Computational Intelligence for Pattern Recognition in EEG Signals

Aunnoy K Mutasim; Rayhan Sardar Tipu; M Raihanul Bashar; Md Kafiul Islam; M Ashraful Amin

doi:10.1007/978-3-319-89629-8_11

Book Section2018Cited by 10

Computational Intelligence for Pattern Recognition in EEG Signals

Aunnoy K Mutasim, Rayhan Sardar Tipu, M Raihanul Bashar, Md Kafiul Islam, M Ashraful Amin

Computational Intelligence for Pattern Recognition

Springer, pp. 291–320, ISBN: 9783319896281

DOI: 10.1007/978-3-319-89629-8_11 URL

Keywords

ElectroencephalographyComputer scienceArtificial intelligenceInterface (matter)Brain–computer interfacePattern recognition (psychology)Feature extractionProcess (computing)Noise (video)Computational modelSpeech recognitionMachine learning

CCDS Authors

Md Kafiul Islam, PhD

Director, BISPL Wing

Professor

Dept. of Electrical and Electronic Engineering

Independent University, Bangladesh (IUB)

M Ashraful Amin, PhD

Founder Director, CCDS
Director, AI/ML, HCI & DS Wings

Professor

Department of Computer Science and Engineering

Independent University, Bangladesh

Research Interests

Machine Learning, Cognitive & Vision Science, Cybernetics, Surveillance & Security, ICT in Education, Health, & Agriculture, Human-Computer Interaction, Internet of Things, Robotics

References

1.Tzyy‐Ping Jung, Scott Makeig, Colin Humphries, Te‐Won Lee, Martin J. McKeown, Vicente J. Iragui, Terrence J. Sejnowski. (2000). Removing electroencephalographic artifacts by blind source separation. Psychophysiology, 37(2), 163–178[10.1111/1469-8986.3720163]
2.Valer Jurcak, Daisuke Tsuzuki, Ippeita Dan. (2007). 10/20, 10/10, and 10/5 systems revisited: Their validity as relative head-surface-based positioning systems. NeuroImage, 34(4), 1600–1611[10.1016/j.neuroimage.2006.09.024]
3.José Antonio Urigüen, Begonya García-Zapirain. (2015). EEG artifact removal—state-of-the-art and guidelines. Journal of Neural Engineering, 12(3), 031001[10.1088/1741-2560/12/3/031001]
4.Christa Neuper, Michael Wörtz, Gert Pfurtscheller. (2006). ERD/ERS patterns reflecting sensorimotor activation and deactivation. Progress in brain research, 159, 211–222[10.1016/s0079-6123(06)59014-4]
5.Irina I. Goncharova, Dennis J. McFarland, Theresa M. Vaughan, Jonathan R. Wolpaw. (2003). EMG contamination of EEG: spectral and topographical characteristics. Clinical Neurophysiology, 114(9), 1580–1593[10.1016/s1388-2457(03)00093-2]
6.Shravani Sur, VK Sinha. (2009). Event-related potential: An overview. Industrial Psychiatry Journal, 18(1), 70[10.4103/0972-6748.57865]
7.Tom Carlson, José del R. Millán. (2013). Brain-Controlled Wheelchairs: A Robotic Architecture. IEEE Robotics & Automation Magazine, 20(1), 65–73[10.1109/mra.2012.2229936]
8.Ning-Han Liu, Cheng-Yu Chiang, Hsuan-Chin Chu. (2013). Recognizing the Degree of Human Attention Using EEG Signals from Mobile Sensors. Sensors, 13(8), 10273–10286[10.3390/s130810273]
9.Wei‐Long Zheng, Jiayi Zhu, Yong Peng, Bao‐Liang Lu. (2014). EEG-based emotion classification using deep belief networks. , 1–6[10.1109/icme.2014.6890166]
10.Frédéric Roux, Michael Wibral, Harald M. Mohr, Wolf Singer, Peter J. Uhlhaas. (2012). Gamma-Band Activity in Human Prefrontal Cortex Codes for the Number of Relevant Items Maintained in Working Memory. Journal of Neuroscience, 32(36), 12411–12420[10.1523/jneurosci.0421-12.2012]
11.Daniel Szafır, Bilge Mutlu. (2012). Pay attention!. , 11–20[10.1145/2207676.2207679]
12.Gregory A. Light, Lisa E. Williams, Falk Minow, Joyce Sprock, Anthony J. Rissling, Richard F. Sharp, Neal R. Swerdlow, David Braff. (2010). Electroencephalography (EEG) and Event‐Related Potentials (ERPs) with Human Participants. Current Protocols in Neuroscience, 52(1), Unit 6.25.1–24[10.1002/0471142301.ns0625s52]
13.Giorgio Bonmassar. (2002). Motion and Ballistocardiogram Artifact Removal for Interleaved Recording of EEG and EPs during MRI. NeuroImage, 16(4), 1127–1141[10.1006/nimg.2002.1125]
14.Antonio Frisoli, Claudio Loconsole, Daniele Leonardis, Filippo Bannò, Michele Barsotti, Carmelo Chisari, Massimo Bergamasco. (2012). A New Gaze-BCI-Driven Control of an Upper Limb Exoskeleton for Rehabilitation in Real-World Tasks. IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews), 42(6), 1169–1179[10.1109/tsmcc.2012.2226444]
15.Andrew Myrden, Tom Chau. (2015). Effects of user mental state on EEG-BCI performance. Frontiers in Human Neuroscience, 9, 308[10.3389/fnhum.2015.00308]
16.Xiu An, Deping Kuang, Xiaojiao Guo, Yilu Zhao, Lianghua He. (2014). A Deep Learning Method for Classification of EEG Data Based on Motor Imagery. Lecture notes in computer science, 203–210[10.1007/978-3-319-09330-7_25]
17.Minjue Wang, Ian Daly, Brendan Z. Allison, Jing Jin, Yu Zhang, Lanlan Chen, Xingyu Wang. (2014). A new hybrid BCI paradigm based on P300 and SSVEP. Journal of Neuroscience Methods, 244, 16–25[10.1016/j.jneumeth.2014.06.003]
18.Enrique Hortal, Daniel Planelles, Álvaro Costa, Eduardo Iáñez, Andrés Úbeda, José M. Azorín, Eduardo Fernández. (2014). SVM-based Brain–Machine Interface for controlling a robot arm through four mental tasks. Neurocomputing, 151, 116–121[10.1016/j.neucom.2014.09.078]
19.Noriaki Kanayama, Atsushi Sato, Hideki Ohira. (2007). Crossmodal effect with rubber hand illusion and gamma‐band activity. Psychophysiology, 44(3), 392–402[10.1111/j.1469-8986.2007.00511.x]
20.Rafał Kuś, Anna Duszyk-Bogorodzka, Piotr Milanowski, Maciej Łabęcki, Maria Bierzyńska, Zofia Radzikowska, Magdalena Michalska, Jarosław Żygierewicz, Piotr Suffczyński, Piotr Durka. (2013). On the Quantification of SSVEP Frequency Responses in Human EEG in Realistic BCI Conditions. PLoS ONE, 8(10), e77536[10.1371/journal.pone.0077536]
21.Elisa Mira Holz, Johannes Höhne, Pit Staiger-Sälzer, Michael Tangermann, Andrea Kübler. (2013). Brain–computer interface controlled gaming: Evaluation of usability by severely motor restricted end-users. Artificial Intelligence in Medicine, 59(2), 111–120[10.1016/j.artmed.2013.08.001]
22.Kian Bee Ng, Andrew P. Bradley, Ross Cunnington. (2012). Stimulus specificity of a steady-state visual-evoked potential-based brain–computer interface. Journal of Neural Engineering, 9(3), 036008[10.1088/1741-2560/9/3/036008]
23.Sarah N. Carvalho, Thiago Bulhões da Silva Costa, Luisa Fernanda Suárez Uribe, Diogo C. Soriano, Glauco Ferreira Gazel Yared, Luis Cláudius Coradine, Romis Attux. (2015). Comparative analysis of strategies for feature extraction and classification in SSVEP BCIs. Biomedical Signal Processing and Control, 21, 34–42[10.1016/j.bspc.2015.05.008]
24.Gangadhar Garipelli, Ricardo Chavarriaga, José del R. Millán. (2013). Single trial analysis of slow cortical potentials: a study on anticipation related potentials. Journal of Neural Engineering, 10(3), 036014[10.1088/1741-2560/10/3/036014]
25.Siuly Siuly, Yan Li, Peng Wen. (2014). Modified CC-LR algorithm with three diverse feature sets for motor imagery tasks classification in EEG based brain–computer interface. Computer Methods and Programs in Biomedicine, 113(3), 767–780[10.1016/j.cmpb.2013.12.020]
26.Jing Hu, Chunsheng Wang, Min Wu, Yuxiao Du, Yong He, Jinhua She. (2014). Removal of EOG and EMG artifacts from EEG using combination of functional link neural network and adaptive neural fuzzy inference system. Neurocomputing, 151, 278–287[10.1016/j.neucom.2014.09.040]
27.Gerwin Schalk, Jürgen Mellinger. (2010). Brain–Computer Interfaces. , 3–8[10.1007/978-1-84996-092-2_1]
28.Arzu Güneysu Özgür, H. Levent Akın. (2013). An SSVEP based BCI to control a humanoid robot by using portable EEG device. , 2013, 6905–6908[10.1109/embc.2013.6611145]
29.Mahyar Hamedi, Sh‐Hussain Salleh, Alias Mohd Noor, Iman Mohammad-Rezazadeh. (2014). Neural network-based three-class motor imagery classification using time-domain features for BCI applications. 2014 IEEE REGION 10 SYMPOSIUM, 204–207[10.1109/tenconspring.2014.6863026]
30.Gerwin Schalk, Jrgen Mellinger. (2010). A Practical Guide to Brain–Computer Interfacing with BCI2000: General-Purpose Software for Brain-Computer Interface Research, Data Acquisition, Stimulus Presentation, and Brain Monitoring. Medical Entomology and Zoology
31.Brendan Z. Allison, Jing Jin, Yu Zhang, Xingyu Wang. (2014). A four-choice hybrid P300/SSVEP BCI for improved accuracy. Brain-Computer Interfaces, 1(1), 17–26[10.1080/2326263x.2013.869003]
32.Andreas Pinegger, Josef Faller, Sebastian Halder, Selina C. Wriessnegger, Gernot Müller-Putz. (2015). Control or non-control state: that is the question! An asynchronous visual P300-based BCI approach. Journal of Neural Engineering, 12(1), 014001[10.1088/1741-2560/12/1/014001]
33.Pierre Gergondet, Sébastien Druon, Abderrahmane Kheddar, Christoph Hintermüller, Christoph Guger, Mel Slater. (2011). Using brain-computer interface to steer a humanoid robot. , 192–197[10.1109/robio.2011.6181284]
34.Lech Kipiński, Reinhard König, Cezary Sielużycki, Wojciech Kordecki. (2011). Application of modern tests for stationarity to single-trial MEG data. Biological Cybernetics, 105(3-4), 183–195[10.1007/s00422-011-0456-4]
35.Lin Yao, Jianjun Meng, Xinjun Sheng, Dingguo Zhang, Xiangyang Zhu. (2014). A novel calibration and task guidance framework for motor imagery BCI via a tendon vibration induced sensation with kinesthesia illusion. Journal of Neural Engineering, 12(1), 016005[10.1088/1741-2560/12/1/016005]
36.Sumner L. Norman, Mark Dennison, Eric T. Wolbrecht, Steven C. Cramer, Ramesh Srinivasan, David J. Reinkensmeyer. (2016). Movement Anticipation and EEG: Implications for BCI-Contingent Robot Therapy. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 24(8), 911–919[10.1109/tnsre.2016.2528167]
37.Reza Fazel-Rezai, Waqas Ahm. (2011). P300-based Brain-Computer Interface Paradigm Design. InTech eBooks[10.5772/14858]
38.Eric W. Sellers, Yael Arbel, Emanuel Donchin. (2012). BCIs That Use P300 Event-Related Potentials. Oxford University Press eBooks, 215–226[10.1093/acprof:oso/9780195388855.003.0012]
39.Günter Edlinger, Clemens Holzner, Christoph Groenegress, Christoph Guger, Mel Slater. (2009). Goal-Oriented Control with Brain-Computer Interface. Lecture notes in computer science, 732–740[10.1007/978-3-642-02812-0_83]
40.Chih-Yu Chen, Chunwei Wu, Chin‐Teng Lin, Shi‐An Chen. (2014). A novel classification method for motor imagery based on Brain-Computer Interface. , 4099–4102[10.1109/ijcnn.2014.6889535]
41.Rajesh Singla, Arun Khosla, Rameshwar Jha. (2013). Influence of stimuli color on steady-state visual evoked potentials based BCI wheelchair control. Journal of Biomedical Science and Engineering, 06(11), 1050–1055[10.4236/jbise.2013.611131]
42.Kapil D. Katyal, Matthew S. Johannes, Spencer Kellis, Tyson Aflalo, Christian Klaes, T. G. McGee, Matthew P. Para, Ying Shi, Brian Lee, Kelsie Pejsa, Charles Y. Liu, Brock A. Wester, Francesco V. Tenore, James D. Beaty, Alan Ravitz, Richard A. Andersen, Michael P. McLoughlin. (2014). A collaborative BCI approach to autonomous control of a prosthetic limb system. , 1479–1482[10.1109/smc.2014.6974124]
43.Shoji Inoue, Yoshihisa Akiyama, Yasuhiro Izumi, Sgehiro Nishijima. (2008). The Development of BCI Using Alpha Waves for Controlling the Robot Arm. IEICE Transactions on Communications, E91-B(7), 2125–2132[10.1093/ietcom/e91-b.7.2125]
44.Shuvo Kumar Paul, Md. S. Q. Zulkar Nine, Mahady Hasan, M. Ashraful Amin. (2015). Cognitive Task Classificaiton from Wireless EEG. Lecture notes in computer science, 13–22[10.1007/978-3-319-23344-4_2]
45.Günter Edlinger, Christoph Guger. (2011). Social Environments, Mixed Communication and Goal-Oriented Control Application Using a Brain-Computer Interface. Lecture notes in computer science, 545–554[10.1007/978-3-642-21663-3_59]
46.Li-Wei Ko, Shih-Chuan Lin, Meng-Shue Song, Oleksii Komarov. (2014). Developing a few-channel hybrid BCI system by using motor imagery with SSVEP assist. , 4114–4120[10.1109/ijcnn.2014.6889901]
47.William Speier, Jennifer Knall, Nader Pouratian. (2013). Unsuperv&#x00EE;sed training of brain-computer interface systems using exnectation maximization. , 7, 707–710[10.1109/ner.2013.6696032]
48.Maryam Alimardani, Shuichi Nishio, Hiroshi Ishiguro. (2014). The effect of feedback presentation on motor imagery performance during BCI-teleoperation of a humanlike robot. , 403–408[10.1109/biorob.2014.6913810]
49.S. I. Babkin. (1978). Plenary session of the Central Board of the All-Union Medical Engineering Scientific Society. Biomedical Engineering, 12(1), 56–58[10.1007/bf00557027]
50.Wenxuan Li, Mengfan Li, Wei Li. (2015). Independent component analysis-based channel selection to achieve high performance of N200 and P300 classification. , 167, 384–389[10.1109/icci-cc.2015.7259414]
51.Jonathan R. Wolpaw, Niels Birbaumer, Dennis J. McFarland, Gert Pfurtscheller, Theresa M. Vaughan. (2002). Brain–computer interfaces for communication and control. Clinical Neurophysiology, 113(6), 767–791[10.1016/s1388-2457(02)00057-3]
52.Lawrence A. Farwell, Emanuel Donchin. (1988). Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials. Electroencephalography and Clinical Neurophysiology, 70(6), 510–523[10.1016/0013-4694(88)90149-6]
53.Gerwin Schalk, Dennis J. McFarland, Thilo Hinterberger, Niels Birbaumer, Jonathan R. Wolpaw. (2004). BCI2000: A General-Purpose Brain-Computer Interface (BCI) System. IEEE Transactions on Biomedical Engineering, 51(6), 1034–1043[10.1109/tbme.2004.827072]
54.Jonathan R. Wolpaw, Niels Birbaumer, William Heetderks, Dennis J. McFarland, P. Hunter Peckham, Gerwin Schalk, Emanuel Donchin, Louis A. Quatrano, Charles J. Robinson, Theresa M. Vaughan. (2000). Brain-computer interface technology: a review of the first international meeting. IEEE Transactions on Rehabilitation Engineering, 8(2), 164–173[10.1109/tre.2000.847807]
55.Arnaud Delorme, T. J. Sejnowski, Scott Makeig. (2007). Enhanced detection of artifacts in EEG data using higher-order statistics and independent component analysis. NeuroImage, 34(4), 1443–1449[10.1016/j.neuroimage.2006.11.004]
56.Marc W. Howard. (2003). Gamma Oscillations Correlate with Working Memory Load in Humans. Cerebral Cortex, 13(12), 1369–1374[10.1093/cercor/bhg084]
57.Christoph Guger, Shahab Daban, Eric W. Sellers, Clemens Holzner, Gunther Krausz, Roberta Carabalona, Furio Gramatica, Guenter Edlinger. (2009). How many people are able to control a P300-based brain–computer interface (BCI)?. Neuroscience Letters, 462(1), 94–98[10.1016/j.neulet.2009.06.045]
58.Gernot Müller-Putz, G. Pfurtscheller. (2007). Control of an Electrical Prosthesis With an SSVEP-Based BCI. IEEE Transactions on Biomedical Engineering, 55(1), 361–364[10.1109/tbme.2007.897815]
59.George Townsend, Brandon K. LaPallo, Chadwick Boulay, Dean J. Krusienski, G. E. Frye, Christopher K. Hauser, N.E. Schwartz, Theresa M. Vaughan, Jonathan R. Wolpaw, Eric W. Sellers. (2010). A novel P300-based brain–computer interface stimulus presentation paradigm: Moving beyond rows and columns. Clinical Neurophysiology, 121(7), 1109–1120[10.1016/j.clinph.2010.01.030]
60.Ola Friman, Ivan Volosyak, Axel Gräser. (2007). Multiple Channel Detection of Steady-State Visual Evoked Potentials for Brain-Computer Interfaces. IEEE Transactions on Biomedical Engineering, 54(4), 742–750[10.1109/tbme.2006.889160]
61.M. Murugappan, Nagarajan Ramachandran, Yaacob Sazali. (2010). Classification of human emotion from EEG using discrete wavelet transform. Journal of Biomedical Science and Engineering, 03(04), 390–396[10.4236/jbise.2010.34054]
62.Mu Li, Bao‐Liang Lu. (2009). Emotion classification based on gamma-band EEG. , 2009, 1223–1226[10.1109/iembs.2009.5334139]
63.Reza Fazel-Rezai, Brendan Z. Allison, Christoph Guger, Eric W. Sellers, Sonja C. Kleih, Andrea Kübler. (2012). P300 brain computer interface: current challenges and emerging trends. Frontiers in Neuroengineering, 5, 14[10.3389/fneng.2012.00014]
64.Matthieu Duvinage, T. Castermans, Mathieu Petieau, Thomas Hoellinger, Guy Chéron, Thierry Dutoit. (2013). Performance of the Emotiv Epoc headset for P300-based applications. BioMedical Engineering OnLine, 12(1), 56[10.1186/1475-925x-12-56]
65.Guangyu Bin, Xiaorong Gao, Yijun Wang, Bo Hong, Shangkai Gao. (2009). VEP-based brain-computer interfaces: time, frequency, and code modulations [Research Frontier. IEEE Computational Intelligence Magazine, 4(4), 22–26[10.1109/mci.2009.934562]
66.Wei Wang, Jennifer L. Collinger, Mónica A. Pérez, Elizabeth C. Tyler‐Kabara, Leonardo G. Cohen, Niels Birbaumer, Steven W. Brose, Andrew B. Schwartz, Michael L. Boninger, Douglas J. Weber. (2009). Neural Interface Technology for Rehabilitation: Exploiting and Promoting Neuroplasticity. Physical Medicine and Rehabilitation Clinics of North America, 21(1), 157–178[10.1016/j.pmr.2009.07.003]
67.Rajesh C. Panicker, Sadasivan Puthusserypady, Ying Sun. (2011). An Asynchronous P300 BCI With SSVEP-Based Control State Detection. IEEE Transactions on Biomedical Engineering, 58(6), 1781–1788[10.1109/tbme.2011.2116018]
68.Dennis J. McFarland, Jonathan R. Wolpaw. (2008). Brain-Computer Interface Operation of Robotic and Prosthetic Devices. Computer, 41(10), 52–56[10.1109/mc.2008.409]
69.Yu Zhang, Yu Wang, Jing Jin, Xingyu Wang. (2016). Sparse Bayesian Learning for Obtaining Sparsity of EEG Frequency Bands Based Feature Vectors in Motor Imagery Classification. International Journal of Neural Systems, 27(02), 1650032[10.1142/s0129065716500325]
70.Jana Münßinger, Sebastian Halder, Sonja C. Kleih, Adrian Furdea, Valerio Raco, Adi Hösle, Andrea Kübler. (2010). Brain Painting: First Evaluation of a New Brain–Computer Interface Application with ALS-Patients and Healthy Volunteers. Frontiers in Neuroscience, 4, 182[10.3389/fnins.2010.00182]
71.Yue Liu, Xiao Song Jiang, Teng Cao, Feng Wan, Peng Un Mak, Pui‐In Mak, Mang I Vai. (2012). Implementation of SSVEP based BCI with Emotiv EPOC. , 34–37[10.1109/vecims.2012.6273184]
72.Vera Kaiser, Ian Daly, Floriana Pichiorri, Donatella Mattia, Gernot Müller-Putz, Christa Neuper. (2012). Relationship Between Electrical Brain Responses to Motor Imagery and Motor Impairment in Stroke. Stroke, 43(10), 2735–2740[10.1161/strokeaha.112.665489]
73.Andrew Jackson, Chet T. Moritz, J. Mavoori, Timothy H. Lucas, Eberhard E. Fetz. (2006). The neurochip BCI: towards a neural prosthesis for upper limb function. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 14(2), 187–190[10.1109/tnsre.2006.875547]
74.Matthieu Duvinage, T. Castermans, Thierry Dutoit, Mathieu Petieau, Thomas Hoellinger, C. De Saedeleer, Karthik Seetharaman, Guy Chéron. (2012). A P300-based Quantitative Comparison between the Emotiv Epoc Headset and a Medical EEG Device. [10.2316/p.2012.764-071]
75.Ignas Martišius, Robertas Damaševičius. (2016). A Prototype SSVEP Based Real Time BCI Gaming System. Computational Intelligence and Neuroscience, 2016, 1–15[10.1155/2016/3861425]
76.Hoang-Anh The Nguyen, J. Musson, Feng Li, Wei Wang, Guangfan Zhang, Roger Xu, Carl Richey, Tom Schnell, Frederic D. McKenzie, Jiang Li. (2012). EOG artifact removal using a wavelet neural network. Neurocomputing, 97, 374–389[10.1016/j.neucom.2012.04.016]
77.Wei‐Yen Hsu. (2013). SINGLE-TRIAL MOTOR IMAGERY CLASSIFICATION USING ASYMMETRY RATIO, PHASE RELATION, WAVELET-BASED FRACTAL, AND THEIR SELECTED COMBINATION. International Journal of Neural Systems, 23(02), 1350007[10.1142/s012906571350007x]
78.Michael A. Kisley, Zoe M. Cornwell. (2006). Gamma and beta neural activity evoked during a sensory gating paradigm: Effects of auditory, somatosensory and cross-modal stimulation. Clinical Neurophysiology, 117(11), 2549–2563[10.1016/j.clinph.2006.08.003]
79.Damien Coyle, Jhonatan Garcia, Abdul Satti, T.M. McGinnity. (2011). EEG-based continuous control of a game using a 3 channel motor imagery BCI: BCI game. , 1–7[10.1109/ccmb.2011.5952128]
80.Feng Duan, Dongxue Lin, Wenyu Li, Zhao Zhang. (2015). Design of a Multimodal EEG-based Hybrid BCI System with Visual Servo Module. IEEE Transactions on Autonomous Mental Development, 7(4), 332–341[10.1109/tamd.2015.2434951]
81.Marijn van Vliet, Arne Robben, Nikolay Chumerin, Nikolay V. Manyakov, Adrien Combaz, Marc M. Van Hulle. (2012). Designing a brain-computer interface controlled video-game using consumer grade EEG hardware. , 1–6[10.1109/brc.2012.6222186]
82.David E.J. Linden, Nikolaas N. Oosterhof, Christoph Klein, Paul E. Downing. (2011). Mapping brain activation and information during category-specific visual working memory. Journal of Neurophysiology, 107(2), 628–639[10.1152/jn.00105.2011]
83.William Speier, Corey Arnold, Nader Pouratian. (2016). Integrating language models into classifiers for BCI communication: a review. Journal of Neural Engineering, 13(3), 031002[10.1088/1741-2560/13/3/031002]
84.Giuseppe Giglia, Filippo Brighina, Silvia Rizzo, Angela Puma, Serena Indovino, Simona Maccora, Roberta Baschi, Giuseppe Cosentino, Brigida Fierro. (2015). Anodal transcranial direct current stimulation of the right dorsolateral prefrontal cortex enhances memory-guided responses in a visuospatial working memory task.. PubMed, 29(3), 189–93[link]
85.Sandra Mara Torres Müller, Teodiano Bastos-Filho, Mário Sarcinelli-Filho. (2011). Using a SSVEP-BCI to command a robotic wheelchair. , 957–962[10.1109/isie.2011.5984288]
86.Muhammad Noor Fakhruzzaman, Edwin Riksakomara, Hatma Suryotrisongko. (2015). EEG Wave Identification in Human Brain with Emotiv EPOC for Motor Imagery. Procedia Computer Science, 72, 269–276[10.1016/j.procs.2015.12.140]
87.David E Thompson, Stefanie Blain‐Moraes, Jane E. Huggins. (2013). Performance assessment in brain-computer interface-based augmentative and alternative communication. BioMedical Engineering OnLine, 12(1), 43[10.1186/1475-925x-12-43]
88.Md. Kafiul Islam, Amir Rastegarnia, Anh Tuan Nguyen, Zhi Yang. (2014). Artifact characterization and removal for in vivo neural recording. Journal of Neuroscience Methods, 226, 110–123[10.1016/j.jneumeth.2014.01.027]
89.Takashi Kasahara, Kentaro Terasaki, Yuki Ogawa, Junichi Ushiba, Harumichi Aramaki, Yoshihisa Masakado. (2012). The correlation between motor impairments and event-related desynchronization during motor imagery in ALS patients. BMC Neuroscience, 13(1), 66[10.1186/1471-2202-13-66]
90.Vangelis P. Oikonomou, Georgios Liaros, Kostantinos Georgiadis, Elisavet Chatzilari, Katerina Adam, Spiros Nikolopoulos, Ioannis Kompatsiaris. (2016). Comparative Evaluation Of State-Of-The-Art Algorithms For Ssvep-Based Bcis. arXiv (Cornell University)[10.5281/zenodo.581153]
91.Mengfan Li, Wei Li, Huihui Zhou. (2015). Increasing N200 Potentials Via Visual Stimulus Depicting Humanoid Robot Behavior. International Journal of Neural Systems, 26(01), 1550039[10.1142/s0129065715500392]
92.Glenn F. Wilson, Frank T. Fisher. (1995). Cognitive task classification based upon topographic EEG data. Biological Psychology, 40(1-2), 239–250[10.1016/0301-0511(95)05102-3]
93.Patrizio Campisi, Daria La Rocca, Gaetano Scarano. (2012). EEG for Automatic Person Recognition. Computer, 45(7), 87–89[10.1109/mc.2012.233]
94.Feng Zou, Debao Chen, Jiangtao Wang. (2016). An Improved Teaching-Learning-Based Optimization with the Social Character of PSO for Global Optimization. Computational Intelligence and Neuroscience, 2016, 1–10[10.1155/2016/4561507]
95.Tom Carlson, Guillaume Monnard, José del R. Millán. (2011). Vision-Based Shared Control for a BCI Wheelchair. Infoscience (Ecole Polytechnique Fédérale de Lausanne), 13(1), 20–21[link]
96.Song Wen-di, Xiangzhou Wang, Shuhua Zheng, Yingzi Lin. (2014). Mobile Robot Control by BCI Based on Motor Imagery. , 28, 383–387[10.1109/ihmsc.2014.194]
97.Haitao Guo, C.S. Burrus. (2002). Convolution using the undecimated discrete wavelet transform. , 3, 1291–1294[10.1109/icassp.1996.543662]
98.Samuel Boudet, Laurent Peyrodie, Philippe Gallois, Christian Vasseur. (2006). A global approach for automatic artifact removal for standard EEG record. , 2, 5719–5722[10.1109/iembs.2006.259237]
99.Jing Zhao, Wei Li, Xiaoqian Mao, Mengfan Li. (2015). SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots. Journal of Visualized Experiments(105)[10.3791/53558]
100.Manuela Petti, Donatella Mattia, Floriana Pichiorri, Jlenia Toppi, S. Salinari, Fabio Babiloni, Laura Astolfi, Febo Cincotti. (2014). A new descriptor of neuroelectrical activity during BCI-assisted motor imagery-based training in stroke patients. , 29, 1267–1269[10.1109/embc.2014.6943828]
101.(1999). Lecture Notes in Computer Science 1205. Industrial Robot the international journal of robotics research and application, 26(6)[10.1108/ir.1999.04926fae.001]
102.Yousef R. Tabar, Uğur Halıcı. (2016). A novel deep learning approach for classification of EEG motor imagery signals. Journal of Neural Engineering, 14(1), 016003[10.1088/1741-2560/14/1/016003]
103.Chethan Pandarinath, Paul Nuyujukian, Christine H Blabe, Brittany L Sorice, Jad Saab, Francis R. Willett, Leigh R. Hochberg, Krishna V. Shenoy, Jaimie M. Henderson. (2017). High performance communication by people with paralysis using an intracortical brain-computer interface. eLife, 6[10.7554/elife.18554]
104.Md. Kafiul Islam, Amir Rastegarnia, Zhi Yang. (2016). Methods for artifact detection and removal from scalp EEG: A review. Neurophysiologie Clinique, 46(4-5), 287–305[10.1016/j.neucli.2016.07.002]
105.Jasmin Kevrić, Abdülhamit Subaşı. (2016). Comparison of signal decomposition methods in classification of EEG signals for motor-imagery BCI system. Biomedical Signal Processing and Control, 31, 398–406[10.1016/j.bspc.2016.09.007]
106.Md. Kafiul Islam, Amir Rastegarnia, Zhi Yang. (2015). A Wavelet-Based Artifact Reduction From Scalp EEG for Epileptic Seizure Detection. IEEE Journal of Biomedical and Health Informatics, 20(5), 1321–1332[10.1109/jbhi.2015.2457093]
107.Rajdeep Chatterjee, Tathagata Bandyopadhyay. (2016). EEG Based Motor Imagery Classification Using SVM and MLP. , 84–89[10.1109/cine.2016.22]
108.Xiaoqian Mao, Mengfan Li, Wei Li, Linwei Niu, Bin Xian, Ming Zeng, Genshe Chen. (2017). Progress in EEG-Based Brain Robot Interaction Systems. Computational Intelligence and Neuroscience, 2017, 1–25[10.1155/2017/1742862]
109.Reza Fazel-Rezai. (2011). Recent Advances in Brain-Computer Interface Systems. InTech eBooks[10.5772/579]
110.Amir Jalilifard, Ednaldo Brigante Pizzolato, Md. Kafiul Islam. (2016). Emotion classification using single-channel scalp-EEG recording. , 2016, 845–849[10.1109/embc.2016.7590833]
111.Emmanuele Tidoni, Pierre Gergondet, Gabriele Fusco, Abderrahmane Kheddar, Salvatore Maria Aglioti. (2016). The Role of Audio-Visual Feedback in a Thought-Based Control of a Humanoid Robot: A BCI Study in Healthy and Spinal Cord Injured People. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 25(6), 772–781[10.1109/tnsre.2016.2597863]
112.Rahul Kumar Chaurasiya, Narendra D. Londhe, Subhojit Ghosh. (2016). Binary DE-Based Channel Selection and Weighted Ensemble of SVM Classification for Novel Brain–Computer Interface Using Devanagari Script-Based P300 Speller Paradigm. International Journal of Human-Computer Interaction, 32(11), 861–877[10.1080/10447318.2016.1203047]
113.William Speier, Aniket Deshpande, Lucy Cui, Nand Chandravadia, Dustin Roberts, Nader Pouratian. (2017). A comparison of stimulus types in online classification of the P300 speller using language models. PLoS ONE, 12(4), e0175382[10.1371/journal.pone.0175382]
114.Paul Nuyujukian, Jonathan C. Kao, Stephen I. Ryu, Krishna V. Shenoy. (2016). A Nonhuman Primate Brain–Computer Typing Interface. Proceedings of the IEEE, 105(1), 66–72[10.1109/jproc.2016.2586967]
115.Yeou‐Jiunn Chen, Shih-Chung Chen, Ilham Ari Elbaith Zaeni, Chung-Min Wu. (2016). Fuzzy Tracking and Control Algorithm for an SSVEP-Based BCI System. Applied Sciences, 6(10), 270[10.3390/app6100270]
116.Hongtao Wang, Ting Li, Zhenfeng Huang. (2010). Remote control of an electrical car with SSVEP-Based BCI. , 837–840[10.1109/icitis.2010.5689710]
117.De-Shuang Huang, Kyungsook Han, M. Michael Gromiha. (2014). Intelligent Computing in Bioinformatics. Lecture notes in computer science[10.1007/978-3-319-09330-7]
118.Fotis P. Kalaganis, Elisavet Chatzilari, Kostas Georgiadis, Spiros Nikolopoulos, Nikos Laskaris, Ioannis Kompatsiaris. (2017). An Error Aware SSVEP-based BCI. , 775–780[10.1109/cbms.2017.44]
119.Hung-Luen Jian, Kea‐Tiong Tang. (2014). Improving classification accuracy of SSVEP based BCI using RBF SVM with signal quality evaluation. , 302–306[10.1109/ispacs.2014.7024473]
120.Tejaswy Pailla, Werner Jiang, Ben Dichter, Edward F. Chang, Vikash Gilja. (2016). ECoG data analyses to inform closed-loop BCI experiments for speech-based prosthetic applications. , 5713–5716[10.1109/embc.2016.7592024]
121.Nicholas R. Waytowich, Dean J. Krusienski. (2017). Development of an extensible SSVEP-BCI software platform and application to wheelchair control. , 259–532[10.1109/ner.2017.8008406]
122.Qi Li, Kaiyang Shi, Shengyuan Ma, Ning Gao. (2016). Improving classification accuracy of SVM ensemble using random training set for BCI P300-speller. [10.1109/icma.2016.7558978]
123.Aunnoy K Mutasim, Rayhan Sardar Tipu, Mohammad Raihanul Bashar, M. Ashraful Amin. (2017). Video Category Classification Using Wireless EEG. Lecture notes in computer science, 39–48[10.1007/978-3-319-70772-3_4]
124.Christoph Guger, William G. Coon, James Swift, Brendan Z. Allison, Günter Edlinger. (2017). A motor rehabilitation BCI with multi-modal feedback in chronic stroke patients (P5.300). Neurology, 88(16_supplement)[10.1212/wnl.88.16_supplement.p5.300]
125.Chi-Yuan Lin, Wei‐Fan Chiang, Sheng-Chih Yang, Shu‐Yi Huang. (2014). Combining Event-Related Synchronization and Event-Related Desynchronization with Fuzzy C-Means to Classify Motor Imagery-Induced EEG Signals. Lecture notes in electrical engineering, 1039–1045[10.1007/978-3-319-04573-3_127]
126.Qi Li, Shengyuan Ma, Kaiyang Shi, Ning Gao. (2016). Comparing the classification performance of Bayesian linear discriminate analysis (BLDA) and support vector machine (SVM) in BCI P300-speller with familiar face paradigm. , 32, 1476–1481[10.1109/cisp-bmei.2016.7852950]
127.Joshua P. Kulasingham, V. Vibujithan, W. A. R. Kithmini, Y.V. A. C. Kumara, Anjula De Silva. (2016). P300 speller for local languages using Support Vector Machines. , 1–5[10.1109/iciafs.2016.7946525]
128.Anastasios Maronidis, Vangelis P. Oikonomou, Spiros Nikolopoulos, Ioannis Kompatsiaris. (2017). Steady state visual evoked potential detection using Subclass Marginal Fisher Analysis. , 37–41[10.1109/ner.2017.8008286]

Cited By

1.Antora Dev, Nipa Roy, Md. Kafiul Islam, Chiranjeeb Biswas, Helal Uddin Ahmed, Md. Ashraful Amin, Farhana Sarker, Ravi Vaidyanathan, Khondaker A. Mamun. (2022). Exploration of EEG-Based Depression Biomarkers Identification Techniques and Their Applications: A Systematic Review. IEEE Access, 10, 16756–16781[10.1109/access.2022.3146711]
2.Bandiyah Sri Aprillia, Achmad Rizal, Muhammad Arik Geraldy Fauzi. (2024). Grey Level Differences Matrix for Alcoholic EEG Signal Classification. JOIV International Journal on Informatics Visualization, 8(1), 26[10.62527/joiv.8.1.2602]
3.Amir Jalilifard, Dehua Chen, Aunnoy K. Mutasim, M. Raihanul Bashar, Rayhan Sardar Tipu, Ahsan-Ul Kabir Shawon, Nazmus Sakib, M. Ashraful Amin, Md. Kafiul Islam. (2020). Use of spontaneous blinking for application in human authentication. Engineering Science and Technology an International Journal, 23(4), 903–910[10.1016/j.jestch.2020.05.007]
4.Bommala Silpa, Malaya Kumar Hota, Norrima Mokthar. (2024). Suppression of Artifacts from EEG Recordings Using Computational Intelligence. Studies in computational intelligence, 261–279[10.1007/978-981-99-8853-2_17]
5.Lavinia Ferariu, Corina Cimpanu, Tiberius Dumitriu, Florina Ungureanu. (2018). EEG Multi-Objective Feature Selection Using Temporal Extension. , 777, 105–110[10.1109/iccp.2018.8516613]
6.Aunnoy K. Mutasim, M. Raihanul Bashar, Rayhan Sardar Tipu, Md. Kafiul Islam, M. Ashraful Amin. (2018). Effect of Artefact Removal Techniques on EEG Signals for Video Category Classification. , 9250, 3513–3518[10.1109/icpr.2018.8545416]
7.(2021). Implementation of Web Scraping on News Sites Using the Supervised Learning Method. İlköğretim Online, 20(3)[10.17051/ilkonline.2021.03.43]
8.Oana Andreea Rușanu. (2021). Advanced LabVIEW Applications Aimed for the Acquisition, Processing and Classification of the Electroencephalographic Signals Used in a Brain-Computer Interface System. Preprints.org[10.20944/preprints202106.0016.v1]
9.Oana Andreea Rușanu. (2022). A LabVIEW Instrument Aimed for the Research on Brain-Computer Interface by Enabling the Acquisition, Processing, and the Neural Networks based Classification of the Raw EEG Signal Detected by the Embedded NeuroSky Biosensor. Preprints.org[10.20944/preprints202106.0016.v2]
10.Eugenio Martínez, Rosario Baltazar, Carlos A. Reyes-García, Miguel Casillas, Martha-Alicia Rocha, Socorro Gutierrez, M. Del Consuelo Martínez Wbaldo. (2020). Multiagent System as Support for the Diagnosis of Language Impairments Using BCI-Neurofeedback: Preliminary Study. Smart innovation, systems and technologies, 235–243[10.1007/978-981-15-5764-4_21]

← All publications

CCDS Authors

Md Kafiul Islam, PhD

Director, BISPL Wing

Professor

Dept. of Electrical and Electronic Engineering

Independent University, Bangladesh (IUB)

M Ashraful Amin, PhD

Founder Director, CCDS
Director, AI/ML, HCI & DS Wings

Professor

Department of Computer Science and Engineering

Independent University, Bangladesh

Research Interests

Machine Learning, Cognitive & Vision Science, Cybernetics, Surveillance & Security, ICT in Education, Health, & Agriculture, Human-Computer Interaction, Internet of Things, Robotics

References

1.Tzyy‐Ping Jung, Scott Makeig, Colin Humphries, Te‐Won Lee, Martin J. McKeown, Vicente J. Iragui, Terrence J. Sejnowski. (2000). Removing electroencephalographic artifacts by blind source separation. Psychophysiology, 37(2), 163–178[10.1111/1469-8986.3720163]

2.Valer Jurcak, Daisuke Tsuzuki, Ippeita Dan. (2007). 10/20, 10/10, and 10/5 systems revisited: Their validity as relative head-surface-based positioning systems. NeuroImage, 34(4), 1600–1611[10.1016/j.neuroimage.2006.09.024]

3.José Antonio Urigüen, Begonya García-Zapirain. (2015). EEG artifact removal—state-of-the-art and guidelines. Journal of Neural Engineering, 12(3), 031001[10.1088/1741-2560/12/3/031001]

4.Christa Neuper, Michael Wörtz, Gert Pfurtscheller. (2006). ERD/ERS patterns reflecting sensorimotor activation and deactivation. Progress in brain research, 159, 211–222[10.1016/s0079-6123(06)59014-4]

5.Irina I. Goncharova, Dennis J. McFarland, Theresa M. Vaughan, Jonathan R. Wolpaw. (2003). EMG contamination of EEG: spectral and topographical characteristics. Clinical Neurophysiology, 114(9), 1580–1593[10.1016/s1388-2457(03)00093-2]

6.Shravani Sur, VK Sinha. (2009). Event-related potential: An overview. Industrial Psychiatry Journal, 18(1), 70[10.4103/0972-6748.57865]

7.Tom Carlson, José del R. Millán. (2013). Brain-Controlled Wheelchairs: A Robotic Architecture. IEEE Robotics & Automation Magazine, 20(1), 65–73[10.1109/mra.2012.2229936]

8.Ning-Han Liu, Cheng-Yu Chiang, Hsuan-Chin Chu. (2013). Recognizing the Degree of Human Attention Using EEG Signals from Mobile Sensors. Sensors, 13(8), 10273–10286[10.3390/s130810273]

9.Wei‐Long Zheng, Jiayi Zhu, Yong Peng, Bao‐Liang Lu. (2014). EEG-based emotion classification using deep belief networks. , 1–6[10.1109/icme.2014.6890166]

10.Frédéric Roux, Michael Wibral, Harald M. Mohr, Wolf Singer, Peter J. Uhlhaas. (2012). Gamma-Band Activity in Human Prefrontal Cortex Codes for the Number of Relevant Items Maintained in Working Memory. Journal of Neuroscience, 32(36), 12411–12420[10.1523/jneurosci.0421-12.2012]

11.Daniel Szafır, Bilge Mutlu. (2012). Pay attention!. , 11–20[10.1145/2207676.2207679]

12.Gregory A. Light, Lisa E. Williams, Falk Minow, Joyce Sprock, Anthony J. Rissling, Richard F. Sharp, Neal R. Swerdlow, David Braff. (2010). Electroencephalography (EEG) and Event‐Related Potentials (ERPs) with Human Participants. Current Protocols in Neuroscience, 52(1), Unit 6.25.1–24[10.1002/0471142301.ns0625s52]

13.Giorgio Bonmassar. (2002). Motion and Ballistocardiogram Artifact Removal for Interleaved Recording of EEG and EPs during MRI. NeuroImage, 16(4), 1127–1141[10.1006/nimg.2002.1125]

14.Antonio Frisoli, Claudio Loconsole, Daniele Leonardis, Filippo Bannò, Michele Barsotti, Carmelo Chisari, Massimo Bergamasco. (2012). A New Gaze-BCI-Driven Control of an Upper Limb Exoskeleton for Rehabilitation in Real-World Tasks. IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews), 42(6), 1169–1179[10.1109/tsmcc.2012.2226444]

15.Andrew Myrden, Tom Chau. (2015). Effects of user mental state on EEG-BCI performance. Frontiers in Human Neuroscience, 9, 308[10.3389/fnhum.2015.00308]

16.Xiu An, Deping Kuang, Xiaojiao Guo, Yilu Zhao, Lianghua He. (2014). A Deep Learning Method for Classification of EEG Data Based on Motor Imagery. Lecture notes in computer science, 203–210[10.1007/978-3-319-09330-7_25]

17.Minjue Wang, Ian Daly, Brendan Z. Allison, Jing Jin, Yu Zhang, Lanlan Chen, Xingyu Wang. (2014). A new hybrid BCI paradigm based on P300 and SSVEP. Journal of Neuroscience Methods, 244, 16–25[10.1016/j.jneumeth.2014.06.003]

18.Enrique Hortal, Daniel Planelles, Álvaro Costa, Eduardo Iáñez, Andrés Úbeda, José M. Azorín, Eduardo Fernández. (2014). SVM-based Brain–Machine Interface for controlling a robot arm through four mental tasks. Neurocomputing, 151, 116–121[10.1016/j.neucom.2014.09.078]

19.Noriaki Kanayama, Atsushi Sato, Hideki Ohira. (2007). Crossmodal effect with rubber hand illusion and gamma‐band activity. Psychophysiology, 44(3), 392–402[10.1111/j.1469-8986.2007.00511.x]

20.Rafał Kuś, Anna Duszyk-Bogorodzka, Piotr Milanowski, Maciej Łabęcki, Maria Bierzyńska, Zofia Radzikowska, Magdalena Michalska, Jarosław Żygierewicz, Piotr Suffczyński, Piotr Durka. (2013). On the Quantification of SSVEP Frequency Responses in Human EEG in Realistic BCI Conditions. PLoS ONE, 8(10), e77536[10.1371/journal.pone.0077536]

21.Elisa Mira Holz, Johannes Höhne, Pit Staiger-Sälzer, Michael Tangermann, Andrea Kübler. (2013). Brain–computer interface controlled gaming: Evaluation of usability by severely motor restricted end-users. Artificial Intelligence in Medicine, 59(2), 111–120[10.1016/j.artmed.2013.08.001]

22.Kian Bee Ng, Andrew P. Bradley, Ross Cunnington. (2012). Stimulus specificity of a steady-state visual-evoked potential-based brain–computer interface. Journal of Neural Engineering, 9(3), 036008[10.1088/1741-2560/9/3/036008]

23.Sarah N. Carvalho, Thiago Bulhões da Silva Costa, Luisa Fernanda Suárez Uribe, Diogo C. Soriano, Glauco Ferreira Gazel Yared, Luis Cláudius Coradine, Romis Attux. (2015). Comparative analysis of strategies for feature extraction and classification in SSVEP BCIs. Biomedical Signal Processing and Control, 21, 34–42[10.1016/j.bspc.2015.05.008]

24.Gangadhar Garipelli, Ricardo Chavarriaga, José del R. Millán. (2013). Single trial analysis of slow cortical potentials: a study on anticipation related potentials. Journal of Neural Engineering, 10(3), 036014[10.1088/1741-2560/10/3/036014]

25.Siuly Siuly, Yan Li, Peng Wen. (2014). Modified CC-LR algorithm with three diverse feature sets for motor imagery tasks classification in EEG based brain–computer interface. Computer Methods and Programs in Biomedicine, 113(3), 767–780[10.1016/j.cmpb.2013.12.020]

26.Jing Hu, Chunsheng Wang, Min Wu, Yuxiao Du, Yong He, Jinhua She. (2014). Removal of EOG and EMG artifacts from EEG using combination of functional link neural network and adaptive neural fuzzy inference system. Neurocomputing, 151, 278–287[10.1016/j.neucom.2014.09.040]

27.Gerwin Schalk, Jürgen Mellinger. (2010). Brain–Computer Interfaces. , 3–8[10.1007/978-1-84996-092-2_1]

28.Arzu Güneysu Özgür, H. Levent Akın. (2013). An SSVEP based BCI to control a humanoid robot by using portable EEG device. , 2013, 6905–6908[10.1109/embc.2013.6611145]

29.Mahyar Hamedi, Sh‐Hussain Salleh, Alias Mohd Noor, Iman Mohammad-Rezazadeh. (2014). Neural network-based three-class motor imagery classification using time-domain features for BCI applications. 2014 IEEE REGION 10 SYMPOSIUM, 204–207[10.1109/tenconspring.2014.6863026]

30.Gerwin Schalk, Jrgen Mellinger. (2010). A Practical Guide to Brain–Computer Interfacing with BCI2000: General-Purpose Software for Brain-Computer Interface Research, Data Acquisition, Stimulus Presentation, and Brain Monitoring. Medical Entomology and Zoology

31.Brendan Z. Allison, Jing Jin, Yu Zhang, Xingyu Wang. (2014). A four-choice hybrid P300/SSVEP BCI for improved accuracy. Brain-Computer Interfaces, 1(1), 17–26[10.1080/2326263x.2013.869003]

32.Andreas Pinegger, Josef Faller, Sebastian Halder, Selina C. Wriessnegger, Gernot Müller-Putz. (2015). Control or non-control state: that is the question! An asynchronous visual P300-based BCI approach. Journal of Neural Engineering, 12(1), 014001[10.1088/1741-2560/12/1/014001]

33.Pierre Gergondet, Sébastien Druon, Abderrahmane Kheddar, Christoph Hintermüller, Christoph Guger, Mel Slater. (2011). Using brain-computer interface to steer a humanoid robot. , 192–197[10.1109/robio.2011.6181284]

34.Lech Kipiński, Reinhard König, Cezary Sielużycki, Wojciech Kordecki. (2011). Application of modern tests for stationarity to single-trial MEG data. Biological Cybernetics, 105(3-4), 183–195[10.1007/s00422-011-0456-4]

35.Lin Yao, Jianjun Meng, Xinjun Sheng, Dingguo Zhang, Xiangyang Zhu. (2014). A novel calibration and task guidance framework for motor imagery BCI via a tendon vibration induced sensation with kinesthesia illusion. Journal of Neural Engineering, 12(1), 016005[10.1088/1741-2560/12/1/016005]

36.Sumner L. Norman, Mark Dennison, Eric T. Wolbrecht, Steven C. Cramer, Ramesh Srinivasan, David J. Reinkensmeyer. (2016). Movement Anticipation and EEG: Implications for BCI-Contingent Robot Therapy. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 24(8), 911–919[10.1109/tnsre.2016.2528167]

37.Reza Fazel-Rezai, Waqas Ahm. (2011). P300-based Brain-Computer Interface Paradigm Design. InTech eBooks[10.5772/14858]

38.Eric W. Sellers, Yael Arbel, Emanuel Donchin. (2012). BCIs That Use P300 Event-Related Potentials. Oxford University Press eBooks, 215–226[10.1093/acprof:oso/9780195388855.003.0012]

39.Günter Edlinger, Clemens Holzner, Christoph Groenegress, Christoph Guger, Mel Slater. (2009). Goal-Oriented Control with Brain-Computer Interface. Lecture notes in computer science, 732–740[10.1007/978-3-642-02812-0_83]

40.Chih-Yu Chen, Chunwei Wu, Chin‐Teng Lin, Shi‐An Chen. (2014). A novel classification method for motor imagery based on Brain-Computer Interface. , 4099–4102[10.1109/ijcnn.2014.6889535]

41.Rajesh Singla, Arun Khosla, Rameshwar Jha. (2013). Influence of stimuli color on steady-state visual evoked potentials based BCI wheelchair control. Journal of Biomedical Science and Engineering, 06(11), 1050–1055[10.4236/jbise.2013.611131]

42.Kapil D. Katyal, Matthew S. Johannes, Spencer Kellis, Tyson Aflalo, Christian Klaes, T. G. McGee, Matthew P. Para, Ying Shi, Brian Lee, Kelsie Pejsa, Charles Y. Liu, Brock A. Wester, Francesco V. Tenore, James D. Beaty, Alan Ravitz, Richard A. Andersen, Michael P. McLoughlin. (2014). A collaborative BCI approach to autonomous control of a prosthetic limb system. , 1479–1482[10.1109/smc.2014.6974124]

43.Shoji Inoue, Yoshihisa Akiyama, Yasuhiro Izumi, Sgehiro Nishijima. (2008). The Development of BCI Using Alpha Waves for Controlling the Robot Arm. IEICE Transactions on Communications, E91-B(7), 2125–2132[10.1093/ietcom/e91-b.7.2125]

44.Shuvo Kumar Paul, Md. S. Q. Zulkar Nine, Mahady Hasan, M. Ashraful Amin. (2015). Cognitive Task Classificaiton from Wireless EEG. Lecture notes in computer science, 13–22[10.1007/978-3-319-23344-4_2]

45.Günter Edlinger, Christoph Guger. (2011). Social Environments, Mixed Communication and Goal-Oriented Control Application Using a Brain-Computer Interface. Lecture notes in computer science, 545–554[10.1007/978-3-642-21663-3_59]

46.Li-Wei Ko, Shih-Chuan Lin, Meng-Shue Song, Oleksii Komarov. (2014). Developing a few-channel hybrid BCI system by using motor imagery with SSVEP assist. , 4114–4120[10.1109/ijcnn.2014.6889901]

47.William Speier, Jennifer Knall, Nader Pouratian. (2013). Unsuperv&#x00EE;sed training of brain-computer interface systems using exnectation maximization. , 7, 707–710[10.1109/ner.2013.6696032]

48.Maryam Alimardani, Shuichi Nishio, Hiroshi Ishiguro. (2014). The effect of feedback presentation on motor imagery performance during BCI-teleoperation of a humanlike robot. , 403–408[10.1109/biorob.2014.6913810]

49.S. I. Babkin. (1978). Plenary session of the Central Board of the All-Union Medical Engineering Scientific Society. Biomedical Engineering, 12(1), 56–58[10.1007/bf00557027]

50.Wenxuan Li, Mengfan Li, Wei Li. (2015). Independent component analysis-based channel selection to achieve high performance of N200 and P300 classification. , 167, 384–389[10.1109/icci-cc.2015.7259414]

51.Jonathan R. Wolpaw, Niels Birbaumer, Dennis J. McFarland, Gert Pfurtscheller, Theresa M. Vaughan. (2002). Brain–computer interfaces for communication and control. Clinical Neurophysiology, 113(6), 767–791[10.1016/s1388-2457(02)00057-3]

52.Lawrence A. Farwell, Emanuel Donchin. (1988). Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials. Electroencephalography and Clinical Neurophysiology, 70(6), 510–523[10.1016/0013-4694(88)90149-6]

53.Gerwin Schalk, Dennis J. McFarland, Thilo Hinterberger, Niels Birbaumer, Jonathan R. Wolpaw. (2004). BCI2000: A General-Purpose Brain-Computer Interface (BCI) System. IEEE Transactions on Biomedical Engineering, 51(6), 1034–1043[10.1109/tbme.2004.827072]

54.Jonathan R. Wolpaw, Niels Birbaumer, William Heetderks, Dennis J. McFarland, P. Hunter Peckham, Gerwin Schalk, Emanuel Donchin, Louis A. Quatrano, Charles J. Robinson, Theresa M. Vaughan. (2000). Brain-computer interface technology: a review of the first international meeting. IEEE Transactions on Rehabilitation Engineering, 8(2), 164–173[10.1109/tre.2000.847807]

55.Arnaud Delorme, T. J. Sejnowski, Scott Makeig. (2007). Enhanced detection of artifacts in EEG data using higher-order statistics and independent component analysis. NeuroImage, 34(4), 1443–1449[10.1016/j.neuroimage.2006.11.004]

56.Marc W. Howard. (2003). Gamma Oscillations Correlate with Working Memory Load in Humans. Cerebral Cortex, 13(12), 1369–1374[10.1093/cercor/bhg084]

57.Christoph Guger, Shahab Daban, Eric W. Sellers, Clemens Holzner, Gunther Krausz, Roberta Carabalona, Furio Gramatica, Guenter Edlinger. (2009). How many people are able to control a P300-based brain–computer interface (BCI)?. Neuroscience Letters, 462(1), 94–98[10.1016/j.neulet.2009.06.045]

58.Gernot Müller-Putz, G. Pfurtscheller. (2007). Control of an Electrical Prosthesis With an SSVEP-Based BCI. IEEE Transactions on Biomedical Engineering, 55(1), 361–364[10.1109/tbme.2007.897815]

59.George Townsend, Brandon K. LaPallo, Chadwick Boulay, Dean J. Krusienski, G. E. Frye, Christopher K. Hauser, N.E. Schwartz, Theresa M. Vaughan, Jonathan R. Wolpaw, Eric W. Sellers. (2010). A novel P300-based brain–computer interface stimulus presentation paradigm: Moving beyond rows and columns. Clinical Neurophysiology, 121(7), 1109–1120[10.1016/j.clinph.2010.01.030]

60.Ola Friman, Ivan Volosyak, Axel Gräser. (2007). Multiple Channel Detection of Steady-State Visual Evoked Potentials for Brain-Computer Interfaces. IEEE Transactions on Biomedical Engineering, 54(4), 742–750[10.1109/tbme.2006.889160]

61.M. Murugappan, Nagarajan Ramachandran, Yaacob Sazali. (2010). Classification of human emotion from EEG using discrete wavelet transform. Journal of Biomedical Science and Engineering, 03(04), 390–396[10.4236/jbise.2010.34054]

62.Mu Li, Bao‐Liang Lu. (2009). Emotion classification based on gamma-band EEG. , 2009, 1223–1226[10.1109/iembs.2009.5334139]

63.Reza Fazel-Rezai, Brendan Z. Allison, Christoph Guger, Eric W. Sellers, Sonja C. Kleih, Andrea Kübler. (2012). P300 brain computer interface: current challenges and emerging trends. Frontiers in Neuroengineering, 5, 14[10.3389/fneng.2012.00014]

64.Matthieu Duvinage, T. Castermans, Mathieu Petieau, Thomas Hoellinger, Guy Chéron, Thierry Dutoit. (2013). Performance of the Emotiv Epoc headset for P300-based applications. BioMedical Engineering OnLine, 12(1), 56[10.1186/1475-925x-12-56]

65.Guangyu Bin, Xiaorong Gao, Yijun Wang, Bo Hong, Shangkai Gao. (2009). VEP-based brain-computer interfaces: time, frequency, and code modulations [Research Frontier. IEEE Computational Intelligence Magazine, 4(4), 22–26[10.1109/mci.2009.934562]

66.Wei Wang, Jennifer L. Collinger, Mónica A. Pérez, Elizabeth C. Tyler‐Kabara, Leonardo G. Cohen, Niels Birbaumer, Steven W. Brose, Andrew B. Schwartz, Michael L. Boninger, Douglas J. Weber. (2009). Neural Interface Technology for Rehabilitation: Exploiting and Promoting Neuroplasticity. Physical Medicine and Rehabilitation Clinics of North America, 21(1), 157–178[10.1016/j.pmr.2009.07.003]

67.Rajesh C. Panicker, Sadasivan Puthusserypady, Ying Sun. (2011). An Asynchronous P300 BCI With SSVEP-Based Control State Detection. IEEE Transactions on Biomedical Engineering, 58(6), 1781–1788[10.1109/tbme.2011.2116018]

68.Dennis J. McFarland, Jonathan R. Wolpaw. (2008). Brain-Computer Interface Operation of Robotic and Prosthetic Devices. Computer, 41(10), 52–56[10.1109/mc.2008.409]

69.Yu Zhang, Yu Wang, Jing Jin, Xingyu Wang. (2016). Sparse Bayesian Learning for Obtaining Sparsity of EEG Frequency Bands Based Feature Vectors in Motor Imagery Classification. International Journal of Neural Systems, 27(02), 1650032[10.1142/s0129065716500325]

70.Jana Münßinger, Sebastian Halder, Sonja C. Kleih, Adrian Furdea, Valerio Raco, Adi Hösle, Andrea Kübler. (2010). Brain Painting: First Evaluation of a New Brain–Computer Interface Application with ALS-Patients and Healthy Volunteers. Frontiers in Neuroscience, 4, 182[10.3389/fnins.2010.00182]

71.Yue Liu, Xiao Song Jiang, Teng Cao, Feng Wan, Peng Un Mak, Pui‐In Mak, Mang I Vai. (2012). Implementation of SSVEP based BCI with Emotiv EPOC. , 34–37[10.1109/vecims.2012.6273184]

72.Vera Kaiser, Ian Daly, Floriana Pichiorri, Donatella Mattia, Gernot Müller-Putz, Christa Neuper. (2012). Relationship Between Electrical Brain Responses to Motor Imagery and Motor Impairment in Stroke. Stroke, 43(10), 2735–2740[10.1161/strokeaha.112.665489]

73.Andrew Jackson, Chet T. Moritz, J. Mavoori, Timothy H. Lucas, Eberhard E. Fetz. (2006). The neurochip BCI: towards a neural prosthesis for upper limb function. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 14(2), 187–190[10.1109/tnsre.2006.875547]

74.Matthieu Duvinage, T. Castermans, Thierry Dutoit, Mathieu Petieau, Thomas Hoellinger, C. De Saedeleer, Karthik Seetharaman, Guy Chéron. (2012). A P300-based Quantitative Comparison between the Emotiv Epoc Headset and a Medical EEG Device. [10.2316/p.2012.764-071]

75.Ignas Martišius, Robertas Damaševičius. (2016). A Prototype SSVEP Based Real Time BCI Gaming System. Computational Intelligence and Neuroscience, 2016, 1–15[10.1155/2016/3861425]

76.Hoang-Anh The Nguyen, J. Musson, Feng Li, Wei Wang, Guangfan Zhang, Roger Xu, Carl Richey, Tom Schnell, Frederic D. McKenzie, Jiang Li. (2012). EOG artifact removal using a wavelet neural network. Neurocomputing, 97, 374–389[10.1016/j.neucom.2012.04.016]

77.Wei‐Yen Hsu. (2013). SINGLE-TRIAL MOTOR IMAGERY CLASSIFICATION USING ASYMMETRY RATIO, PHASE RELATION, WAVELET-BASED FRACTAL, AND THEIR SELECTED COMBINATION. International Journal of Neural Systems, 23(02), 1350007[10.1142/s012906571350007x]

78.Michael A. Kisley, Zoe M. Cornwell. (2006). Gamma and beta neural activity evoked during a sensory gating paradigm: Effects of auditory, somatosensory and cross-modal stimulation. Clinical Neurophysiology, 117(11), 2549–2563[10.1016/j.clinph.2006.08.003]

79.Damien Coyle, Jhonatan Garcia, Abdul Satti, T.M. McGinnity. (2011). EEG-based continuous control of a game using a 3 channel motor imagery BCI: BCI game. , 1–7[10.1109/ccmb.2011.5952128]

80.Feng Duan, Dongxue Lin, Wenyu Li, Zhao Zhang. (2015). Design of a Multimodal EEG-based Hybrid BCI System with Visual Servo Module. IEEE Transactions on Autonomous Mental Development, 7(4), 332–341[10.1109/tamd.2015.2434951]

81.Marijn van Vliet, Arne Robben, Nikolay Chumerin, Nikolay V. Manyakov, Adrien Combaz, Marc M. Van Hulle. (2012). Designing a brain-computer interface controlled video-game using consumer grade EEG hardware. , 1–6[10.1109/brc.2012.6222186]

82.David E.J. Linden, Nikolaas N. Oosterhof, Christoph Klein, Paul E. Downing. (2011). Mapping brain activation and information during category-specific visual working memory. Journal of Neurophysiology, 107(2), 628–639[10.1152/jn.00105.2011]

83.William Speier, Corey Arnold, Nader Pouratian. (2016). Integrating language models into classifiers for BCI communication: a review. Journal of Neural Engineering, 13(3), 031002[10.1088/1741-2560/13/3/031002]

84.Giuseppe Giglia, Filippo Brighina, Silvia Rizzo, Angela Puma, Serena Indovino, Simona Maccora, Roberta Baschi, Giuseppe Cosentino, Brigida Fierro. (2015). Anodal transcranial direct current stimulation of the right dorsolateral prefrontal cortex enhances memory-guided responses in a visuospatial working memory task.. PubMed, 29(3), 189–93[link]

85.Sandra Mara Torres Müller, Teodiano Bastos-Filho, Mário Sarcinelli-Filho. (2011). Using a SSVEP-BCI to command a robotic wheelchair. , 957–962[10.1109/isie.2011.5984288]

86.Muhammad Noor Fakhruzzaman, Edwin Riksakomara, Hatma Suryotrisongko. (2015). EEG Wave Identification in Human Brain with Emotiv EPOC for Motor Imagery. Procedia Computer Science, 72, 269–276[10.1016/j.procs.2015.12.140]

87.David E Thompson, Stefanie Blain‐Moraes, Jane E. Huggins. (2013). Performance assessment in brain-computer interface-based augmentative and alternative communication. BioMedical Engineering OnLine, 12(1), 43[10.1186/1475-925x-12-43]

88.Md. Kafiul Islam, Amir Rastegarnia, Anh Tuan Nguyen, Zhi Yang. (2014). Artifact characterization and removal for in vivo neural recording. Journal of Neuroscience Methods, 226, 110–123[10.1016/j.jneumeth.2014.01.027]

89.Takashi Kasahara, Kentaro Terasaki, Yuki Ogawa, Junichi Ushiba, Harumichi Aramaki, Yoshihisa Masakado. (2012). The correlation between motor impairments and event-related desynchronization during motor imagery in ALS patients. BMC Neuroscience, 13(1), 66[10.1186/1471-2202-13-66]

90.Vangelis P. Oikonomou, Georgios Liaros, Kostantinos Georgiadis, Elisavet Chatzilari, Katerina Adam, Spiros Nikolopoulos, Ioannis Kompatsiaris. (2016). Comparative Evaluation Of State-Of-The-Art Algorithms For Ssvep-Based Bcis. arXiv (Cornell University)[10.5281/zenodo.581153]

91.Mengfan Li, Wei Li, Huihui Zhou. (2015). Increasing N200 Potentials Via Visual Stimulus Depicting Humanoid Robot Behavior. International Journal of Neural Systems, 26(01), 1550039[10.1142/s0129065715500392]

92.Glenn F. Wilson, Frank T. Fisher. (1995). Cognitive task classification based upon topographic EEG data. Biological Psychology, 40(1-2), 239–250[10.1016/0301-0511(95)05102-3]

93.Patrizio Campisi, Daria La Rocca, Gaetano Scarano. (2012). EEG for Automatic Person Recognition. Computer, 45(7), 87–89[10.1109/mc.2012.233]

94.Feng Zou, Debao Chen, Jiangtao Wang. (2016). An Improved Teaching-Learning-Based Optimization with the Social Character of PSO for Global Optimization. Computational Intelligence and Neuroscience, 2016, 1–10[10.1155/2016/4561507]

95.Tom Carlson, Guillaume Monnard, José del R. Millán. (2011). Vision-Based Shared Control for a BCI Wheelchair. Infoscience (Ecole Polytechnique Fédérale de Lausanne), 13(1), 20–21[link]

96.Song Wen-di, Xiangzhou Wang, Shuhua Zheng, Yingzi Lin. (2014). Mobile Robot Control by BCI Based on Motor Imagery. , 28, 383–387[10.1109/ihmsc.2014.194]

97.Haitao Guo, C.S. Burrus. (2002). Convolution using the undecimated discrete wavelet transform. , 3, 1291–1294[10.1109/icassp.1996.543662]

98.Samuel Boudet, Laurent Peyrodie, Philippe Gallois, Christian Vasseur. (2006). A global approach for automatic artifact removal for standard EEG record. , 2, 5719–5722[10.1109/iembs.2006.259237]

99.Jing Zhao, Wei Li, Xiaoqian Mao, Mengfan Li. (2015). SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots. Journal of Visualized Experiments(105)[10.3791/53558]

100.Manuela Petti, Donatella Mattia, Floriana Pichiorri, Jlenia Toppi, S. Salinari, Fabio Babiloni, Laura Astolfi, Febo Cincotti. (2014). A new descriptor of neuroelectrical activity during BCI-assisted motor imagery-based training in stroke patients. , 29, 1267–1269[10.1109/embc.2014.6943828]

101.(1999). Lecture Notes in Computer Science 1205. Industrial Robot the international journal of robotics research and application, 26(6)[10.1108/ir.1999.04926fae.001]

102.Yousef R. Tabar, Uğur Halıcı. (2016). A novel deep learning approach for classification of EEG motor imagery signals. Journal of Neural Engineering, 14(1), 016003[10.1088/1741-2560/14/1/016003]

103.Chethan Pandarinath, Paul Nuyujukian, Christine H Blabe, Brittany L Sorice, Jad Saab, Francis R. Willett, Leigh R. Hochberg, Krishna V. Shenoy, Jaimie M. Henderson. (2017). High performance communication by people with paralysis using an intracortical brain-computer interface. eLife, 6[10.7554/elife.18554]

104.Md. Kafiul Islam, Amir Rastegarnia, Zhi Yang. (2016). Methods for artifact detection and removal from scalp EEG: A review. Neurophysiologie Clinique, 46(4-5), 287–305[10.1016/j.neucli.2016.07.002]

105.Jasmin Kevrić, Abdülhamit Subaşı. (2016). Comparison of signal decomposition methods in classification of EEG signals for motor-imagery BCI system. Biomedical Signal Processing and Control, 31, 398–406[10.1016/j.bspc.2016.09.007]

106.Md. Kafiul Islam, Amir Rastegarnia, Zhi Yang. (2015). A Wavelet-Based Artifact Reduction From Scalp EEG for Epileptic Seizure Detection. IEEE Journal of Biomedical and Health Informatics, 20(5), 1321–1332[10.1109/jbhi.2015.2457093]

107.Rajdeep Chatterjee, Tathagata Bandyopadhyay. (2016). EEG Based Motor Imagery Classification Using SVM and MLP. , 84–89[10.1109/cine.2016.22]

108.Xiaoqian Mao, Mengfan Li, Wei Li, Linwei Niu, Bin Xian, Ming Zeng, Genshe Chen. (2017). Progress in EEG-Based Brain Robot Interaction Systems. Computational Intelligence and Neuroscience, 2017, 1–25[10.1155/2017/1742862]

109.Reza Fazel-Rezai. (2011). Recent Advances in Brain-Computer Interface Systems. InTech eBooks[10.5772/579]

110.Amir Jalilifard, Ednaldo Brigante Pizzolato, Md. Kafiul Islam. (2016). Emotion classification using single-channel scalp-EEG recording. , 2016, 845–849[10.1109/embc.2016.7590833]

111.Emmanuele Tidoni, Pierre Gergondet, Gabriele Fusco, Abderrahmane Kheddar, Salvatore Maria Aglioti. (2016). The Role of Audio-Visual Feedback in a Thought-Based Control of a Humanoid Robot: A BCI Study in Healthy and Spinal Cord Injured People. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 25(6), 772–781[10.1109/tnsre.2016.2597863]

112.Rahul Kumar Chaurasiya, Narendra D. Londhe, Subhojit Ghosh. (2016). Binary DE-Based Channel Selection and Weighted Ensemble of SVM Classification for Novel Brain–Computer Interface Using Devanagari Script-Based P300 Speller Paradigm. International Journal of Human-Computer Interaction, 32(11), 861–877[10.1080/10447318.2016.1203047]

113.William Speier, Aniket Deshpande, Lucy Cui, Nand Chandravadia, Dustin Roberts, Nader Pouratian. (2017). A comparison of stimulus types in online classification of the P300 speller using language models. PLoS ONE, 12(4), e0175382[10.1371/journal.pone.0175382]

114.Paul Nuyujukian, Jonathan C. Kao, Stephen I. Ryu, Krishna V. Shenoy. (2016). A Nonhuman Primate Brain–Computer Typing Interface. Proceedings of the IEEE, 105(1), 66–72[10.1109/jproc.2016.2586967]

115.Yeou‐Jiunn Chen, Shih-Chung Chen, Ilham Ari Elbaith Zaeni, Chung-Min Wu. (2016). Fuzzy Tracking and Control Algorithm for an SSVEP-Based BCI System. Applied Sciences, 6(10), 270[10.3390/app6100270]

116.Hongtao Wang, Ting Li, Zhenfeng Huang. (2010). Remote control of an electrical car with SSVEP-Based BCI. , 837–840[10.1109/icitis.2010.5689710]

117.De-Shuang Huang, Kyungsook Han, M. Michael Gromiha. (2014). Intelligent Computing in Bioinformatics. Lecture notes in computer science[10.1007/978-3-319-09330-7]

118.Fotis P. Kalaganis, Elisavet Chatzilari, Kostas Georgiadis, Spiros Nikolopoulos, Nikos Laskaris, Ioannis Kompatsiaris. (2017). An Error Aware SSVEP-based BCI. , 775–780[10.1109/cbms.2017.44]

119.Hung-Luen Jian, Kea‐Tiong Tang. (2014). Improving classification accuracy of SSVEP based BCI using RBF SVM with signal quality evaluation. , 302–306[10.1109/ispacs.2014.7024473]

120.Tejaswy Pailla, Werner Jiang, Ben Dichter, Edward F. Chang, Vikash Gilja. (2016). ECoG data analyses to inform closed-loop BCI experiments for speech-based prosthetic applications. , 5713–5716[10.1109/embc.2016.7592024]

121.Nicholas R. Waytowich, Dean J. Krusienski. (2017). Development of an extensible SSVEP-BCI software platform and application to wheelchair control. , 259–532[10.1109/ner.2017.8008406]

122.Qi Li, Kaiyang Shi, Shengyuan Ma, Ning Gao. (2016). Improving classification accuracy of SVM ensemble using random training set for BCI P300-speller. [10.1109/icma.2016.7558978]

123.Aunnoy K Mutasim, Rayhan Sardar Tipu, Mohammad Raihanul Bashar, M. Ashraful Amin. (2017). Video Category Classification Using Wireless EEG. Lecture notes in computer science, 39–48[10.1007/978-3-319-70772-3_4]

124.Christoph Guger, William G. Coon, James Swift, Brendan Z. Allison, Günter Edlinger. (2017). A motor rehabilitation BCI with multi-modal feedback in chronic stroke patients (P5.300). Neurology, 88(16_supplement)[10.1212/wnl.88.16_supplement.p5.300]

125.Chi-Yuan Lin, Wei‐Fan Chiang, Sheng-Chih Yang, Shu‐Yi Huang. (2014). Combining Event-Related Synchronization and Event-Related Desynchronization with Fuzzy C-Means to Classify Motor Imagery-Induced EEG Signals. Lecture notes in electrical engineering, 1039–1045[10.1007/978-3-319-04573-3_127]

126.Qi Li, Shengyuan Ma, Kaiyang Shi, Ning Gao. (2016). Comparing the classification performance of Bayesian linear discriminate analysis (BLDA) and support vector machine (SVM) in BCI P300-speller with familiar face paradigm. , 32, 1476–1481[10.1109/cisp-bmei.2016.7852950]

127.Joshua P. Kulasingham, V. Vibujithan, W. A. R. Kithmini, Y.V. A. C. Kumara, Anjula De Silva. (2016). P300 speller for local languages using Support Vector Machines. , 1–5[10.1109/iciafs.2016.7946525]

128.Anastasios Maronidis, Vangelis P. Oikonomou, Spiros Nikolopoulos, Ioannis Kompatsiaris. (2017). Steady state visual evoked potential detection using Subclass Marginal Fisher Analysis. , 37–41[10.1109/ner.2017.8008286]

Cited By

1.Antora Dev, Nipa Roy, Md. Kafiul Islam, Chiranjeeb Biswas, Helal Uddin Ahmed, Md. Ashraful Amin, Farhana Sarker, Ravi Vaidyanathan, Khondaker A. Mamun. (2022). Exploration of EEG-Based Depression Biomarkers Identification Techniques and Their Applications: A Systematic Review. IEEE Access, 10, 16756–16781[10.1109/access.2022.3146711]

2.Bandiyah Sri Aprillia, Achmad Rizal, Muhammad Arik Geraldy Fauzi. (2024). Grey Level Differences Matrix for Alcoholic EEG Signal Classification. JOIV International Journal on Informatics Visualization, 8(1), 26[10.62527/joiv.8.1.2602]

3.Amir Jalilifard, Dehua Chen, Aunnoy K. Mutasim, M. Raihanul Bashar, Rayhan Sardar Tipu, Ahsan-Ul Kabir Shawon, Nazmus Sakib, M. Ashraful Amin, Md. Kafiul Islam. (2020). Use of spontaneous blinking for application in human authentication. Engineering Science and Technology an International Journal, 23(4), 903–910[10.1016/j.jestch.2020.05.007]

4.Bommala Silpa, Malaya Kumar Hota, Norrima Mokthar. (2024). Suppression of Artifacts from EEG Recordings Using Computational Intelligence. Studies in computational intelligence, 261–279[10.1007/978-981-99-8853-2_17]

5.Lavinia Ferariu, Corina Cimpanu, Tiberius Dumitriu, Florina Ungureanu. (2018). EEG Multi-Objective Feature Selection Using Temporal Extension. , 777, 105–110[10.1109/iccp.2018.8516613]

6.Aunnoy K. Mutasim, M. Raihanul Bashar, Rayhan Sardar Tipu, Md. Kafiul Islam, M. Ashraful Amin. (2018). Effect of Artefact Removal Techniques on EEG Signals for Video Category Classification. , 9250, 3513–3518[10.1109/icpr.2018.8545416]

7.(2021). Implementation of Web Scraping on News Sites Using the Supervised Learning Method. İlköğretim Online, 20(3)[10.17051/ilkonline.2021.03.43]

8.Oana Andreea Rușanu. (2021). Advanced LabVIEW Applications Aimed for the Acquisition, Processing and Classification of the Electroencephalographic Signals Used in a Brain-Computer Interface System. Preprints.org[10.20944/preprints202106.0016.v1]

9.Oana Andreea Rușanu. (2022). A LabVIEW Instrument Aimed for the Research on Brain-Computer Interface by Enabling the Acquisition, Processing, and the Neural Networks based Classification of the Raw EEG Signal Detected by the Embedded NeuroSky Biosensor. Preprints.org[10.20944/preprints202106.0016.v2]

10.Eugenio Martínez, Rosario Baltazar, Carlos A. Reyes-García, Miguel Casillas, Martha-Alicia Rocha, Socorro Gutierrez, M. Del Consuelo Martínez Wbaldo. (2020). Multiagent System as Support for the Diagnosis of Language Impairments Using BCI-Neurofeedback: Preliminary Study. Smart innovation, systems and technologies, 235–243[10.1007/978-981-15-5764-4_21]