Call for Paper - January 2023 Edition
IJCA solicits original research papers for the January 2023 Edition. Last date of manuscript submission is December 20, 2022. Read More

Analyzing EEG based Neurological Phenomenon in BCI Systems

Print
PDF
International Journal of Computer Applications
© 2012 by IJCA Journal
Volume 57 - Number 17
Year of Publication: 2012
Authors:
Mandeep Kaur
P. Ahmed
M. Qasim Rafiq
10.5120/9209-3755

Mandeep Kaur, P Ahmed and Qasim M Rafiq. Article: Analyzing EEG based Neurological Phenomenon in BCI Systems. International Journal of Computer Applications 57(17):40-49, November 2012. Full text available. BibTeX

@article{key:article,
	author = {Mandeep Kaur and P. Ahmed and M. Qasim Rafiq},
	title = {Article: Analyzing EEG based Neurological Phenomenon in BCI Systems},
	journal = {International Journal of Computer Applications},
	year = {2012},
	volume = {57},
	number = {17},
	pages = {40-49},
	month = {November},
	note = {Full text available}
}

Abstract

The paper presents a comprehensive survey on International system for EEG (Electroencephalography) signal acquisition. The paper also explored various neuro-imaging techniques and EEG based neurological phenomenon applied for the development of BCI systems extremely useful for able bodied and disabled people. From the survey it is concluded that P300 signal are the most appropriate signal for classifying brain activity using EEG imaging technique.

References

  • Carolyn Asbury, "Brain Imaging Technologies and Their Applications in Neuroscience" The Dana Foundation, Nov2011.
  • Vasileios Megalooikonomou, James Ford, Li Shen, Fillia Makedon, "Data mining in brain imaging", Statistical Methods in Medical Research, vol. 9, pp. 359–394, 2000.
  • Demitri, M. (2007), "Types of Brain Imaging Techniques", http://psychcentral. com/lib/2007/types-of-brain-imaging-techniques, Retrieved on May 16, 2012.
  • Abigail A. Baird, "Brain Imaging", http://faculty. vassar. edu/abbaird/resources/brain_science/imaging. php
  • Shiliang Sun, Changshui Zhang, "Adaptive feature extraction for EEG signal classification", Med. Biol. Engineering and Computing vol. 44, no. 10, pp. 931-935, 2006.
  • Francesc Benimeli and Ken Sharman, "Electroencephalogram signal classification for brain computer interfaces using wavelets and support vector machines", Proceedings of European Symposium on Artificial Neural Networks Bruges (Belgium), pp. 361-366, 25-27 April 2007.
  • Dandan Huang, "EEG-Based Online Two-Dimensional Cursor Control", 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Minneapolis, Minnesota, USA, pp. 4547-4550, September 3-6, 2009.
  • I. Iturrate, J. Antelis and J. Minguez, "Synchronous EEG Brain-Actuated Wheelchair with Automated Navigation", IEEE International Conference on Robotics and Automation Kobe International Conference Center Kobe, Japan, pp. 2318-2325, May 12-17, 2009.
  • Yuan-Pin Lin, Chi-Hong Wang, Tien-Lin Wu, Shyh-Kang Jeng and Jyh-Horng Chen, "Support Vector Machine for EEG Signal Classification during Listening to Emotional Music", IEEE 10th Workshop on Multimedia Signal Processing, pp. 127-130, 8-10 Oct. 2008.
  • Dong Ming, Yuhuan Zhu, Hongzhi Qi, Baikun Wan, Yong Hu, KDK Luk, "Study on EEG-Based Mouse System by Using Brain-Computer Interface", IEEE International Conference on Virtual Environments, Human-Computer Interfaces and Measurements Systems, Hong Kong, China, pp. 236-239, May 11-13, 2009.
  • Eduardo Iáñez , José María Azorín, Andrés Úbeda, José Manuel Ferrández, Eduardo Fernández, "Mental tasks-based brain–robot interface", Robotics and Autonomous Systems, vol. 58, no. 12, pp. 1238-1245, 31 December 2010.
  • Tie-Jun Liu, Ping Yang, Xu-Yong Peng, Yu Huang, and De-Zhong Yao, "Real-Time Brain-Computer Interface System Based on Motor Imagery", Journal of Electronic Science and Technology of China, vol. 7, no. 1, March 2009.
  • Kelly, S, Burke, D. ; de Chazal, P. ; Reilly, R. , "Parametric models and spectral analysis for classification in brain-computer interfaces", 14th International Conference on Digital Signal Processing, vol. 1, pp. 307-310, 2002.
  • Hailong Liu, Jue Wang, Chongxun Zheng and Ping He, "Study on the Effect of Different Frequency Bands of EEG Signals on Mental Tasks Classification", 27th Annual International Conference of the Engineering in Medicine and Biology Society, Shanghai, China, pp. 5369-5372, 17-18 Jan. 2006.
  • Ronny Plontke, "Language and Brain", Term paper, Proseminar "Linguistically relevant films", Anne SchrÄoder WS 02/03, March 13, 2003.
  • Baher Soliman, Mariam Tadros, Marian Abdel-Shahid, Mina Guirguis, Mina Mikhail, Nadine Shehad, "Brain Computer Interface", Thesis Project Proposal, The American University in Cairo Computer Science Department.
  • 10-20 International System, "iomstudy. com/measure%20head%20x. swf/, this domain deleted on 5 March, 2012 and pending for removal.
  • Ilja Kuzovkin, "Pattern recognition for non-invasive EEG-based BCI", Bachelor's thesis, University of Tartu Faculty of Mathematics and Computer Science Institute of Computer Science, June 2011
  • Raymond Carl Smith, "Electroencephalograph based Brain Computer Interfaces", A thesis presented to University College Dublin (NUI) Dublin, Ireland, Feb 2004
  • Pierre Ferrez, "Error-Related EEG Potentials in Brain-Computer Interfaces", ÉCOLE POLYTECHNIQUE FÉDÉRALE DE LAUSANNE, EPFL 2007
  • Mandeep Kaur, P Ahmed and Qasim M Rafiq. Article, "Technology Development for Unblessed People using BCI: A Survey", International Journal of Computer Applications by Foundation of Computer Science, New York, USA, vol. 40, no. 1, pp. 18-24, February 2012.
  • Luis Fernando Nicolas-Alonso and Jaime Gomez-Gil, "Brain Computer Interfaces, a Review", Sensors, vol. 12, pp. 1211-1279.
  • Hinterberger, T. ; Wilhelm, B. ; Mellinger, J. ; Kotchoubey, B. ; Birbaumer, N. , "A device for the detection of cognitive brain functions in completely paralyzed or unresponsive patients", IEEE Transactions on Biomedical Engineering, vol. 52, no. 2, pp. 211-220, Feb. 2005. References Cited: 30 Cited by: 9
  • Diserens, K. ; Ebrahimi, T. ; Hoffmann, U. ; & Vesin, J. M. , "An efficient P300-based brain-computer interface for disabled subjects", Journal of Neuroscience Methods, vol. 167, no. 1, pp. 115-125, 15 January 2008.
  • Beverina, F. ; Giorgi, F. ; Giove, S. ; Palmas, G. ; Piccione, F. ; Priftis, K. ; Silvoni, S. ; & Tonin, P. , "P300based brain computer interface: Reliability and performance in healthy and paralyzed participants", Journal of Clinical Neurophysiology, vol. 117, no. 3, pp. 531-7, 2006.
  • Shijian Lu, Cuntai Guan and Haihong Zhang, "Subject-Independent Brain Computer Interface through Boosting", 19th International Conference on Pattern Recognition, (ICPR, 2008), Tampa, FL, pp. 1 – 4, 8-11Dec. 2008.