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A fully on-line adaptive BCI

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TLDR
A viable fully on-line adaptive brain computer interface (BCI) is introduced that was based on motor imagery, the feature extraction was performed with an adaptive autoregressive model and the classifier was an adaptive quadratic discriminant analysis.
Abstract
A viable fully on-line adaptive brain computer interface (BCI) is introduced. On-line experiments with nine naive and able-bodied subjects were carried out using a continuously adaptive BCI system. The data were analyzed and the viability of the system was studied. The BCI was based on motor imagery, the feature extraction was performed with an adaptive autoregressive model and the classifier used was an adaptive quadratic discriminant analysis. The classifier was on-line updated by an adaptive estimation of the information matrix (ADIM). The system was also able to provide continuous feedback to the subject. The success of the feedback was studied analyzing the error rate and mutual information of each session and this analysis showed a clear improvement of the subject's control of the BCI from session to session.

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Citations
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Journal ArticleDOI

Optimizing Spatial filters for Robust EEG Single-Trial Analysis

TL;DR: The theoretical background of the common spatial pattern (CSP) algorithm, a popular method in brain-computer interface (BCD research), is elucidated and tricks of the trade for achieving a powerful CSP performance are revealed.
Journal ArticleDOI

Single-Trial Analysis and Classification of ERP Components - a Tutorial

TL;DR: This tutorial proposes to use shrinkage estimators and shows that appropriate regularization of linear discriminant analysis (LDA) by shrinkage yields excellent results for single-trial ERP classification that are far superior to classical LDA classification.
Journal ArticleDOI

Combining Brain-Computer Interfaces and Assistive Technologies: State-of-the-Art and Challenges.

TL;DR: This paper focuses on the prospect of improving the lives of countless disabled individuals through a combination of BCI technology with existing assistive technologies (AT) and identifies four application areas where disabled individuals could greatly benefit from advancements inBCI technology, namely, “Communication and Control”, ‘Motor Substitution’, ”Entertainment” and “Motor Recovery”.
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A brain-actuated wheelchair: asynchronous and non-invasive Brain-computer interfaces for continuous control of robots.

TL;DR: The results show that subjects can rapidly master the authors' asynchronous EEG-based BCI to control a wheelchair and can autonomously operate the BCI over long periods of time without the need for adaptive algorithms externally tuned by a human operator to minimize the impact of EEG non-stationarities.
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Neurophysiological Predictor of SMR-based BCI Performance

TL;DR: A neurophysiological predictor of BCI performance is proposed which can be determined from a two minute recording of a 'relax with eyes open' condition using two Laplacian EEG channels.
References
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Book

Adaptive Filter Theory

Simon Haykin
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.
Journal ArticleDOI

Brain-computer interfaces for communication and control.

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

Brain-computer interface technology: a review of the first international meeting

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.
Journal ArticleDOI

Motor imagery and direct brain-computer communication

TL;DR: At this time, a tetraplegic patient is able to operate an EEG-based control of a hand orthosis with nearly 100% classification accuracy by mental imagination of specific motor commands.
Journal ArticleDOI

A spelling device for the paralysed

TL;DR: A new means of communication for the completely paralysed that uses slow cortical potentials of the electro-encephalogram to drive an electronic spelling device is developed.
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