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User Customization of the Feature Generator of an Asynchronous Brain Interface

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A study that customizes the feature generator parameters of an asynchronous Brain Interface (BI) is discussed. The goal is to detect the presence of a certain pattern, in the ongoing EEG, associated with a specific movement and to improve the system's performance. Results of this study show that customization mostly benefits able-bodied subjects with performance improvements of up to 6.8%. We evaluate the performance of our BI using stratified cross-validation scheme. This scheme repeats the analysis on the different cross-validation sets. It is shown that the performances of the system across the different sets are very similar. Thus, we conclude that a robust performance measure of the system can be obtained by using only one of these performance results.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada, V6T 1Z4

    Ali Bashashati, Mehrdad Fatourechi, Rabab K. Ward & Gary E. Birch

  2. Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada, V6T 1Z4

    Ali Bashashati & Gary E. Birch

  3. Neil Squire Society, Burnaby, BC, Canada, V5M 3Z3

    Rabab K. Ward

Authors
  1. Ali Bashashati
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  2. Mehrdad Fatourechi
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  3. Rabab K. Ward
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  4. Gary E. Birch
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Correspondence to Ali Bashashati.

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Bashashati, A., Fatourechi, M., Ward, R.K. et al. User Customization of the Feature Generator of an Asynchronous Brain Interface. Ann Biomed Eng 34, 1051–1060 (2006). https://doi.org/10.1007/s10439-006-9097-5

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  • DOI: https://doi.org/10.1007/s10439-006-9097-5

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