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Dimension Reduction Techniques in a Brain–Computer Interface Application

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Book cover Neural Approaches to Dynamics of Signal Exchanges

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 151))

Abstract

Electroencephalography (EEG)-based Brain–computer interface (BCI) technology allows a user to control an external device without muscle intervention through recorded neural activity. Ongoing research on BCI systems includes applications in the medical field to assist subjects with impaired motor functionality (e.g., for the control of prosthetic devices). In this context, the accuracy and efficiency of a BCI system are of paramount importance. Comparing four different dimension reduction techniques in combination with linear and nonlinear classifiers, we show that integrating these methods in a BCI system results in a reduced model complexity without affecting overall accuracy.

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Author information

Authors and Affiliations

  1. NeuRoNeLab, Department of Management and Innovation Systems, University of Salerno, 84084, Fisciano, SA, Italy

    Federico Cozza, Paola Galdi, Angela Serra & Roberto Tagliaferri

  2. Neuromed, Mediterranean Neurological Institute, 86077, Pozzilli, IS, Italy

    Gabriele Pasqua & Luigi Pavone

  3. MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, EH16 4TJ, UK

    Paola Galdi

  4. Faculty of Medicine and Health Technology, Tampere University, 33200, Tampere, Finland

    Angela Serra

Authors
  1. Federico Cozza
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  2. Paola Galdi
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  3. Angela Serra
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  4. Gabriele Pasqua
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  5. Luigi Pavone
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  6. Roberto Tagliaferri
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Corresponding author

Correspondence to Roberto Tagliaferri .

Editor information

Editors and Affiliations

  1. Department of Psychology, University of Campania Luigi Vanvitelli, Caserta, Italy

    Anna Esposito

  2. Tecnocampus, Mataró, Spain

    Marcos Faundez-Zanuy

  3. Department of Civil, Environment, Energy and Materials Engineering, Mediterranea University of Reggio Calabria, Reggio Calabria, Italy

    Francesco Carlo Morabito

  4. Dipartimento di Elettronica e Telecomunicazioni, Politecnico di Torino, Turin, Italy

    Eros Pasero

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Cozza, F., Galdi, P., Serra, A., Pasqua, G., Pavone, L., Tagliaferri, R. (2020). Dimension Reduction Techniques in a Brain–Computer Interface Application. In: Esposito, A., Faundez-Zanuy, M., Morabito, F., Pasero, E. (eds) Neural Approaches to Dynamics of Signal Exchanges. Smart Innovation, Systems and Technologies, vol 151. Springer, Singapore. https://doi.org/10.1007/978-981-13-8950-4_11

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