Brain-Computer Interface Speller System for Alternative Communication: A Review

被引:15
|
作者
Kundu, S. [1 ,2 ]
Ari, S. [2 ]
机构
[1] CV Raman Global Univ, Dept Elect & Telecommun Engn, Bhubaneswar 752054, Odisha, India
[2] Natl Inst Technol Rourkela, Dept Elect & Commun Engn, Rourkela 769008, Odisha, India
关键词
Brain-computer interface; Machine learning; Motor imagery; P300; steady-state visually evoked potential (SSVEP); BCI COMPETITION 2003; MOTOR IMAGERY; CLASSIFICATION; PROSTHESIS; POTENTIALS; ALGORITHMS; MOVEMENT; P300;
D O I
10.1016/j.irbm.2021.07.001
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Brain-computer interface (BCI) speller is a system that provides an alternative communication for the disable people. The brain wave is translated into machine command through a BCI speller which can be used as a communication medium for the patients to express their thought without any motor movement. A BCI speller aims to spell characters by using the electroencephalogram (EEG) signal. Several types of BCI spellers are available based on the EEG signal. A standard BCI speller system consists of the following elements: BCI speller paradigm, data acquisition system and signal processing algorithms. In this work, a systematic review is provided on the BCI speller system and it includes speller paradigms, feature extraction, feature optimization and classification techniques for BCI speller. The advantages and limitations of different speller paradigm and machine learning algorithms are discussed in this article. Also, the future research directions are discussed which can overcome the limitations of present state-of-the-art techniques for BCI speller. (C) 2021 AGBM. Published by Elsevier Masson SAS. All rights reserved.
引用
收藏
页码:317 / 324
页数:8
相关论文
共 50 条
  • [41] INTRODUCTION OF A UNIVERSAL P300 BRAIN-COMPUTER INTERFACE COMMUNICATION SYSTEM
    Pinegger, Andreas
    Wriessnegger, Selina
    Mueller-Putz, Gernot
    [J]. BIOMEDICAL ENGINEERING-BIOMEDIZINISCHE TECHNIK, 2013, 58
  • [42] A Review of Adaptive Brain-Computer Interface Research
    Xiao, Xiaolin
    Xin, Fengran
    Mei, Jie
    Li, Ang
    Cao, Hongtao
    Xu, Fangzhou
    Xu, Minpeng
    Ming, Dong
    [J]. JOURNAL OF ELECTRONICS & INFORMATION TECHNOLOGY, 2023, 45 (07) : 2386 - 2394
  • [43] A Review of Hybrid Brain-Computer Interface Systems
    Amiri, Setare
    Fazel-Rezai, Reza
    Asadpour, Vahid
    [J]. ADVANCES IN HUMAN-COMPUTER INTERACTION, 2013, 2013
  • [44] Brain-Computer Interface Software: A Review and Discussion
    Stegman, Pierce
    Crawford, Chris S.
    Andujar, Marvin
    Nijholt, Anton
    Gilbert, Juan E.
    [J]. IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS, 2020, 50 (02) : 101 - 115
  • [45] Review on brain-computer interface technologies in healthcare
    Evelyn Karikari
    Konstantin A. Koshechkin
    [J]. Biophysical Reviews, 2023, 15 : 1351 - 1358
  • [46] The Brain-Computer Interface
    Langmoen, Iver A.
    Berg-Johnsen, Jon
    [J]. WORLD NEUROSURGERY, 2012, 78 (06) : 573 - 575
  • [47] Flexible Electrodes for Brain-Computer Interface System
    Wang, Junjie
    Wang, Tengjiao
    Liu, Haoyan
    Wang, Kun
    Moses, Kumi
    Feng, Zhuoya
    Li, Peng
    Huang, Wei
    [J]. ADVANCED MATERIALS, 2023, 35 (47)
  • [48] A screening protocol incorporating brain-computer interface feature matching considerations for augmentative and alternative communication
    Pitt, Kevin
    Brumberg, Jonathan
    [J]. ASSISTIVE TECHNOLOGY, 2020, 32 (03) : 161 - 172
  • [49] Prosthetic hand for the brain-computer interface system
    Yahud, S.
    Abu Osman, N. A.
    [J]. 3RD KUALA LUMPUR INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING 2006, 2007, 15 : 643 - +
  • [50] Interprofessional Practitioners' Opinions on Features and Services for an Augmentative and Alternative Communication Brain-Computer Interface Device
    Hill, Katya
    Huggins, Jane
    Woodworth, Chelsea
    [J]. PM&R, 2021, 13 (10) : 1111 - 1121