EEG-based classification of imaginary left and right foot movements using beta rebound
- PMID: 23757379
- DOI: 10.1016/j.clinph.2013.05.006
EEG-based classification of imaginary left and right foot movements using beta rebound
Abstract
Objective: The purpose of this study was to investigate cortical lateralization of event-related (de)synchronization during left and right foot motor imagery tasks and to determine classification accuracy of the two imaginary movements in a brain-computer interface (BCI) paradigm.
Methods: We recorded 31-channel scalp electroencephalograms (EEGs) from nine healthy subjects during brisk imagery tasks of left and right foot movements. EEG was analyzed with time-frequency maps and topographies, and the accuracy rate of classification between left and right foot movements was calculated.
Results: Beta rebound at the end of imagination (increase of EEG beta rhythm amplitude) was identified from the two EEGs derived from the right-shift and left-shift bipolar pairs at the vertex. This process enabled discrimination between right or left foot imagery at a high accuracy rate (maximum 81.6% in single trial analysis).
Conclusion: These data suggest that foot motor imagery has potential to elicit left-right differences in EEG, while BCI using the unilateral foot imagery can achieve high classification accuracy, similar to ordinary BCI, based on hand motor imagery.
Significance: By combining conventional discrimination techniques, the left-right discrimination of unilateral foot motor imagery provides a novel BCI system that could control a foot neuroprosthesis or a robotic foot.
Keywords: Beta rebound; Brain–computer interface (BCI); Electroencephalogram (EEG); Event-related desynchronization (ERD); Event-related synchronization (ERS); Motor imagery.
Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
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