Literature DB >> 17409474

A survey of signal processing algorithms in brain-computer interfaces based on electrical brain signals.

Ali Bashashati1, Mehrdad Fatourechi, Rabab K Ward, Gary E Birch.   

Abstract

Brain-computer interfaces (BCIs) aim at providing a non-muscular channel for sending commands to the external world using the electroencephalographic activity or other electrophysiological measures of the brain function. An essential factor in the successful operation of BCI systems is the methods used to process the brain signals. In the BCI literature, however, there is no comprehensive review of the signal processing techniques used. This work presents the first such comprehensive survey of all BCI designs using electrical signal recordings published prior to January 2006. Detailed results from this survey are presented and discussed. The following key research questions are addressed: (1) what are the key signal processing components of a BCI, (2) what signal processing algorithms have been used in BCIs and (3) which signal processing techniques have received more attention?

Mesh:

Year:  2007        PMID: 17409474     DOI: 10.1088/1741-2560/4/2/R03

Source DB:  PubMed          Journal:  J Neural Eng        ISSN: 1741-2552            Impact factor:   5.379


  91 in total

1.  A quantitative EEG method for detecting post clamp changes during carotid endarterectomy.

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Journal:  J Clin Monit Comput       Date:  2011-09-30       Impact factor: 2.502

2.  Joint spatial-spectral feature space clustering for speech activity detection from ECoG signals.

Authors:  Vasileios G Kanas; Iosif Mporas; Heather L Benz; Kyriakos N Sgarbas; Anastasios Bezerianos; Nathan E Crone
Journal:  IEEE Trans Biomed Eng       Date:  2014-04       Impact factor: 4.538

3.  Heading for new shores! Overcoming pitfalls in BCI design.

Authors:  Ricardo Chavarriaga; Melanie Fried-Oken; Sonja Kleih; Fabien Lotte; Reinhold Scherer
Journal:  Brain Comput Interfaces (Abingdon)       Date:  2016-12-30

4.  Towards a user-friendly brain-computer interface: initial tests in ALS and PLS patients.

Authors:  Ou Bai; Peter Lin; Dandan Huang; Ding-Yu Fei; Mary Kay Floeter
Journal:  Clin Neurophysiol       Date:  2010-03-29       Impact factor: 3.708

5.  Enabling fast brain-computer interaction by single-trial extraction of visual evoked potentials.

Authors:  Min Chen; Jinan Guan; Haihua Liu
Journal:  J Med Syst       Date:  2011-06-18       Impact factor: 4.460

6.  Improving mental task classification by adding high frequency band information.

Authors:  Li Zhang; Wei He; Chuanhong He; Ping Wang
Journal:  J Med Syst       Date:  2010-02       Impact factor: 4.460

7.  Optimizing spatial filters for single-trial EEG classification via a discriminant extension to CSP: the Fisher criterion.

Authors:  Haixian Wang
Journal:  Med Biol Eng Comput       Date:  2011-03-25       Impact factor: 2.602

8.  The advantages of the surface Laplacian in brain-computer interface research.

Authors:  Dennis J McFarland
Journal:  Int J Psychophysiol       Date:  2014-08-01       Impact factor: 2.997

Review 9.  A survey of stimulation methods used in SSVEP-based BCIs.

Authors:  Danhua Zhu; Jordi Bieger; Gary Garcia Molina; Ronald M Aarts
Journal:  Comput Intell Neurosci       Date:  2010-03-07

10.  Unscented Kalman filter for brain-machine interfaces.

Authors:  Zheng Li; Joseph E O'Doherty; Timothy L Hanson; Mikhail A Lebedev; Craig S Henriquez; Miguel A L Nicolelis
Journal:  PLoS One       Date:  2009-07-15       Impact factor: 3.240

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