Comparing Classification Methods for Asynchronous Brain-computer Interfaces
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2011-08-29
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en
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Abstract
In the field of Brain-Computer Interfacing, the asynchronous approach adds a new ”no movement” class to the classic trial-based synchronous approach. This ”no movement” class is very unbalanced (most of the data will belong to this class) and therefore causes a major classification obstacle. This study investigates the suitability of
different classification methods for use in an asynchronous Brain-Computer Interface. We used a Guitar Hero like game to gather EEG data to compare the classification methods using the Readiness Potential in different movement conditions. Based on the results, we recommend to use a hierarchical method that first classifies between
movement and no movement, and only if movement is detected, classifies between left and right movement.
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Faculteit der Sociale Wetenschappen