Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Erschienen in:
Brain-Computer Interfaces and Human-Computer Interaction Kapitel lesen Erstes Kapitel lesen

2010 | OriginalPaper | Buchkapitel

14. MATLAB-Based Tools for BCI Research

verfasst von : Arnaud Delorme, Christian Kothe, Andrey Vankov, Nima Bigdely-Shamlo, Robert Oostenveld, Thorsten O. Zander, Scott Makeig

Erschienen in: Brain-Computer Interfaces

Verlag: Springer London

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

We first discuss two MATLAB-centered solutions for real-time data streaming, the environments FieldTrip (Donders Institute, Nijmegen) and DataSuite (Data- River, Producer, MatRiver) (Swartz Center, La Jolla). We illustrate the relative simplicity of coding BCI feature extraction and classification under MATLAB (The Mathworks, Inc.) using a minimalist BCI example, and then describe BCILAB (Team PhyPa, Berlin), a new BCI package that uses the data structures and extends the capabilities of the widely used EEGLAB signal processing environment. We finally review the range of standalone and MATLAB-based software currently freely available to BCI researchers.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Vorheriges Kapitel From Brain Signals to Adaptive Interfaces: Using fNIRS in HCI
Nächstes Kapitel Using BCI2000 for HCI-Centered BCI Research
Literatur
Adapt © 1987–2003 and Varieté, © 2000, 2001 are property of EEG Solutions LLC, and are used under free license for scientific non-profit research
Bell AJ, Sejnowski TJ (1995) An information-maximization approach to blind separation and blind deconvolution. Neural Comput 7(6):1129–1159 CrossRef
Babiloni F, et al. (1995) Performances of surface Laplacian estimators: A study of simulated and real scalp potential distributions. Brain Topogr 8(1):35–45 CrossRef
Bilmes J (1998) Gentle Tutorial of the EM Algorithm and its Application to Parameter Estimation for Gaussian Mixture and Hidden Markov Models. International Computer Science Institute
Birbaumer N, et al. (2009) Neurofeedback and brain-computer interface clinical applications. Int Rev Neurobiol 86:107–187 CrossRef
Blankertz B, Curio G, Müller K (2002a) Classifying single trial EEG: Towards brain computer interfacing. In: Diettrich T, Becker S, Ghahramani Z (eds) Advances in Neural Inf Proc Systems (NIPS 01), pp 157–164
Blankertz B, et al (2002b) Single trial detection of EEG error potentials: A tool for increasing BCI transmission rates. In: Artificial Neural Networks—ICANN 2002
Delorme A, Makeig S (2004) EEGLAB: An open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J Neurosci Methods 134(1):9–21 CrossRef
Dornhege G, Blankertz B, Curio G (2003a) Speeding up classification of multi-channel brain-computer interfaces: Common spatial patterns for slow cortical potentials. In: First International IEEE EMBS Conference on In Neural Engineering
Dornhege G, et al (2003b) Combining features for BCI, In: Becker S, Thrun S, Obermayer K (eds), Proc Systems (NIPS 02), pp 1115–1122
Farwell L, Donchin E (1988) Talking off the top of your head: Toward a mental prosthesis utilizing event-related brain potentials. Electroencephalogr Clin Neurophysiol 70(6):510–523 CrossRef
Figueiredo M, Jain A (2002) Unsupervised learning on finite mixture models. IEEE Trans Pattern Anal Mach Intell 24(3)
Fisher R (1936) The use of multiple measurements in taxonomic problems. Ann Eugen 7:179–188 CrossRef
Friedman J (2002) Regularized discriminant analysis. J Am Stat Assoc 84(405):165–175 CrossRef
Jaakkola T, Jordan M (1997) A variational approach to Bayesian logistic regression models and their extensions. In: Sixth International Workshop on Artificial Intelligence and Statistics
Jung T-P, et al. (1997) Estimating alertness from the EEG power spectrum. IEEE Trans Biomed Eng 44(1):60–69 CrossRef
Kothe C (2009) Design and Implementation of a Research Brain-Computer Interface. Berlin Institute of Technology, Berlin. Section 8.2.1
Lin C-T, et al. (2008) A noninvasive prosthetic platform using mobile & wireless EEG. Proc IEEE 96(7):1167–1183 CrossRef
Makeig S, et al. (2009) Linking brain, mind and behavior. Int J Psychophysiol 73(2):95–100 CrossRef
Makeig S, et al. (2002) Dynamic brain sources of visual evoked responses. Science 295(5555):690–694 CrossRef
Makeig S, Inlow M (1993) Lapses in alertness: Coherence of fluctuations in performance and EEG spectrum. Electroencephalogr Clin Neurophysiol 86(1):23–35 CrossRef
Makeig S, et al (1996) Independent component analysis of electroencephalographic data. In: Touretzky D, Mozer M, Hasselmo M (eds), Advances in Neural Information Processing Systems, pp 145–151
Miner LA, McFarland DJ, Wolpaw JR (1998) Answering questions with an electroencephalogram-based brain-computer interface. Arch Phys Med Rehabil 79(9):1029–1033 CrossRef
Palmer JA, et al (2007) Modeling and estimation of dependent subspaces with non-radially symmetric and skewed densities. In: 7th International Conference on Independent Component Analysis and Signal Separation, London, UK
Perrin F et al. (1987) Mapping of scalp potentials by surface spline interpolation. Electroencephalogr Clin Neurophysiol 66(1):75–81 MathSciNetCrossRef
Ramoser H, Müller-Gerking J, Pfurtscheller G (1998) Optimal spatial filtering of single trial EEG during imagined hand movement. IEEE Trans Rehabil Eng 1998(8):441–446
Schalk G, et al. (2004) BCI2000: A general-purpose brain-computer interface (BCI) system. IEEE Trans Biomed Eng 51(6):1034–1043 CrossRef
Schlögl A (2000) The electroencephalogram and the Adaptive Autoregressive Model: Theory and Applications. Shaker Verlag, Aachen. ISBN3-8265-7640-3
Schlögl A, Brunner C (2000) Biosig: A free and open source software library for BCI research. Computer 41(10):44–50 CrossRef
Schölkopf B, Smola A (2002) Learning with Kernels. MIT Press, Cambridge, MA
Sellers E, et al. (2006) A p300 event-related potential brain-computer interface (BCI): The effects of matrix size and inter stimulus interval on performance. Biol Psychol 73(3):242–252 CrossRef
Tipping M (2001) Sparse Bayesian learning and the relevance vector machine. J Mach Learn Res 1:211–244 MathSciNetMATH
Tomioka R et al. (2006) An iterative algorithm for spatio-temporal filter optimization. In: 3rd International BCI Workshop and Training Course. Verlag der Technischen Universität Graz, Graz
Venthur B, Blankertz B (2008) A platform-independent open-source feedback framework for BCI systems. In: 4th International Brain-Computer Interface Workshop and Training Course
Vidaurre C, Schlögl (2008) A comparison of adaptive features with linear discriminant classifier for brain computer interfaces. In: Engineering in Medicine and Biology Society. EMBS 2008. 30th Annual International Conference of the IEEE
Vlassis N, Likas A, Greedy EM (2002) Algorithm for Gaussian Mixture Learning. Neural Processing Letters, vol 15. Kluwer Academic Publishers, Dordrecht
Zander T, Jatzev S (2009) Detecting affective covert user states with passive brain-computer interfaces. In: ACII 2009. IEEE Computer Society Press, Los Alamitos, CA
Metadaten
Titel
MATLAB-Based Tools for BCI Research
verfasst von
Arnaud Delorme
Christian Kothe
Andrey Vankov
Nima Bigdely-Shamlo
Robert Oostenveld
Thorsten O. Zander
Scott Makeig
Copyright-Jahr
2010
Verlag
Springer London
Buch
Brain-Computer Interfaces

Print ISBN: 978-1-84996-271-1

Electronic ISBN: 978-1-84996-272-8

Copyright-Jahr: 2010

DOI
https://doi.org/10.1007/978-1-84996-272-8_14

Neuer Inhalt

    Bildnachweise