Journal ArticleDOI
The non-invasive Berlin Brain-Computer Interface: fast acquisition of effective performance in untrained subjects.
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TLDR
It is proposed that the key to quick efficiency in the BBCI system is its flexibility due to complex but physiologically meaningful features and its adaptivity which respects the enormous inter-subject variability.About:
This article is published in NeuroImage.The article was published on 2007-08-15. It has received 865 citations till now. The article focuses on the topics: Brain–computer interface.read more
Citations
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Journal ArticleDOI
Optimization of Model Training Based on Iterative Minimum Covariance Determinant In Motor-Imagery BCI.
TL;DR: The common spatial patterns (CSP) algorithm is one of the most frequently used and effective spatial filtering methods for extracting relevant features for use in motor imagery brain-computer inter....
Posted Content
Transfer Learning for Motor Imagery Based Brain-Computer Interfaces: A Complete Pipeline
TL;DR: This paper proposes that TL could be considered in all three components of MI-based BCIs, and it is also very important to specifically add a data alignment component before signal processing to make the data from different subjects more consistent, and hence to facilitate subsequential TL.
Journal ArticleDOI
Mental State Estimation for Brain--Computer Interfaces
TL;DR: Four mental states have been identified and decoded from the electrocorticograms of six epileptic patients, engaged in a memory reach task, and a novel signal analysis technique has been applied to high-dimensional, statistically sparse ECoGs recorded by a large number of electrodes.
Book ChapterDOI
Machine-Learning based co-adaptive calibration: a perspective to fight BCI illiteracy
TL;DR: This work investigates to what extent co-adapting learning enables substantial BCI control for completely novice users and those who suffered from BCI illiteracy before.
Proceedings ArticleDOI
EEG denoising with a recurrent quantum neural network for a brain-computer interface
TL;DR: An alternative neural information processing architecture using the Schrödinger wave equation (SWE) for enhancement of the raw EEG signal is presented and the improvement in classification accuracy computed over nine subjects is found to be statistically significant.
References
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Book
Adaptive Filter Theory
TL;DR: In this paper, the authors propose a recursive least square adaptive filter (RLF) based on the Kalman filter, which is used as the unifying base for RLS Filters.
Book
Introduction to Statistical Pattern Recognition
TL;DR: This completely revised second edition presents an introduction to statistical pattern recognition, which is appropriate as a text for introductory courses in pattern recognition and as a reference book for workers in the field.
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
Event-related EEG/MEG synchronization and desynchronization: basic principles.
TL;DR: Quantification of ERD/ERS in time and space is demonstrated on data from a number of movement experiments, whereby either the same or different locations on the scalp can display ERD and ERS simultaneously.