Literature DB >> 16761852

A fully on-line adaptive BCI.

C Vidaurre1, A Schlögl, A Schlöogl, R Cabeza, R Scherer, G Pfurtscheller.   

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.

Mesh:

Year:  2006        PMID: 16761852     DOI: 10.1109/TBME.2006.873542

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  25 in total

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Journal:  Med Biol Eng Comput       Date:  2008-04-17       Impact factor: 2.602

2.  ERD-based online brain-machine interfaces (BMI) in the context of neurorehabilitation: optimizing BMI learning and performance.

Authors:  Surjo R Soekadar; Matthias Witkowski; Jürgen Mellinger; Ander Ramos; Niels Birbaumer; Leonardo G Cohen
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2011-10       Impact factor: 3.802

3.  Should the parameters of a BCI translation algorithm be continually adapted?

Authors:  Dennis J McFarland; William A Sarnacki; Jonathan R Wolpaw
Journal:  J Neurosci Methods       Date:  2011-05-06       Impact factor: 2.390

4.  Efficient human-machine control with asymmetric marginal reliability input devices.

Authors:  John H Williamson; Melissa Quek; Iulia Popescu; Andrew Ramsay; Roderick Murray-Smith
Journal:  PLoS One       Date:  2020-06-01       Impact factor: 3.240

5.  Unsupervised adaptation of brain-machine interface decoders.

Authors:  Tayfun Gürel; Carsten Mehring
Journal:  Front Neurosci       Date:  2012-11-16       Impact factor: 4.677

6.  Performance assessment in brain-computer interface-based augmentative and alternative communication.

Authors:  David E Thompson; Stefanie Blain-Moraes; Jane E Huggins
Journal:  Biomed Eng Online       Date:  2013-05-16       Impact factor: 2.819

7.  The Berlin Brain-Computer Interface: Non-Medical Uses of BCI Technology.

Authors:  Benjamin Blankertz; Michael Tangermann; Carmen Vidaurre; Siamac Fazli; Claudia Sannelli; Stefan Haufe; Cecilia Maeder; Lenny Ramsey; Irene Sturm; Gabriel Curio; Klaus-Robert Müller
Journal:  Front Neurosci       Date:  2010-12-08       Impact factor: 4.677

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

Authors:  J D R Millán; R Rupp; G R Müller-Putz; R Murray-Smith; C Giugliemma; M Tangermann; C Vidaurre; F Cincotti; A Kübler; R Leeb; C Neuper; K-R Müller; D Mattia
Journal:  Front Neurosci       Date:  2010-09-07       Impact factor: 4.677

9.  BioSig: the free and open source software library for biomedical signal processing.

Authors:  Carmen Vidaurre; Tilmann H Sander; Alois Schlögl
Journal:  Comput Intell Neurosci       Date:  2011-03-08

10.  Whatever works: a systematic user-centered training protocol to optimize brain-computer interfacing individually.

Authors:  Elisabeth V C Friedrich; Christa Neuper; Reinhold Scherer
Journal:  PLoS One       Date:  2013-09-23       Impact factor: 3.240

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