Electro-encephalogram based brain-computer interface: improved performance by mental practice and concentration skills

被引:33
作者
Mahmoudi, Babak [1 ]
Erfanian, Abbas [1 ]
机构
[1] Iran Univ Sci & Technol, Fac Elect Engn, Dept Biomed Engn, Tehran 16844, Iran
关键词
EEG; neural network; brain-computer interface; mental practice; meditation;
D O I
10.1007/s11517-006-0111-8
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Mental imagination is the essential part of the most EEG-based communication systems. Thus, the quality of mental rehearsal, the degree of imagined effort, and mind controllability should have a major effect on the performance of electro-encephalogram (EEG) based brain-computer interface (BCI). It is now well established that mental practice using motor imagery improves motor skills. The effects of mental practice on motor skill learning are the result of practice on central motor programming. According to this view, it seems logical that mental practice should modify the neuronal activity in the primary sensorimotor areas and consequently change the performance of EEG-based BCI. For developing a practical BCI system, recognizing the resting state with eyes opened and the imagined voluntary movement is important. For this purpose, the mind should be able to focus on a single goal for a period of time. without deviation to another context. In this work, we are going to examine the role of mental practice and concentration skills on the EEG control during imaginative hand movements. The results show that the mental practice and concentration can generally improve the classification accuracy of the EEG patterns. It is found that mental training has a significant effect on the classification accuracy over the primary motor cortex and frontal area.
引用
收藏
页码:959 / 969
页数:11
相关论文
共 34 条
[21]   A local neural classifier for the recognition of EEG patterns associated to mental tasks [J].
Millán, JD ;
Mouriño, J ;
Franzé, M ;
Cincotti, F ;
Varsta, M ;
Heikkonen, J ;
Babiloni, F .
IEEE TRANSACTIONS ON NEURAL NETWORKS, 2002, 13 (03) :678-686
[22]   A new brain-computer interface design using fuzzy ARTMAP [J].
Palaniappan, R ;
Paramesran, R ;
Nishida, S ;
Saiwaki, N .
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 2002, 10 (03) :140-148
[23]  
Perez-De-Albeniz A., 2000, INT J PSYCHOTHER, V1, P49, DOI [10.1080/13569080050020263, DOI 10.1080/13569080050020263]
[24]   Walking from thought [J].
Pfurtscheller, G ;
Leeb, R ;
Keinrath, C ;
Friedman, D ;
Neuper, C ;
Guger, C ;
Slaterc, M .
BRAIN RESEARCH, 2006, 1071 (01) :145-152
[25]  
Pfurtscheller G, 1998, IEEE Trans Rehabil Eng, V6, P316, DOI 10.1109/86.712230
[26]   Motor imagery and direct brain-computer communication [J].
Pfurtscheller, G ;
Neuper, C .
PROCEEDINGS OF THE IEEE, 2001, 89 (07) :1123-1134
[27]  
Pregenzer M, 1999, IEEE Trans Rehabil Eng, V7, P413, DOI 10.1109/86.808944
[28]   Optimal spatial filtering of single trial EEG during imagined hand movement [J].
Ramoser, H ;
Müller-Gerking, J ;
Pfurtscheller, G .
IEEE TRANSACTIONS ON REHABILITATION ENGINEERING, 2000, 8 (04) :441-446
[29]   An improved P300-based brain-computer interface [J].
Serby, H ;
Yom-Tov, E ;
Inbar, GF .
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 2005, 13 (01) :89-98
[30]  
UHI F, 1990, NEUROPSYCHOLOGIA, V28, P81