Performance variation in motor imagery brain-computer interface: A brief review

被引:231
作者
Ahn, Minkyu [1 ]
Jun, Sung Chan [2 ]
机构
[1] Brown Univ, Dept Neurosci, Providence, RI 02912 USA
[2] Gwangju Inst Sci & Technol, Sch Informat & Commun, Kwangju 500712, South Korea
基金
新加坡国家研究基金会;
关键词
Brain computer interface; BCI-illiteracy; Performance variation; Prediction; Motor imagery; ALPHA; CLASSIFICATION; COMMUNICATION; OSCILLATIONS; POTENTIALS; PEOPLE; POWER;
D O I
10.1016/j.jneumeth.2015.01.033
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Brain-computer interface (BCI) technology has attracted significant attention over recent decades, and has made remarkable progress. However, BCI still faces a critical hurdle, in that performance varies greatly across and even within subjects, an obstacle that degrades the reliability of BCI systems. Understanding the causes of these problems is important if we are to create more stable systems. In this short review, we report the most recent studies and findings on performance variation, especially in motor imagery-based BCI, which has found that low-performance groups have a less-developed brain network that is incapable of motor imagery. Further, psychological and physiological states influence performance variation within subjects. We propose a possible strategic approach to deal with this variation, which may contribute to improving the reliability of BCI. In addition, the limitations of current work and opportunities for future studies are discussed. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:103 / 110
页数:8
相关论文
共 79 条
[61]   Sensorimotor rhythm-based brain-computer interface training: the impact on motor cortical responsiveness [J].
Pichiorri, F. ;
Fallani, F. De Vico ;
Cincotti, F. ;
Babiloni, F. ;
Molinari, M. ;
Kleih, S. C. ;
Neuper, C. ;
Kuebler, A. ;
Mattia, D. .
JOURNAL OF NEURAL ENGINEERING, 2011, 8 (02)
[62]  
Randolph A. B., 2012, 2012 45th Hawaii International Conference on System Sciences (HICSS), P572, DOI 10.1109/HICSS.2012.451
[63]   Individual Characteristics and Their Effect on Predicting Mu Rhythm Modulation [J].
Randolph, Adriane B. ;
Jackson, Melody Moore ;
Karmakar, Saurav .
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION, 2011, 27 (01) :24-37
[64]   Reactivity of magnetic parieto-occipital alpha rhythm during visual imagery [J].
Salenius, S ;
Kajola, M ;
Thompson, WL ;
Kosslyn, S ;
Hari, R .
ELECTROENCEPHALOGRAPHY AND CLINICAL NEUROPHYSIOLOGY, 1995, 95 (06) :453-462
[65]   Stationary common spatial patterns for brain-computer interfacing [J].
Samek, Wojciech ;
Vidaurre, Carmen ;
Mueller, Klaus-Robert ;
Kawanabe, Motoaki .
JOURNAL OF NEURAL ENGINEERING, 2012, 9 (02)
[66]  
Sannelli C., 2008, Estimating noise and dimensionality in BCI data sets: Towards illiteracy comprehension
[67]   Early modulation of visual cortex by sound: an MEG study [J].
Shams, L ;
Iwaki, S ;
Chawla, A ;
Bhattacharya, J .
NEUROSCIENCE LETTERS, 2005, 378 (02) :76-81
[68]   Towards adaptive classification for BCI [J].
Shenoy, Pradeep ;
Krauledat, Matthias ;
Blankertz, Benjamin ;
Rao, Raiesh P. N. ;
Mueller, Klaus-Robert .
JOURNAL OF NEURAL ENGINEERING, 2006, 3 (01) :R13-R23
[69]   Effect of mindfulness meditation on brain-computer interface performance [J].
Tan, Lee-Fan ;
Dienes, Zoltan ;
Jansari, Ashok ;
Goh, Sing-Yau .
CONSCIOUSNESS AND COGNITION, 2014, 23 :12-21
[70]   Neural synchrony in cortical networks: history, concept and current status [J].
Uhlhaas, Peter J. ;
Pipa, Gordon ;
Lima, Bruss ;
Melloni, Lucia ;
Neuenschwander, Sergio ;
Nikolic, Danko ;
Singer, Wolf .
FRONTIERS IN INTEGRATIVE NEUROSCIENCE, 2009, 3