Abstract
Different types of mental activity are utilised as an input in Brain-Computer Interface (BCI) systems. One such activity type is based on Event-Related Potentials (ERPs). The characteristics of ERPs are not visible in single-trials, thus averaging over a number of trials is necessary before the signals become usable. An improvement in ERP-based BCI operation and system usability could be obtained if the use of single-trial ERP data was possible. The method of Independent Component Analysis (ICA) can be utilised to separate single-trial recordings of ERP data into components that correspond to ERP characteristics, background electroencephalogram (EEG) activity and other components with non-cerebral origin. Choice of specific components and their use to reconstruct "denoised" single-trial data could improve the signal quality, thus allowing the successful use of single-trial data without the need for averaging. This paper assesses single-trial ERP signals reconstructed using a selection of estimated components from the application of ICA on the raw ERP data. Signal improvement is measured using Contrast-To-Noise measures. It was found that such analysis improves the signal quality in all single-trials.
Original language | English |
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Title of host publication | AISB 2008 Convention |
Subtitle of host publication | Communication, Interaction and Social Intelligence - Proceedings of the AISB 2008 Symposium on Brain Computer Interfaces and Human Computer Interaction: A Convergence of Ideas |
Pages | 13-19 |
Number of pages | 7 |
Volume | 5 |
Publication status | Published - 1 Dec 2008 |
Externally published | Yes |
Event | AISB 2008 Symposium on Brain Computer Interfaces and Human Computer Interaction: A Convergence of Ideas - Aberdeen, United Kingdom Duration: 1 Apr 2008 → 4 Apr 2008 |
Conference
Conference | AISB 2008 Symposium on Brain Computer Interfaces and Human Computer Interaction: A Convergence of Ideas |
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Country/Territory | United Kingdom |
City | Aberdeen |
Period | 1/04/08 → 4/04/08 |