Towards Enhancing Motor Imagery Based Brain-Computer Interface Performance by Integrating Speed of Imagined Movement

被引:0
作者
Xie, Tao [1 ]
Yao, Lin [1 ]
Sheng, Xinjun [1 ]
Zhang, Dingguo [1 ]
Zhu, Xiangyang [1 ]
机构
[1] Shanghai Jiao Tong Univ, State Key Lab Mech Syst & Vibrat, Shanghai 200030, Peoples R China
来源
INTELLIGENT ROBOTICS AND APPLICATIONS, ICIRA 2014, PT I | 2014年 / 8917卷
关键词
Brain-computer interface; motor imagery; clenching speed; ERD/ERS; HAND MOVEMENT; EEG;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Left and right motor imagery tasks have commonly been utilized to construct a two-class Brain-computer Interface system, whilst the speed property of imagined movement has received less attention. In this study, we are trying to integrate the types and speed property of both imagined movement and real movement to further improve the performance of the two-class BCI system. Thus, real movement session and imagined movement session were carried out on the separated days. In real movement session, it has shown that 8 healthy volunteers have achieved an average accuracy of 67.62% with the same actual left and right hand clenching speed, and 78.62% with diverse speeds, which was a significant improvement (p=0.0176). Besides, only three subjects could pass the 70% accuracy threshold with same actual clenching speed, while six of them achieved to pass it with diverse speeds. In imagined movement session, all the subjects with diverse imagined clenching speed achieved a better control compared with same imagined speed. The proposed idea of integration of speed information has shown a promising benefit in two-class BCI construction in this preliminary study.
引用
收藏
页码:234 / 241
页数:8
相关论文
共 19 条
  • [1] Toward a hybrid brain-computer interface based on imagined movement and visual attention
    Allison, B. Z.
    Brunner, C.
    Kaiser, V.
    Mueller-Putz, G. R.
    Neuper, C.
    Pfurtscheller, G.
    [J]. JOURNAL OF NEURAL ENGINEERING, 2010, 7 (02)
  • [2] FUKUNAGA K, 1990, INTRO STAT PATTERN R, P1
  • [3] How many people are able to control a P300-based brain-computer interface (BCI)?
    Guger, Christoph
    Daban, Shahab
    Sellers, Eric
    Holzner, Clemens
    Krausz, Gunther
    Carabalona, Roberta
    Gramatica, Furio
    Edlinger, Guenter
    [J]. NEUROSCIENCE LETTERS, 2009, 462 (01) : 94 - 98
  • [4] Inferring hand movement kinematics from MEG, EEG and intracranial EEG: From brain-machine interfaces to motor rehabilitation
    Jerbi, K.
    Vidal, J. R.
    Mattout, J.
    Maby, E.
    Lecaignard, F.
    Ossandon, T.
    Hamame, C. M.
    Dalal, S. S.
    Bouet, R.
    Lachaux, J. -P.
    Leahy, R. M.
    Baillet, S.
    Garnero, L.
    Delpuech, C.
    Bertrand, O.
    [J]. IRBM, 2011, 32 (01) : 8 - 18
  • [5] Mu and beta rhythm topographies during motor imagery and actual movements
    McFarland, DJ
    Miner, LA
    Vaughan, TM
    Wolpaw, JR
    [J]. BRAIN TOPOGRAPHY, 2000, 12 (03) : 177 - 186
  • [6] Noninvasive brain-actuated control of a mobile robot by human EEG
    Millán, JD
    Renkens, F
    Mouriño, J
    Gerstner, W
    [J]. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2004, 51 (06) : 1026 - 1033
  • [7] EEG-based discrimination between imagination of right and left hand movement
    Pfurtscheller, G
    Neuper, C
    Flotzinger, D
    Pregenzer, M
    [J]. ELECTROENCEPHALOGRAPHY AND CLINICAL NEUROPHYSIOLOGY, 1997, 103 (06): : 642 - 651
  • [8] β rebound after different types of motor imagery in man
    Pfurtscheller, G
    Neuper, C
    Brunner, C
    da Silva, FL
    [J]. NEUROSCIENCE LETTERS, 2005, 378 (03) : 156 - 159
  • [9] 'Thought' -: control of functional electrical stimulation to restore hand grasp in a patient with tetraplegia
    Pfurtscheller, G
    Müller, GR
    Pfurtscheller, J
    Gerner, HJ
    Rupp, R
    [J]. NEUROSCIENCE LETTERS, 2003, 351 (01) : 33 - 36
  • [10] Event-related EEG/MEG synchronization and desynchronization: basic principles
    Pfurtscheller, G
    da Silva, FHL
    [J]. CLINICAL NEUROPHYSIOLOGY, 1999, 110 (11) : 1842 - 1857