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Transactions on Rough Sets V pp 207–223Cite as

P300 Wave Detection Based on Rough Sets

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Part of the Lecture Notes in Computer Science book series (TRS,volume 4100)

Abstract

The goal of P300 wave detection is to extract relevant features from the huge number of electrical signals and to detect the P300 component accurately. This paper introduces a modified approach to P300 wave detection combined with an application of rough set methods and non-rough set based methods to classify P300 signals. The modifications include an averaging method using Mexican hat wavelet coefficients to extract features of signals. The data set has been expanded to include signals from six words and a total of 3960 objects. Experiments with a variety of classifiers were performed. The signal data analysis includes comparisons of error rates, true positives and false negatives performed using a paired t-test. It has been found that the false negatives are better indicators of efficacy of the feature extraction method rather than error rate due to the nature of the signal data. The contribution of this paper is an in-depth study P300 wave detection using a modified averaging method for feature extraction together with rough set-based classification on an expanded data set.

Keywords

  • Brain computer interface
  • EEG signal classification
  • Mexican hat wavelet
  • P300 wave detection
  • feature extraction
  • rough sets

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Author information

Authors and Affiliations

  1. Department of Applied Computer Science, University of Winnipeg, Winnipeg, Manitoba, R3B 2E9, Canada

    Sheela Ramanna

  2. Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, Manitoba, R3T 5V6, Canada

    Reza Fazel-Rezai

Authors
  1. Sheela Ramanna
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  2. Reza Fazel-Rezai
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Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering, University of Manitoba, R3T 5V6, Winnipeg, Manitoba, Canada

    James F. Peters

  2. Institute of Mathematics, Warsaw University, Banacha 2, 02-097, Warsaw, Poland

    Andrzej Skowron

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© 2006 Springer-Verlag Berlin Heidelberg

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Ramanna, S., Fazel-Rezai, R. (2006). P300 Wave Detection Based on Rough Sets. In: Peters, J.F., Skowron, A. (eds) Transactions on Rough Sets V. Lecture Notes in Computer Science, vol 4100. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11847465_10

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  • DOI: https://doi.org/10.1007/11847465_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-39382-5

  • Online ISBN: 978-3-540-39383-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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