherer, M. Slater, and G. Pfurtscheller, “Self-paced (asynchronous) BCI control of a wheelchair in virtual environments: a case study with a tetraplegic.,” Comput. Intell. Neurosci., vol. 2007, p. 79642, Jan. 2007.

L. Bi, X. Fan, and Y. Liu, “EEG-Based brain-controlled mobile robots : a survey,” IEEE Trans. Human-Machine Syst., vol. 43, no. 2, pp. 161–176, 2013.

G. Pfurtscheller and C. Neuper, “Motor imagery and direct braincomputer communication,” Proc. IEEE, vol. 89, no. 7, pp. 1123– 1134, 2001.

V. P. C. Jenkinson, R. Fitzpatrick, M. Swash, “The ALS health profile study: Quality of life of amyotrophic lateral sclerosis patients and cares in europe,” J. Neurol, vol. 247, no. 11, pp. 835–840, 2000.

J. O. M. Hagedoorn, R. Sanderman, A. V. Ranchor, E. I. Brilman, G. I. Kempen, “Chronic disease in elderly couples; are women more responsive to their spouses’ health condition than men?,” J. Psychosom., vol. 51, no. 5, pp. 693–696, 2001.

H. Azmy and N. M. Safri, “EEG based bci using visual imagery task for robot control,” Jurnal Teknologi, vol. 2, pp. 7–11, 2013.

K. Hirano, S. Nishimura, and S. Mitra, “Design of Digital Notch Filters,” IEEE Trans. Commun., vol. 22, pp. 964–970, 1974.

G. Pfurtscheller and F. H. Lopes Da Silva, “Event-related EEG/MEG synchronization and desynchronization: Basic principles,” Clin. Neurophysiol, vol. 110, no. 11, pp. 1842–1857, 1999.

Peter D. Welch, “The use of fast fourier transform for the estimation of power spectra: a method based on time averaging over shoot, modified periodograms”, IEEE Trans. Audio and Electroacoust., vol. AU-15, pp.70-73, June 1967.

H. Cao, W. G. Besio, S. Jones, and P. Zhou, “Individualization of data-segment-related parameters for improvement of EEG signal classification in brain-computer interface,” Trans. Tianjin Univ., vol. 16, no. 3, pp. 235–238, 2010.

Published

2017-12-04

How to Cite

Adha, M. S., Mat Safri, N., Othman, M. A., & Ariffin, I. (2017). Scanning and Locating Target Position with Minimal Training for Brain Computer Interface. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9(3-9), 21–26. Retrieved from https://jtec.utem.edu.my/jtec/article/view/3137

Issue

Vol. 9 No. 3-9: Biomedical Electronics and Informatics

Section

Articles

License

TRANSFER OF COPYRIGHT AGREEMENT

The manuscript is herewith submitted for publication in the Journal of Telecommunication, Electronic and Computer Engineering (JTEC). It has not been published before, and it is not under consideration for publication in any other journals. It contains no material that is scandalous, obscene, libelous or otherwise contrary to law. When the manuscript is accepted for publication, I, as the author, hereby agree to transfer to JTEC, all rights including those pertaining to electronic forms and transmissions, under existing copyright laws, except for the following, which the author(s) specifically retain(s):

  1. All proprietary right other than copyright, such as patent rights
  2. The right to make further copies of all or part of the published article for my use in classroom teaching
  3. The right to reuse all or part of this manuscript in a compilation of my own works or in a textbook of which I am the author; and
  4. The right to make copies of the published work for internal distribution within the institution that employs me

I agree that copies made under these circumstances will continue to carry the copyright notice that appears in the original published work. I agree to inform my co-authors, if any, of the above terms. I certify that I have obtained written permission for the use of text, tables, and/or illustrations from any copyrighted source(s), and I agree to supply such written permission(s) to JTEC upon request.