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[9] Armagan Amcalar and Mujdat Cetin, “Design, Implementation and Evaluation of a Real-
time P300-based Brain-Computer Interface System,” IEEE International Conference on
Pattern Recognition, pp. 117-120, 2010.
[10] Asa Ben-Hur and Jason Weston, “A User's Guide to Support Vector Machines,” Data
Mining Techniques for the Life Sciences, Oliviero Carugo1, Frank Eisenhaber, ISBN: 978-
1-60327-240-7, Springer Protocols, 2008. Available from
http://www.springerprotocols.com/Abstract/doi/10.1007-/978-1-60327-241-4_13.
[11] B. Blankertz, K.-R. Mueller, D. Krusienski, G. Schalk, J. Wolpaw, A. Schloegl, G.
Pfurtscheller, J. del R. Millan, M. Schroeder, and N. Birbaumer, “The BCI competition III:
Validating alternative approaches to actual BCI problems,” IEEE Transactions on Neural
Systems and Rehabilitation Engineering, vol. 14, no. 2, pp.. 153–159, 2006.
[12] Benjamin Blankertz, Klaus-Robert Müller, Gabriel Curio, Theresa M. Vaughan, Gerwin
Schalk, Jonathan R. Wolpaw, Alois Schlögl, Christa Neuper, Gert Pfurtscheller, Thilo
Hinterberger,Michael Schröder, and Niels Birbaumer, “The BCI Competition 2004: Progress
and Perspectives in Detection and Discrimination of EEG Single Trials,” IEEE transactions
on Biomedical Engineering, vol. 51, no. 6, pp.1044-1051, 2004.
[13] Berger, “Über das Elektrenkephalogramm des Menschen,” European Archives of Psychiatry
and Clinical Neuroscience, vol. 99, no. 1, pp. 555-574, 1929.
[14] Brendan Z. Allison and Jaime A. Pineda, “ERPs Evoked by Different Matrix Sizes:
Implications for A Brain Computer Interface (BCI) System,” IEEE Transactions on Neural
Systems and Rehabilitation Engineering, vol. 11, no. 2, pp. 110–113, 2003.
[15] Brice Rebsamen, Chee Leong Teo, Qiang Zeng, Marcelo H. Ang Jr, Etienne Burdet, Cuntai
Guan and Haihong Zhang, and Christian Laugier, “Controlling a Wheelchair Indoors Using
Thought,“ Intelligent Systems, IEEE, vol. 22, no.2, pp. 18-24, 2007.
[16] Changyuan Fan, Baoqiang Wang, and Hui Ju, “A New FastICA Algorithm with Symmetric
Orthogonalization,” Communications, Circuits and Systems Proceedings, IEEE, vol. 3, pp.
2058-2061, 2006.
[17] Chaunchu Wang, Cuntai Guan, and Haihong Zhang, “P300 Brain-Computer Interface
Design for Communication and Control Applications,” Engineering in Medicine and
Biology Society, IEEE, pp. 5400-5403, 2005.
104
[18] Chih-Chung Chang and Chih-Jen Lin, “LIBSVM: A Library for Support Vector Machines,”
http://www.csie.ntu.edu.tw/~cjlin/libsvm/.
[19] Christian J Bell, Pradeep Shenoy, Rawichote Chalodhorn and Rajesh P N Rao, “Control of a
humanoid robot by a noninvasive brain–computer interface in humans,” Journal of Neural
Engineering, vol. 5, pp. 214–220, 2008.
[20] Cuntai Guan, Manoj Thulasidas and Jiankang Wu, “High performance P300 speller for
brain-computer interface,” In Proceedings of IEEE International Workshop on Biomedical
Circuits and Systems, pp. S3/5/INV - S3/13-16, 2004.
[21] Dawn M. Taylor, Stephen I. Helms Tillery, and Andrew B. Schwartz, “Direct cortical
control of 3D neuroprosthetic devices,” Science, vol. 296, no. 5574, pp. 1829–1832, 2002.
[22] E. C. Lalor, S. P. Kelly, C. Finucane, R. Burke, R. Smith, R. B. Reilly, and G.McDarby,
“Steady-state VEP-based brain-computer interface control in an immersive 3D gaming
environment,” EURASIP Journal on Applied Signal Processing, vol. 19, pp. 3156–3164,
2005.
[23] E. Donchin, K. Spencer, R. Wijesinghe, “The mental prosthesis: Assessing the speed of a
P300-based brain-computer interface,” IEEE Transactions on Rehabilitation Engineering,
vol. 8, no. 2, pp. 174–179, 2000.
[24] EEGLAB: An Open Source Matlab Toolbox for EEG, EMG and other Electrophysiological
data. Available at: http://sccn.ucsd.edu/eeglab/.
[25] Eleanor Curran, Peter Sykacek, Maria Stokes, Stephen J. Roberts, Will Penny, Ingrid
Johnsrude, and Adrian M. Owen, “Cognitive tasks for driving a brain-computer interfacing
system: A pilot study,” IEEE Transactions on Neural Systems and Rehabilitation
Engineering, vol.12, no. 1, pp. 48–54, 2004.
[26] Emotiv: Become an Emotiv Researcher (2010), http://www.emotiv.com/researchers.
[27] Eric C. Leuthardt, Kai J. Miller, Gerwin Schalk, Rajesh P. N. Rao, and Jeffrey G. Ojemann,
“Electrocorticography-based brain computer interface-The Seattle experience,” IEEE
Transactions on Neural Systems and Rehabilitation Engineering, vol. 14, no. 2, pp. 194–198,
2006.
[28] F. Piccione, F. Giorgi, P. Tonina, K. Priftis, S. Giove, S. Silvoni, G. Palmas, F. Beverina.
“P300-based brain computer interface: Reliability and performance in healthy and paralysed
participants,” Clinical Neurophysiology, vol. 117, pp. 531–537, 2006.
105
[29] Farwell L.A. and Donchin E, “Talking off the top of your head: toward a mental prosthesis
utilizing event-related brain potentials,” Electroencephalography & Clinical
Neurophysiology, vol. 70, no. 6, pp. 510-23, 1988.
[30] Francesco Piccione, Konstantinos Priftis, Paolo Tonin, Denis Vidale, Roberto Furlan,
Marianna Cavinato, Antonio Merico, and Lamberto Piron, “Task and Stimulation Paradigm
Effects in a P300 Brain Computer Interface Exploitable in a Virtual Environment: A Pilot
Study,” PsychNology Journal, vol. 6, no. 1, pp. 99-108. 2008.
[31] G. Townsend, B.K. LaPallo, C.B. Boulay, D.J. Krusienski, G.E. Frye, C.K. Hauser, N.E.
Schwartz, T.M. Vaughan, J.R. Wolpaw, E.W. Sellers, “A novel P300-based brain–computer
interface stimulus presentation paradigm: Moving beyond rows and columns,” Clinical
Neurophysiology, vol. 121, no. 7, pp. 1109-1120, 2010.
[32] Galen F. Hagen, James R. Gatherwright, Brian A. Lopez and John Polich, “P3a from visual
stimuli: Task difficulty effects,” International Journal of Psychophysiology, vol. 59, no. 1,
pp. 8–14, 2006.
[33] Graimann, J. Huggins, S. Levine, and G. Pfurtscheller, “Toward a direct brain interface
based on human subdural recordings and wavelet-packet analysis,” IEEE Transactions on
Biomedical Engineering, vol. 51, no. 6, pp. 954–962, 2004.
[34] Hubert Cecotti and Axel Gr¨aser, “Convolutional neural networks for P300 Detection with
Application to Brain-Computer Interfaces,” Pattern Analysis and Machine Intelligence,
IEEE, vol. 33, no. 3, pp. 433-445, 2010.
[35] I. Iturrate, J. Antelis, A. K¨ubler and J. Minguez, “A Noninvasive Brain-Actuated
Wheelchair Based on a P300 Neurophysiological Protocol and Automated Navigation,”
Robotics, IEEE Transactions, vol. 25, no. 3, pp. 614-627, 2009.
[36] J. R. Wolpaw, D. J. McFarland, G. W. Neat, C. A. Forneris, “An EEG-based brain-computer
interface for cursor control,” Electroencephalography and Clinical Neurophysiology, vol. 78,
pp. 252–259, 1991.
[37] James B. Polikoff, H. Timothy Bunnell and Winslow J. Borkowski Jr, “Toward a P300-
based computer interface,” Proceedings of the RESNA ’95 Annual Conference, 1995.
[38] Javier Minguez, Carlos Escolano, Ander Ramos Murguialday, Tamara Matuz and Niels
Birbaumer, “A Telepresence Robotic System Operated with a P300-based Brain-Computer
106
Interface: Initial Tests with ALS patients,” Engineering in Medicine and Biology Society,
IEEE, pp. 4476-4480, 2010
[39] Jonathan Wolpaw and Dennis McFarland, “Control of a two-dimensional movement signal
by a noninvasive brain-computer interface in humans,” Proceedings of the National
Academy of Sciences, vol. 101, no. 51, pp. 17849–17854, 2004.
[40] Juan Manuel Ramírez-Cortes, Vicente Alarcon-Aquino, Gerardo Rosas-Cholula, Pilar
Gomez-Gil, and Jorge Escamilla-Ambrosio, “P-300 Rhythm Detection Using ANFIS
Algorithm and Wavelet Feature Extraction in EEG signals,” Proceedings of the World
Congress on Engineering and Computer Science, vol. I, 2010.
[41] K Stamps and Y Hamam, “Towards inexpensive BCI control for wheelchair navigation in
the enabled environment–a hardware survey,” Brain Informatics, pp. 336–345, 2010.
[42] K. A. Plant, P.V.S Ponnapalli and D.M. Southall, “Mobile Robots and EEG - A Review,”
Research and Development in Intelligent Systems XXIV, no. 9, pp. 363-368, 2008.
[43] Kavita Mahajan, M. R. Vargantwar, Sangita M. Rajput, “Classification of EEG using PCA,
ICA and Neural Network,” International Journal of Engineering and Advanced Technology,
vol. 1, no. 1, 2011.
[44] Kenji Kansaku, Naoki Hata, and Kouji Takanoa, “My thoughts through a robot's eyes: An
augmented reality-brain–machine interface,” Neuroscience Research, vol. 66, no. 2, pp. 219-
222, 2010.
[45] Kevin A. Jones, Bernice Porjesz, David Chorlian, Madhavi Rangaswamy, Chella Kamarajan,
Ajayan Padmanabhapillai, Arthur Stimus, Henri Begleiter, “S-transform time-frequency
analysis of P300 reveals deficits in individuals diagnosed with alcoholism,” Clinical
Neurophysiology, vol. 117, no. 10, pp. 2128-2143, 2010.
[46] Kun Li, Ravi Sankar, Yael Arbel and Emanuel Donchin, “Single Trial Independent
Component Analysis for P300 BCI System,” Engineering in Medicine and Biology Society,
IEEE, pp. 4035-4038, 2009.
[47] Luca Citi, Riccardo Poli and Caterina Cinel, “Documenting, modeling and exploiting P300
amplitude changes due to variable target delays in Donchin's speller,” Journal Of Neural
Engineering, vol. 7, no. 5, 21 pp., 2010.
107
[48] M. Kaper, Peter Meinicke, Ulf Grossekathoefer, Thomas Lingner, and Helge Ritter,
“Support vector machines for the P300 speller paradigm,” IEEE Transactions on Biomedical
Engineering, vol. 51, no. 6, pp. 1073–1076, 2004.
[49] M. Thulasidas, C. Guan, J. Wu, “Robust classification of EEG signal for brain-computer
interface,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 14,
no. 1, pp. 24–29, 2006.
[50] M.B. Priestley, “Wavelets and time-dependent spectral analysis,” Journal of Time Series
Analysis, vol.17, no. 1, pp. 85–103, 2008.
[51] Martin Lauritzen and Lorenz Gold, “Brain Function and Neurophysiological Correlates of
Signals Used in Functional Neuroimaging,” Journal of Neuroscience, vol. 23, no. 10, pp.
3972–3980, 2003.
[52] Martin T. Hagan, Howard B. Demuth, and Mark H. Beale, “Neural Network Design”,
Thomson Learning, USA, ISBN: 0-9717321-0-8, 1996.
[53] Miguel A. L. Nicolelis, Dragan Dimitrov, Jose M. Carmena, Roy Crist, Gary Lehew, Jerald
D. Kralik and Steven P. Wise, “Chronic, multisite, multielectrode recordings in macaque
monkeys,” Proceedings of the National Academy of Sciences, vol. 100, no. 19, pp. 11041–
11046, 2003.
[54] Mikhail A. Lebedev and Miguel A.L. Nicolelis, “Brain–machine interfaces past present and
future,” Trends in Neurosciences, Elsevier, vol.29, no.9, pp. 536–546, 2006.
[55] N. Birbaumer, N. Ghanayim, T. Hinterberger, I. Iversen, B. Kotchoubey, A. Kübler, J.
Perelmouter, E. Taub and H. Flor, “A spelling device for the paralysed,” Nature, vol. 398,
pp. 297–298, 1999.
[56] Nancy K. Squires, Kenneth C. Squires and Steven A. Hillyard, “Two varieties of long-
latency positive waves evoked by unpredictable auditory stimuli in man,”
Electroencephalography and Clinical Neurophysiology, vol. 38, pp. 387–401, 1975.
[57] Neng Xu, Xiaorong Gao, Bo Hong, Xiaobo Miao, Shangkai Gao, and Fusheng Yang, “BCI
competition 2003–Data Set IIb: Enhancing P300 wave detection using ICA-based subspace
projections for BCI applications,” IEEE Transactions on Biomedical Engineering, vol. 51,
no. 6, pp. 1067–1072, 2004.
108
[58] NeuroFocus: a market leader in bringing neuroscience expertise to advertising, branding,
product development and packaging, and entertainment:
http://www.neurofocus.com/company.htm.
[59] NeuroSky: BCI technology grounded in laboratory research (2010),
http://company.neurosky.com/university.
[60] Niels Birbaumer, Ander Ramos Murguialday, and Leonardo Cohen, “Brain-computer
interfaces: Communication and restoration of movement in paralysis,” Journal of Physiology,
vol. 579, no. 3, pp. 621–636, 2007.
[61] Nikolay Chumerin, Nikolay V. Manyakov, Adrien Combaz, Johan A.K. Suykens, Refet
Firat Yazicioglu, Tom Torfs, Patrick Merken, Herc P. Neves, Chris Van Hoof, and Marc M.
Van Hulle, “P300 Detection Based on Feature Extraction in On-line Brain-Computer
Interface,” KI 2009 Advances in Artificial Intelligence, vol. 5803, no. Ef 2005, pp. 339–346,
2009.
[62] Nuno Figueiredo, Filipe Silva, Pétia Georgieva and Ana Tomé, “Advances in Non-Invasive
Brain Computer Interfaces for Control and Biometry,” Recent Advances in Brain-Computer
Interface Systems, Prof. Reza Fazel (Ed.), ISBN: 978-953-307-175-6, InTech, 2001.
Available from: http://www.intechopen.com/books/recent-advances-in-brain-computer-
interface-systems/advances-in-non-invasive-brain-computer-interfaces-for-control-and-
biometry.
[63] Qiao Xiaoyan and Li Douzhe,Dong Youer. “P300 Feature Extraction Based on Parametric
Model and FastICA Algorithm,” Natural Computation, International Conference, IEEE, vol.
2, pp. 585–589, 2009.
[64] Ramesh Srinivasan, “Methods to improve the spatial resolution of EEG,” International
Journal of Bioelectromagnetism, vol. 1, no.1, pp. 102–111, 1999,
[65] Reza Fazel-Rezai and Waqas Ahmad, “P300-based Brain-Computer Interface Paradigm
Design,” Recent Advances in Brain-Computer Interface Systems, Prof. Reza Fazel (Ed.),
ISBN: 978-953-307-175-6, InTech, 2001. Available from:
http://www.intechopen.com/books/recent-advances-in-brain-computer-interface-
systems/p300-based-brain-computer-interface-paradigm-design.
109
[66] S. G. Mason , A. Bashashati, M. Fatourechi, K. F. Navarro, And G. E. Birch, “A
comprehensive survey of brain interface technology designs,” Annals of Biomedical
Engineering, vol. 35, no. 2, pp. 137–169, 2007.
[67] S. Kanoh, Member, IEEE, K. Miyamoto and T. Yoshinobu, “A P300-based BCI System for
Controlling Computer Cursor Movement,” Engineering in Medicine and Biology Society,
IEEE, 6405-8, 2011.
[68] S. Makeig and J. Onton, “ERP features and EEG dynamics: An ICA perspective,” Oxford
Handbook of Event-Related Potential Components, pp. 1–51, New York, Oxford University
Press, 2009.
[69] S. Makeig, M. Westerfield, T.-P. Jung, J. Covington, J. Townsend, T. J. Sejnowski, and E.
Courchesne, “Functionally independent components of the late positive event-related
potential during visual spatial attention,” The Journal of Neuroscience, vol. 19, no. 7, pp.
2665–2680,1999.
[70] S. Makeig, M. Westerfield, T.-P. Jung, S. Enghoff, J. Townsend, E. Courchesne, and T. J.
Sejnowski, “Dynamic brain sources of visual evoked responses,” Science, vol. 295, no. 5555,
pp. 690–694, 2002.
[71] S. Wang and C. J. James, “Enhancing evoked responses for BCI through advanced ICA
techniques,” IEEE, International Conference on Advances in Medical, Signal and
Information Processing, pp. 1–4, 2006.
[72] Sam Darvishi and Ahmed Al-Ani, “Brain-Computer Interface Analysis using Continuous
Wavelet Transform and Adaptive Neuro-Fuzzy Classifier,” International Conference of the
IEEE on Engineering in Medicine and Biology Society, pp. 3220-3223, 2007.
[73] Samuel Sutton, Margery Braren, Joseph Zubin and E. R. John, “Evoked-potential correlates
of stimulus uncertainty,” Science, vol. 150, no. 700, pp. 1187–1188, 1965.
[74] Sellers and E. Donchin, “A P300-based brain-computer interface: Initial tests by ALS
patients,” Clinical Neurophysiology, vol. 117, no. 3, pp. 538–548, 2006.
[75] Seyedehmina Ayoubian Markazi, S. Qazi, Lampros. S. Stergioulas, Anusha Ramchurn and
David Bunce, “Wavelet Filtering of the P300 Component in Event-Related Potentials,”
International Conference of the IEEE on Engineering in Medicine and Biology Society, pp.
1719-1722, 2006
110
[76] Takano, K., Komatsu, T., Hata, N., Nakajima, Y., Kansaku, K., “Visual stimuli for the P300
brain–computer interface: a comparison of white/gray and green/blue flicker matrices,”
Clinical Neurophysiology, vol. 120, no. 8, pp. 1562–1566, 2009.
[77] The FastICA algorithm package for MATLAB. Laboratory of Information and Computer
Science, Helsinki University of Technology, http://research.ics.tkk.fi/ica/fastica.
[78] Thierry Castermans, Matthieu Duvinage, Mathieu Petieau, Thomas Hoellinger, Caty De
Saedeleer, Karthik Seetharaman, Ana Bengoetxea, Guy Cheron and Thierry Dutoit
“Optimizing the Performances of a P300-Based Brain–Computer Interface in Ambulatory
Conditions,” IEEE Journal on Emerging and Selected Topics in Circuits and Systems, vol. 1,
no. 4, pp. 566-577, 2011.
[79] Tzyy-Ping Jung, Scott Makeig, Marissa Westerfield, Jeanne Townsend, Eric Courchesne,
and Terrence J. Sejnowski, “Analysis and Visualization of Single-Trial Event-Related
Potentials,” Hum Brain Mapping, vol. 14, no. 3, pp. 166-85, 2001.
[80] Ulrich Hoffmann, Jean-Marc Vesin, Karin Diserens, and Touradj Ebrahimi, “An efficient
P300-based brain-computer interface for disabled subjects,” Journal of Neuroscience
Methods, vol. 167, no. 1, pp. 115–125, 2008.
[81] V. Bostanov, “Feature extraction from event-related brain potentials with the continuous
wavelet transform and the t-value scalogram,” IEEE Transactions on Biomedical
Engineering, vol. 51, no. 6, pp. 1057–1061, 2004.
[82] Vahid Abootalebi, Mohammad Hassan Moradi, Mohammad Ali Khalilzadeh, “A new
approach for EEG features extraction in P300-based lie detection,” Computer Methods and
Programs in Biomedicine, vol. 94, no. 1, pp. 48–57. 2009.
[83] Vasil Kolev, Tamer Demiralp, Juliana Yordanova, Ahmet Ademoglu, and Ümmühan Isoglu-
Alkaç, “Time-Frequency Analysis Reveals Multiple Functional Components during Oddball
P300,” NeuroReport, vol. 8, no. 8, pp. 2061-2065. 1997.
[84] Wolpaw JR, Birbaumer N, McFarland DJ, Pfurtscheller G, Vaughan TM, “Brain-computer
interfaces for communication and control,” Clinical Neurophysiology, vol. 113, no 6, pp.
767–791, 2002.
VITA
Nizar Ali Khemri
Candidate for the Degree of
Master of Science
Thesis: P300 WAVE DETECTION USING A COMMERCIAL NON-INVASIVE EEG
SENSOR: RELIABILITY AND PERFORMANCE IN CONTROL
Major Field: Electrical Engineering
Biographical:
Education:
Completed the requirements for the Master of Science in Electrical Engineering
at Oklahoma State University, Stillwater, Oklahoma in July, 2012.
Completed the requirements for the Bachelor of Science in Computer
Engineering at Al Fateh University, Tripoli, Libya in 2006.
Experience:
Worked at Waha Oil Company as a computer technician from 1997 to 2006.
Worked at Waha Oil Company as a computer engineer from 2006 to 2009.
Currently working at Tripoli University.
ADVISER’S APPROVAL: Dr. Weihua Sheng
Name: Nizar Ali Khemri Date of Degree: July, 2012
Institution: Oklahoma State University Location: Stillwater, Oklahoma
Title of Study: P300 WAVE DETECTION USING A COMMERCIAL NON-
INVASIVE EEG SENSOR: RELIABILITY AND PERFORMANCE
IN CONTROL APPLICATIONS
Pages in Study: 110 Candidate for the Degree of Master of Science
Major Field: Electrical Engineering
Scope and Method of Study: This thesis proposes a P300-based Brain Computer Interface
(BCI) system that uses Emotiv Epoc headset (one of the recently commercially
developed headsets for consumers to be used for entertainment purposes) as an EEG
sensor to control simple real-time applications. In the recent years, many developers
have proposed commercial EEG sensors that can be used in different gaming and
entertainment applications. The low cost of these devices compared to the expensive
professional devices motivated several individual and group hobbyists to use these
sensors in the research field. A decade back in the time, it was impossible for
individuals to participate in the research field of BCI and develop their own
purposed applications. Nowadays, inexpensive EEG sensors such as Emotiv Epoc
headset make it possible for those hobbyists to develop different real life
applications. However, the use of such commercial noisy EEG sensors raises the
question about the appropriate approaches and algorithms that can process EEG
signals acquired by theses sensors and detect the P300 wave among them.
Consequently, the work in this thesis first, extensively reviews general BCI systems,
different aspects and approaches of P300-based BCI systems proposed in the
literature and available low-cost EEG acquisition systems and selected examples of
their use in BCI related research. Second, specific P300-based BCI systems data
processing and classification algorithms are tested and compared with well-known
benchmark P300 datasets provided from the BCI Competition III, 2004. Finally, the
tested algorithms and approaches are applied in the proposed P300-based BCI and
real-time experiments are performed to test the feasibility of such an inexpensive
BCI system in simple control applications such as cursor movement. In the future,
more complex applications, such as mobile robot control, can be tested with this
system.
Findings and Conclusions: The overall accuracy of the system is comparable to similar
studies and could reach to high fifties of an overall accuracy. To sum up, the results
show that using commercial EEG sensors in the research field of BCIs is feasible
and promising. Future developments can improve the efficiency of the commercial
EEG sensors and that will lead to an affordable more accurate P300-based BCI
system.
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