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International Conference on Information Technology in Bio- and Medical Informatics

ITBAM 2016: Information Technology in Bio- and Medical Informatics pp 69–84Cite as

Filter Bank Common Spatio-Spectral Patterns for Motor Imagery Classification

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9832))

Abstract

In this study, a new spatio-spectral filtering method for motor imagery signal analysis is introduced. Motor imagery is an important research area in brain computer interfacing. EEG signals related with motor imagery have characteristic frequencies originating from sensorimotor cortex. Common spatial patterns (CSP) method is a very popular and successful spatial filtering algorithm in motor imagery classification. However, CSP only optimizes spatial filters, subject specific frequency selection should be done manually, which is a meticulous process. Therefore, an automatic method for spectral filter optimization is needed. Proposed filter bank common spatio-spectral patterns (FBCSSP) algorithm optimizes spatial and spectral filters. FBCSSP method uses a network of a filter bank and two consecutive CSP layers so that proposed structure has a subject specific response in both spatial and spectral domains. We inspected the proposed method in terms of classification accuracy and physiological consistence of the created filters using publicly available data set. FBCSSP method gave higher classification accuracy than other spatio-spectral pattern methods in the literature. Also, obtained spatial and spectral filters were consistent with the spatial and spectral properties of motor imagery signals.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Istanbul Technical University, Istanbul, Turkey

    Ayhan Yuksel & Tamer Olmez

Authors
  1. Ayhan Yuksel
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  2. Tamer Olmez
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Corresponding author

Correspondence to Ayhan Yuksel .

Editor information

Editors and Affiliations

  1. Institute of Informatics and Telematics , Pisa, Italy

    M. Elena Renda

  2. Czech Technical University in Prague , Prague 6, Czech Republic

    Miroslav Bursa

  3. Medical University Graz , Graz, Austria

    Andreas Holzinger

  4. San José State University , San Jose, California, USA

    Sami Khuri

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© 2016 Springer International Publishing Switzerland

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Yuksel, A., Olmez, T. (2016). Filter Bank Common Spatio-Spectral Patterns for Motor Imagery Classification. In: Renda, M., Bursa, M., Holzinger, A., Khuri, S. (eds) Information Technology in Bio- and Medical Informatics. ITBAM 2016. Lecture Notes in Computer Science(), vol 9832. Springer, Cham. https://doi.org/10.1007/978-3-319-43949-5_5

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  • DOI: https://doi.org/10.1007/978-3-319-43949-5_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-43948-8

  • Online ISBN: 978-3-319-43949-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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