Abstract
A brain-computer interface (BCI) is a device that provides an alternate non-muscular communication/control channel for individuals with severe neuromuscular disabilities. The P300 event-related potential has been demonstrated to be a reliable signal for controlling a BCI. The ultimate goal is to continue io improve the classification speed and accuracy of a P300-based BCI. The method of common spatial patterns (CSP) has proven success with sensorimotor rhythm-based BCIs and, with some modifications, can also be used to accurately classify the P300. The present method, common spatio-temporal patterns (CSTP), extends CSP by incorporating time-delay embedding to extract the prominent spatio-temporal patterns corresponding to each class. The results indicate that CSTP is capable of identifying a decomposition subspace that accurately classifies the P300. In addition, this subspace can be visualized to provide useful insight regarding the discriminable spatio-temporal characteristics of the P300
| Original language | American English |
|---|---|
| Journal | 2007 3rd International IEEE/EMBS Conference on Neural Engineering |
| DOIs | |
| State | Published - Jun 11 2007 |
Keywords
- P300 speller
- neural engineering
- spatio-temporal patterns
Disciplines
- Psychology
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