A Review of Hybrid Brain-Computer Interface Systems

Advances in Human-Computer Interaction - Tập 2013 - Trang 1-8 - 2013
Setare Amiri1, Reza Fazel-Rezai1, Vahid Asadpour1
1Biomedical Signal and Image Processing Laboratory, Department of Electrical Engineering, University of North Dakota, Grand Forks, ND, USA

Tóm tắt

Increasing number of research activities and different types of studies in brain-computer interface (BCI) systems show potential in this young research area. Research teams have studied features of different data acquisition techniques, brain activity patterns, feature extraction techniques, methods of classifications, and many other aspects of a BCI system. However, conventional BCIs have not become totally applicable, due to the lack of high accuracy, reliability, low information transfer rate, and user acceptability. A new approach to create a more reliable BCI that takes advantage of each system is to combine two or more BCI systems with different brain activity patterns or different input signal sources. This type of BCI, called hybrid BCI, may reduce disadvantages of each conventional BCI system. In addition, hybrid BCIs may create more applications and possibly increase the accuracy and the information transfer rate. However, the type of BCIs and their combinations should be considered carefully. In this paper, after introducing several types of BCIs and their combinations, we review and discuss hybrid BCIs, different possibilities to combine them, and their advantages and disadvantages.

Từ khóa


Tài liệu tham khảo

10.1016/S1388-2457(02)00057-3

10.1016/S1053-8119(03)00145-9

10.1523/JNEUROSCI.5171-07.2008

10.1088/0967-3334/25/4/003

1999, Nature, 398, 297, 10.1038/18581

1992, Journal of Microcomputer Applications, 15, 31, 10.1016/0745-7138(92)90045-7

1973, Annual Review of Biophysics and Bioengineering, 2, 157, 10.1146/annurev.bb.02.060173.001105

1977, Proceedings of the IEEE, 65, 633, 10.1109/PROC.1977.10542

2012, BCIs that use steady-state visual evoked potentials or slow cortical potentials

2012, BCIs that uses P300 event-related potentials

10.1007/BF02520010

10.1586/17434440.4.4.463

1988, Electroencephalography and Clinical Neurophysiology, 70, 510, 10.1016/0013-4694(88)90149-6

10.1016/j.jneumeth.2010.02.002

10.1088/1741-2560/7/2/026007

10.1109/TNSRE.2010.2040837

2010, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 18, 107, 10.1109/TNSRE.2009.2039495

10.1049/el.2010.0923

10.3389/fneng.2012.00014

1998, Behavioral and Brain Functions, 11, 357

1979, International Journal of Neuroscience, 9, 175, 10.3109/00207457909147670

10.1007/s002210050617

10.1016/S1388-2457(99)00141-8

10.3389/fnpro.2010.00003

10.1088/1741-2560/8/2/025010

10.1109/TBME.2011.2116018

10.1631/jzus.C1000208

2011, Neuroimage, 59, 519

10.1088/1741-2560/8/2/025011

2011, IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 1, 590, 10.1109/JETCAS.2011.2175589

2007, An introduction to brain-computer interfacing

10.1088/1741-2560/3/4/007

10.1016/j.jneumeth.2007.03.005

1979, Biometrics, 35, 69, 10.2307/2529937

2012, Journal of NeuroEngineering and Rehabilitation, 9, article 50

Thông tin
Thông tin xuất bản

Advances in Human-Computer Interaction

Tập 2013

1-8

Thông tin tác giả