Literature DB >> 18607780

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

Lucia Rita Quitadamo1, Maria Grazia Marciani, Gian Carlo Cardarilli, Luigi Bianchi.   

Abstract

All the protocols currently implemented in brain computer interface (BCI) experiments are characterized by different structural and temporal entities. Moreover, due to the lack of a unique descriptive model for BCI systems, there is not a standard way to define the structure and the timing of a BCI experimental session among different research groups and there is also great discordance on the meaning of the most common terms dealing with BCI, such as trial, run and session. The aim of this paper is to provide a unified modeling language (UML) implementation of BCI systems through a unique dynamic model which is able to describe the main protocols defined in the literature (P300, mu-rhythms, SCP, SSVEP, fMRI) and demonstrates to be reasonable and adjustable according to different requirements. This model includes a set of definitions of the typical entities encountered in a BCI, diagrams which explain the structural correlations among them and a detailed description of the timing of a trial. This last represents an innovation with respect to the models already proposed in the literature. The UML documentation and the possibility of adapting this model to the different BCI systems built to date, make it a basis for the implementation of new systems and a mean for the unification and dissemination of resources. The model with all the diagrams and definitions reported in the paper are the core of the body language framework, a free set of routines and tools for the implementation, optimization and delivery of cross-platform BCI systems.

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Year:  2008        PMID: 18607780     DOI: 10.1007/s12021-008-9015-0

Source DB:  PubMed          Journal:  Neuroinformatics        ISSN: 1539-2791


  35 in total

1.  Rapid prototyping of an EEG-based brain-computer interface (BCI).

Authors:  C Guger; A Schlögl; C Neuper; D Walterspacher; T Strein; G Pfurtscheller
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2001-03       Impact factor: 3.802

2.  Information transfer rate in a five-classes brain-computer interface.

Authors:  B Obermaier; C Neuper; C Guger; G Pfurtscheller
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Review 3.  Brain-computer interfaces for communication and control.

Authors:  Jonathan R Wolpaw; Niels Birbaumer; Dennis J McFarland; Gert Pfurtscheller; Theresa M Vaughan
Journal:  Clin Neurophysiol       Date:  2002-06       Impact factor: 3.708

4.  Introducing BF++: AC++ framework for cognitive bio-feedback systems design.

Authors:  L Bianchi; F Babiloni; F Cincotti; S Salinari; M G Marciani
Journal:  Methods Inf Med       Date:  2003       Impact factor: 2.176

5.  A general framework for characterizing studies of brain interface technology.

Authors:  S G Mason; M M Moore Jackson; G E Birch
Journal:  Ann Biomed Eng       Date:  2005-11       Impact factor: 3.934

6.  A practical VEP-based brain-computer interface.

Authors:  Yijun Wang; Ruiping Wang; Xiaorong Gao; Bo Hong; Shangkai Gao
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2006-06       Impact factor: 3.802

7.  Brain-computer interfaces for 1-D and 2-D cursor control: designs using volitional control of the EEG spectrum or steady-state visual evoked potentials.

Authors:  Leonard J Trejo; Roman Rosipal; Bryan Matthews
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2006-06       Impact factor: 3.802

8.  Brain computer interface research at the neuroscience department of the "Tor Vergata" University of Rome, Italy.

Authors:  Lucia Rita Quitadamo; Manuel Abbafati; Giovanni Saggio; Maria Grazia Marciani; Luigi Bianchi
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2007

9.  Brain-computer communication: self-regulation of slow cortical potentials for verbal communication.

Authors:  A Kübler; N Neumann; J Kaiser; B Kotchoubey; T Hinterberger; N P Birbaumer
Journal:  Arch Phys Med Rehabil       Date:  2001-11       Impact factor: 3.966

10.  A brain-computer interface (BCI) for the locked-in: comparison of different EEG classifications for the thought translation device.

Authors:  Thilo Hinterberger; Andrea Kübler; Jochen Kaiser; Nicola Neumann; Niels Birbaumer
Journal:  Clin Neurophysiol       Date:  2003-03       Impact factor: 3.708

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  4 in total

1.  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

Review 2.  Review of Riemannian Distances and Divergences, Applied to SSVEP-based BCI.

Authors:  S Chevallier; E K Kalunga; Q Barthélemy; E Monacelli
Journal:  Neuroinformatics       Date:  2021-01

3.  Targeting an efficient target-to-target interval for P300 speller brain-computer interfaces.

Authors:  Jing Jin; Eric W Sellers; Xingyu Wang
Journal:  Med Biol Eng Comput       Date:  2012-02-18       Impact factor: 2.602

4.  Tools for Brain-Computer Interaction: A General Concept for a Hybrid BCI.

Authors:  Gernot R Müller-Putz; Christian Breitwieser; Febo Cincotti; Robert Leeb; Martijn Schreuder; Francesco Leotta; Michele Tavella; Luigi Bianchi; Alex Kreilinger; Andrew Ramsay; Martin Rohm; Max Sagebaum; Luca Tonin; Christa Neuper; José Del R Millán
Journal:  Front Neuroinform       Date:  2011-11-24       Impact factor: 4.081

  4 in total

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