Abstract
This paper presents an application of subspace projection techniques to the classification of some EEG data for cognitive psychology.
The data used come from an “odd ball” experiment, where the subject was shown targets to which they had to respond by pressing a button. The target was shown with frequency 1/10 of the frequency with which irrelevant targets (to which no response was necessary) were shown. The data used in this study concern only the recordings when the target of interest was actually shown. This means that we have the recordings of 20 EEG channels, from 1393 trials, concerning 11 different subjects. However, in the classification experiments presented, we use only a single channel at a time. The classes we try to disambiguate are those of fast and slow response. The signals in each class are further subdivided into two halves, one used for training and one for testing.
Our purpose is to predict as soon as possible after the visual stimulus whether the subject is likely to succeed (ie respond fast) or fail (ie respond slowly) in his task.
We show that if each subject is treated individually, and if we use parts of the signal that are identical for the two classes and parts that are maximally different, we obtain results that are significantly better than the pure chance level. The results presented are preliminary results of work in progress.
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© 2001 Springer-Verlag Berlin Heidelberg
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Beltran, A.S., Petrou, M., Barrett, G., Dickson, B. (2001). Identification of electrical activity of the brain associated with changes in behavioural performance. In: Singh, S., Murshed, N., Kropatsch, W. (eds) Advances in Pattern Recognition — ICAPR 2001. ICAPR 2001. Lecture Notes in Computer Science, vol 2013. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44732-6_30
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DOI: https://doi.org/10.1007/3-540-44732-6_30
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