Journal ArticleDOI
Classifying EEG-based motor imagery tasks by means of time–frequency synthesized spatial patterns
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TLDR
The present method promises to provide a useful alternative as a general purpose classification procedure for MI classification by using time-frequency synthesis approach to accommodate the individual difference, and using the spatial patterns derived from electroencephalogram (EEG) rhythmic components as the feature description.About:
This article is published in Clinical Neurophysiology.The article was published on 2004-12-01. It has received 218 citations till now. The article focuses on the topics: Time–frequency analysis & Motor imagery.read more
Citations
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Journal ArticleDOI
A review of classification algorithms for EEG-based brain–computer interfaces
TL;DR: This paper compares classification algorithms used to design brain-computer interface (BCI) systems based on electroencephalography (EEG) in terms of performance and provides guidelines to choose the suitable classification algorithm(s) for a specific BCI.
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Beyond mind-reading: multi-voxel pattern analysis of fMRI data
TL;DR: How researchers are using multi-voxel pattern analysis methods to characterize neural coding and information processing in domains ranging from visual perception to memory search is reviewed.
Journal ArticleDOI
A Review of Classification Algorithms for EEG-based Brain-Computer Interfaces: A 10-year Update
Fabien Lotte,Laurent Bougrain,Andrzej Cichocki,Andrzej Cichocki,Maureen Clerc,Marco Congedo,Alain Rakotomamonjy,Florian Yger +7 more
TL;DR: A comprehensive overview of the modern classification algorithms used in EEG-based BCIs is provided, the principles of these methods and guidelines on when and how to use them are presented, and a number of challenges to further advance EEG classification in BCI are identified.
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A survey of signal processing algorithms in brain-computer interfaces based on electrical brain signals.
TL;DR: This work presents the first such comprehensive survey of all BCI designs using electrical signal recordings published prior to January 2006, and asks what are the key signal processing components of a BCI, and what signal processing algorithms have been used in BCIs.
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Imagery of motor actions: differential effects of kinesthetic and visual-motor mode of imagery in single-trial EEG.
TL;DR: To improve motor-imagery-based BCI control, user training should emphasize kinesthetic experiences instead of visual representations of actions.
References
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Journal ArticleDOI
Brain-computer interfaces for communication and control.
Jonathan R. Wolpaw,Jonathan R. Wolpaw,Niels Birbaumer,Niels Birbaumer,Dennis J. McFarland,Gert Pfurtscheller,Theresa M. Vaughan +6 more
TL;DR: With adequate recognition and effective engagement of all issues, BCI systems could eventually provide an important new communication and control option for those with motor disabilities and might also give those without disabilities a supplementary control channel or a control channel useful in special circumstances.
Journal ArticleDOI
Optimal spatial filtering of single trial EEG during imagined hand movement
TL;DR: It is demonstrated that spatial filters for multichannel EEG effectively extract discriminatory information from two populations of single-trial EEG, recorded during left- and right-hand movement imagery.
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The representing brain: Neural correlates of motor intention and imagery
TL;DR: A mechanism is proposed that is able to encode the desired goal of the action and is applicable to different levels of representational organization, as well as investigating the role of posterior parietal and premotor cortical areas in schema instantiation.
Journal ArticleDOI
Brain-computer interface technology: a review of the first international meeting
Jonathan R. Wolpaw,Niels Birbaumer,W.J. Heetderks,Dennis J. McFarland,Paul Hunter Peckham,Gerwin Schalk,Emanuel Donchin,L.A. Quatrano,C.J. Robinson,C.J. Robinson,Theresa M. Vaughan +10 more
TL;DR: The first international meeting devoted to brain-computer interface research and development is summarized, which focuses on the development of appropriate applications, identification of appropriate user groups, and careful attention to the needs and desires of individual users.