Recent Advances of P300 Speller Paradigms and Algorithms

被引：6

作者：

Fang, Tao ^{[1
]}

Song, Zuoting ^{[1
]}

Niu, Lan ^{[2
]}

Le, Song ^{[1
]}

Zhang, Yuan ^{[1
]}

Zhang, Xueze ^{[1
]}

Zhan, Gege ^{[1
]}

Wang, Shouyan ^{[3
]}

Li, Hui ^{[4
]}

Lin, Yifang ^{[5
]}

Jia, Jie ^{[5
]}

Zhang, Lihua ^{[1
,2
]}

Kang, Xiaoyang ^{[1
,2
,6
]}

机构：

[1] Fudan Univ, Engn Res Ctr AI & Robot, Minist Educ,Inst AI & Robot,Acad Engn & Technol, Shanghai Engn Res Ctr AI & Robot,MOE Frontiers Ct, Shanghai, Peoples R China

[2] Ji Hua Lab, Foshan, Guangdong, Peoples R China

[3] Fudan Univ, Inst Sci & Technol Brain Inspired Intelligence, Shanghai, Peoples R China

[4] Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen, Peoples R China

[5] Fudan Univ, Huashan Hosp, Dept Rehabil Med, Shanghai, Peoples R China

[6] Zhejiang Lab, Res Ctr Intelligent Sensing, Hangzhou 311100, Peoples R China

来源：

2021 9TH IEEE INTERNATIONAL WINTER CONFERENCE ON BRAIN-COMPUTER INTERFACE (BCI) | 2021年

基金：

中国国家自然科学基金;

关键词：

Electroencephalogram (EEG); Brain Computer Interface (BCI); P300; speller; INTERFACE; PERFORMANCE;

D O I：

10.1109/BCI51272.2021.9385369

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

The P300 speller is the most common application that uses brain-computer interface (BCI) for object control. At present, many researches use the P300 for the application of text input. However, there is no unified standard in the design of P300 signal induced interface, signal acquisition process, and signal processing method. Therefore, we searched the articles about P300 speller design in recent years and summarized the key technical improvements. This review focuses on the design of signal induced interface, as well as the algorithms commonly used in signal processing. We particularly emphasized the design ideas of the induced interface, as well as the advantages and limitations of the algorithm. Only by improving or combining the existing induced interface morphology and processing algorithms, then creating new methods, can enhance the practical application capability of P300 speller.

引用

页码：229 / 234

页数：6

共 50 条

[1] Enhancements of the Classification Algorithms for the BCI P300 Speller Diagram
El Dabbagh, Hend
Fakhr, Waleed
2010 5TH CAIRO INTERNATIONAL BIOMEDICAL ENGINEERING CONFERENCE (CIBEC 2010), 2010, : 158 - 162
[2] A comparison study of two P300 speller paradigms for brain–computer interface
Jiahui Pan
Yuanqing Li
Zhenghui Gu
Zhuliang Yu
Cognitive Neurodynamics, 2013, 7 : 523 - 529
[3] Detection of P300 in a BCI Speller
Fira, Monica
CONVERGENCE AND HYBRID INFORMATION TECHNOLOGY, 2011, 206 : 481 - 487
[4] PolyMorph: A P300 Polymorphic Speller
Casagrande, Alberto
Jarmolowska, Joanna
Turconi, Marcello
Fabris, Francesco
Battaglini, Piero Paolo
BRAIN AND HEALTH INFORMATICS, 2013, 8211 : 297 - 306
[5] A Comparison Among Several P300 Brain-Computer Interface Speller Paradigms
Fazel-Rezai, Reza
Gavett, Scott
Ahmad, Waqas
Rabbi, Ahmed
Schneider, Eric
CLINICAL EEG AND NEUROSCIENCE, 2011, 42 (04) : 209 - 213
[6] A comparison study of two P300 speller paradigms for brain-computer interface
Pan, Jiahui
Li, Yuanqing
Gu, Zhenghui
Yu, Zhuliang
COGNITIVE NEURODYNAMICS, 2013, 7 (06) : 523 - 529
[7] Channel selection methods for the P300 Speller
Colwell, K. A.
Ryan, D. B.
Throckmorton, C. S.
Sellers, E. W.
Collins, L. M.
JOURNAL OF NEUROSCIENCE METHODS, 2014, 232 : 6 - 15
[8] A comparison of classification techniques for the P300 Speller
Krusienski, Dean J.
Sellers, Eric W.
Cabestaing, Francois
Bayoudh, Sabri
McFarland, Dennis J.
Vaughan, Theresa M.
Wolpaw, Jonathan R.
JOURNAL OF NEURAL ENGINEERING, 2006, 3 (04) : 299 - 305
[9] Toward enhanced P300 speller performance
Krusienski, D. J.
Sellers, E. W.
McFarland, D. J.
Vaughan, T. M.
Wolpaw, J. R.
JOURNAL OF NEUROSCIENCE METHODS, 2008, 167 (01) : 15 - 21
[10] Ensemble SWLDA Classifiers for the P300 Speller
Johnson, Garett D.
Krusienski, Dean J.
HUMAN-COMPUTER INTERACTION, PT II, 2009, 5611 : 551 - 557

← 1 2 3 4 5 →