Literature DB >> 17601190

Performances evaluation and optimization of brain computer interface systems in a copy spelling task.

Luigi Bianchi1, Lucia Rita Quitadamo, Girolamo Garreffa, Gian Carlo Cardarilli, Maria Grazia Marciani.   

Abstract

The evaluation of the performances of brain-computer interface (BCI) systems could be difficult as a standard procedure does not exist. In fact, every research team creates its own experimental protocol (different input signals, different trial structure, different output devices, etc.) and this makes systems comparison difficult. Moreover, the great question is whether these experiments can be extrapolated to real world applications or not. To overcome some intrinsic limitations of the most used criteria a new efficiency indicator will be described and used. Its main advantages are that it can predict with a high accuracy the performances of a whole system, a fact that can be used to successfully improve its behavior. Finally, simulations were performed to illustrate that the best system is built by tuning the transducer (TR) and the control interface (CI), which are the two main components of a BCI system, so that the best TR and the best CI do not exist but just the best combination of them.

Mesh:

Year:  2007        PMID: 17601190     DOI: 10.1109/TNSRE.2007.897024

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  11 in total

1.  A novel P300-based brain-computer interface stimulus presentation paradigm: moving beyond rows and columns.

Authors:  G Townsend; B K LaPallo; C B Boulay; D J Krusienski; G E Frye; C K Hauser; N E Schwartz; T M Vaughan; J R Wolpaw; E W Sellers
Journal:  Clin Neurophysiol       Date:  2010-03-26       Impact factor: 3.708

2.  Describing different brain computer interface systems through a unique model: a UML implementation.

Authors:  Lucia Rita Quitadamo; Maria Grazia Marciani; Gian Carlo Cardarilli; Luigi Bianchi
Journal:  Neuroinformatics       Date:  2008-07-08

3.  Performance measurement for brain-computer or brain-machine interfaces: a tutorial.

Authors:  David E Thompson; Lucia R Quitadamo; Luca Mainardi; Khalil Ur Rehman Laghari; Shangkai Gao; Pieter-Jan Kindermans; John D Simeral; Reza Fazel-Rezai; Matteo Matteucci; Tiago H Falk; Luigi Bianchi; Cynthia A Chestek; Jane E Huggins
Journal:  J Neural Eng       Date:  2014-05-19       Impact factor: 5.379

4.  Workshops of the Seventh International Brain-Computer Interface Meeting: Not Getting Lost in Translation.

Authors:  Jane E Huggins; Christoph Guger; Erik Aarnoutse; Brendan Allison; Charles W Anderson; Steven Bedrick; Walter Besio; Ricardo Chavarriaga; Jennifer L Collinger; An H Do; Christian Herff; Matthias Hohmann; Michelle Kinsella; Kyuhwa Lee; Fabien Lotte; Gernot Müller-Putz; Anton Nijholt; Elmar Pels; Betts Peters; Felix Putze; Rüdiger Rupp; Gerwin Schalk; Stephanie Scott; Michael Tangermann; Paul Tubig; Thorsten Zander
Journal:  Brain Comput Interfaces (Abingdon)       Date:  2019-12-10

5.  Classifier-based latency estimation: a novel way to estimate and predict BCI accuracy.

Authors:  David E Thompson; Seth Warschausky; Jane E Huggins
Journal:  J Neural Eng       Date:  2012-12-12       Impact factor: 5.379

6.  Workshops of the Fifth International Brain-Computer Interface Meeting: Defining the Future.

Authors:  Jane E Huggins; Christoph Guger; Brendan Allison; Charles W Anderson; Aaron Batista; Anne-Marie A-M Brouwer; Clemens Brunner; Ricardo Chavarriaga; Melanie Fried-Oken; Aysegul Gunduz; Disha Gupta; Andrea Kübler; Robert Leeb; Fabien Lotte; Lee E Miller; Gernot Müller-Putz; Tomasz Rutkowski; Michael Tangermann; David Edward Thompson
Journal:  Brain Comput Interfaces (Abingdon)       Date:  2014-01

7.  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

8.  Improving the efficacy of ERP-based BCIs using different modalities of covert visuospatial attention and a genetic algorithm-based classifier.

Authors:  Mauro Marchetti; Francesco Onorati; Matteo Matteucci; Luca Mainardi; Francesco Piccione; Stefano Silvoni; Konstantinos Priftis
Journal:  PLoS One       Date:  2013-01-14       Impact factor: 3.240

9.  A Fuzzy Integral Ensemble Method in Visual P300 Brain-Computer Interface.

Authors:  Francesco Cavrini; Luigi Bianchi; Lucia Rita Quitadamo; Giovanni Saggio
Journal:  Comput Intell Neurosci       Date:  2015-12-24

10.  Optimal pseudorandom sequence selection for online c-VEP based BCI control applications.

Authors:  Jonas L Isaksen; Ali Mohebbi; Sadasivan Puthusserypady
Journal:  PLoS One       Date:  2017-09-13       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.