An improved P300 pattern in BCI to catch user’s attention
暂无分享,去创建一个
Andrzej Cichocki | Ian Daly | Jing Jin | Xingyu Wang | Hanhan Zhang | A. Cichocki | Xingyu Wang | Jing Jin | I. Daly | Hanhan Zhang
[1] Mark S. Leeson,et al. Artificial Intelligence in Medicine Channel Selection and Classification of Electroencephalogram Signals: an Artificial Neural Network and Genetic Algorithm-based Approach , 2022 .
[2] L. Cohen,et al. Brain–computer interface in paralysis , 2008, Current opinion in neurology.
[3] John P. Donoghue,et al. Bridging the Brain to the World: A Perspective on Neural Interface Systems , 2008, Neuron.
[4] Yu Zhang,et al. Brain Control: Human-computer Integration Control Based on Brain-computer Interface Approach , 2013 .
[5] Xin Zhao,et al. Use of a steady-state baseline to address evoked vs. oscillation models of visual evoked potential origin , 2016, NeuroImage.
[6] E. Donchin,et al. Performance of concurrent tasks: a psychophysiological analysis of the reciprocity of information-processing resources. , 1983, Science.
[7] J. Wolpaw,et al. Brain-computer communication: unlocking the locked in. , 2001, Psychological bulletin.
[8] Ahmet Ademoglu,et al. Wavelet Analysis of P3a and P3b , 2004, Brain Topography.
[9] S M M Martens,et al. Overlap and refractory effects in a brain–computer interface speller based on the visual P300 event-related potential , 2009, Journal of neural engineering.
[10] Eric W Sellers,et al. Manipulating attention via mindfulness induction improves P300-based brain–computer interface performance , 2011, Journal of neural engineering.
[11] Xingyu Wang,et al. Effects of Background Music on Objective and Subjective Performance Measures in an Auditory BCI , 2016, Front. Comput. Neurosci..
[12] Margot J. Taylor,et al. Inversion and Contrast Polarity Reversal Affect both Encoding and Recognition Processes of Unfamiliar Faces: A Repetition Study Using ERPs , 2002, NeuroImage.
[13] Xingyu Wang,et al. P300 Chinese input system based on Bayesian LDA , 2010, Biomedizinische Technik. Biomedical engineering.
[14] J. Wolpaw,et al. A P300 event-related potential brain–computer interface (BCI): The effects of matrix size and inter stimulus interval on performance , 2006, Biological Psychology.
[15] Reza Fazel-Rezai,et al. Reducing human error in P300 speller paradigm for brain-computer interface , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[16] A. Cichocki,et al. The Changing Face of P300 BCIs: A Comparison of Stimulus Changes in a P300 BCI Involving Faces, Emotion, and Movement , 2012, PloS one.
[17] Leandro da Silva Sauer,et al. Variables psicológicas en el control de interfaces cerebro-computadora , 2011 .
[18] Steven Laureys,et al. The locked-in syndrome : what is it like to be conscious but paralyzed and voiceless? , 2005, Progress in brain research.
[19] A. Cichocki,et al. An optimized ERP brain–computer interface based on facial expression changes , 2014, Journal of neural engineering.
[20] E. W. Sellers,et al. Toward enhanced P300 speller performance , 2008, Journal of Neuroscience Methods.
[21] Xiaorong Gao,et al. A brain–computer interface using motion-onset visual evoked potential , 2008, Journal of neural engineering.
[22] Bo Hong,et al. Employing an active mental task to enhance the performance of auditory attention-based brain–computer interfaces , 2013, Clinical Neurophysiology.
[23] B. Blankertz,et al. (C)overt attention and visual speller design in an ERP-based brain-computer interface , 2010, Behavioral and Brain Functions.
[24] Cuntai Guan,et al. Optimizing the Channel Selection and Classification Accuracy in EEG-Based BCI , 2011, IEEE Transactions on Biomedical Engineering.
[25] Anton Nijholt,et al. Affective Pacman: A Frustrating Game for Brain-Computer Interface Experiments , 2009, INTETAIN.
[26] Tzyy-Ping Jung,et al. High-speed spelling with a noninvasive brain–computer interface , 2015, Proceedings of the National Academy of Sciences.
[27] Helge J. Ritter,et al. BCI competition 2003-data set IIb: support vector machines for the P300 speller paradigm , 2004, IEEE Transactions on Biomedical Engineering.
[28] Xingyu Wang,et al. A P300 Brain-Computer Interface Based on a Modification of the Mismatch Negativity Paradigm , 2015, Int. J. Neural Syst..
[29] A. Kübler,et al. Face stimuli effectively prevent brain–computer interface inefficiency in patients with neurodegenerative disease , 2013, Clinical Neurophysiology.
[30] Marvin M. Chun,et al. The Effect of Attention on Repetition Suppression and Multivoxel Pattern Similarity , 2013, Journal of Cognitive Neuroscience.
[31] T. Demiralp,et al. Time–frequency analysis reveals multiple functional components during oddball P300 , 1997, Neuroreport.
[32] Xingyu Wang,et al. Frequency Recognition in SSVEP-Based BCI using Multiset Canonical Correlation Analysis , 2013, Int. J. Neural Syst..
[33] S. Scott. Neuroscience: Converting thoughts into action , 2006, Nature.
[34] Soojin Park,et al. Neural representation of object orientation: A dissociation between MVPA and Repetition Suppression , 2016, NeuroImage.
[35] M. Crommelinck,et al. Is the N170 for faces cognitively penetrable? Evidence from repetition priming of Mooney faces of familiar and unfamiliar persons. , 2003, Brain research. Cognitive brain research.
[36] Xingyu Wang,et al. An ERP-Based BCI using an oddball Paradigm with Different Faces and Reduced errors in Critical Functions , 2014, Int. J. Neural Syst..
[37] E Donchin,et al. The mental prosthesis: assessing the speed of a P300-based brain-computer interface. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.
[38] George R. Mangun,et al. Sustained visual-spatial attention produces costs and benefits in response time and evoked neural activity , 1998, Neuropsychologia.
[39] Peng Yuan,et al. A study of the existing problems of estimating the information transfer rate in online brain–computer interfaces , 2013, Journal of neural engineering.
[40] Brendan Z Allison,et al. Effects of SOA and flash pattern manipulations on ERPs, performance, and preference: implications for a BCI system. , 2006, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.
[41] Ben H. Jansen,et al. An exploratory study of factors affecting single trial P300 detection , 2004, IEEE Transactions on Biomedical Engineering.
[42] Touradj Ebrahimi,et al. An efficient P300-based brain–computer interface for disabled subjects , 2008, Journal of Neuroscience Methods.
[43] M Salvaris,et al. Visual modifications on the P300 speller BCI paradigm , 2009, Journal of neural engineering.
[44] Xingyu Wang,et al. Sparse Bayesian Learning for Obtaining Sparsity of EEG Frequency Bands Based Feature Vectors in Motor Imagery Classification , 2017, Int. J. Neural Syst..
[45] E. Donchin,et al. Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials. , 1988, Electroencephalography and clinical neurophysiology.
[46] Wei Wu,et al. Multimodal BCIs: Target Detection, Multidimensional Control, and Awareness Evaluation in Patients With Disorder of Consciousness , 2016, Proceedings of the IEEE.
[47] J. N. Langdon,et al. Fatigue and boredom in repetitive work , 1937 .
[48] Xingyu Wang,et al. Targeting an efficient target-to-target interval for P300 speller brain–computer interfaces , 2012, Medical & Biological Engineering & Computing.
[49] Rami Saab,et al. An Auditory-Tactile Visual Saccade-Independent P300 Brain-Computer Interface , 2016, Int. J. Neural Syst..
[50] A. Kübler,et al. Flashing characters with famous faces improves ERP-based brain–computer interface performance , 2011, Journal of neural engineering.
[51] Xingyu Wang,et al. A new hybrid BCI paradigm based on P300 and SSVEP , 2015, Journal of Neuroscience Methods.
[52] Brendan Z. Allison,et al. Is It Significant? Guidelines for Reporting BCI Performance , 2012 .
[53] Hulusi Kececi,et al. Habituation and Dishabituation of P300 , 2006, Cognitive and behavioral neurology : official journal of the Society for Behavioral and Cognitive Neurology.
[54] J. Wolpaw,et al. A P300-based brain–computer interface for people with amyotrophic lateral sclerosis , 2008, Clinical Neurophysiology.
[55] E. Donchin,et al. A P300-based brain–computer interface: Initial tests by ALS patients , 2006, Clinical Neurophysiology.
[56] Vladimir Bostanov,et al. BCI competition 2003-data sets Ib and IIb: feature extraction from event-related brain potentials with the continuous wavelet transform and the t-value scalogram , 2004, IEEE Transactions on Biomedical Engineering.
[57] J. Wolpaw,et al. A novel P300-based brain–computer interface stimulus presentation paradigm: Moving beyond rows and columns , 2010, Clinical Neurophysiology.
[58] N. Birbaumer,et al. The Influence of Psychological State and Motivation on Brain–Computer Interface Performance in Patients with Amyotrophic Lateral Sclerosis – a Longitudinal Study , 2010, Front. Neuropharma..