Common spatio-time-frequency patterns for motor imagery-based brain machine interfaces

Authors:
Hiroshi Higashi;Toshihisa Tanaka
Affiliations:
Department of Electronic and Information Engineering, Tokyo University of Agriculture and Technology, Tokyo and RIKEN Brain Science Institute, Saitama, Japan;Department of Electronic and Information Engineering, Tokyo University of Agriculture and Technology, Tokyo and RIKEN Brain Science Institute, Saitama, Japan
Venue:
Computational Intelligence and Neuroscience
Year:
2013

Citing 3
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Brain-Computer Interface Operation of Robotic and Prosthetic Devices

Computer
Brain-computer interfaces for communication and control

Communications of the ACM
Mutual information-based selection of optimal spatial-temporal patterns for single-trial EEG-based BCIs

Pattern Recognition

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Abstract

For efficient decoding of brain activities in analyzing brain function with an application to brain machine interfacing (BMI), we address a problem of how to determine spatial weights (spatial patterns), bandpass filters (frequency patterns), and time windows (time patterns) by utilizing electroencephalogram (EEG) recordings. To find these parameters, we develop a data-driven criterion that is a natural extension of the so-called common spatial patterns (CSP) that are known to be effective features in BMI. We show that the proposed criterion can be optimized by an alternating procedure to achieve fast convergence. Experiments demonstrate that the proposed method can effectively extract discriminative features for a motor imagery-based BMI.