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    Combining fNIRS and EEG to improve motor cortex activity classification during an imagined movement-based task

    Leamy, Darren J. and Collins, Ronan and Ward, Tomas E. (2011) Combining fNIRS and EEG to improve motor cortex activity classification during an imagined movement-based task. In: FAC'11 Proceedings of the 6th international conference on Foundations of augmented cognition: directing the future of adaptive systems. Springer-Verlag Berlin, Berlin, pp. 177-185. ISBN 9783642218514

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    This work serves as an initial investigation into improvements to classification accuracy of an imagined movement-based Brain Computer Interface (BCI) by combining the feature spaces of two unique measurement modalities: functional near infrared spectroscopy (fNIRS) and electroencephalography (EEG). Our dual-modality system recorded concurrent and co-locational hemodynamic and electrical responses in the motor cortex during an imagined movement task, participated in by two subjects. Offline analysis and classification of fNIRS and EEG data was performed using leave-one-out cross-validation (LOOCV) and linear discriminant analysis (LDA). Classification of 2-dimensional fNIRS and EEG feature spaces was performed separately and then their feature spaces were combined for further classification. Results of our investigation indicate that by combining feature spaces, modest gains in classification accuracy of an imagined movement-based BCI can be achieved by employing a supplemental measurement modality. It is felt that this technique may be particularly useful in the design of BCI devices for the augmentation of rehabilitation therapy.

    Item Type: Book Section
    Additional Information: Postprint version of published article.
    Keywords: fNIRS; EEG; motor cortex activity; classification; movement-based task; Brain Computer Interface; functional near infrared spectroscopy; electroencephalography;
    Academic Unit: Faculty of Science and Engineering > Electronic Engineering
    Item ID: 4365
    Depositing User: Dr Tomas Ward
    Date Deposited: 15 May 2013 14:38
    Publisher: Springer-Verlag Berlin
    Refereed: Yes
      Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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