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Roberts, S J and Penny, W D 
ORCID: https://orcid.org/0000-0001-9064-1191
(2000)
Real-time brain-computer interfacing: A preliminary study using Bayesian learning.
Medical and Biological Engineering and Computing, 38 (1).
pp. 56-61.
ISSN 0140-0118
Abstract
Preliminary results from real-time 'brain-computer interface' experiments are presented. The analysis is based on autoregressive modelling of a single EEG channel coupled with classification and temporal smoothing under a Bayesian paradigm. It is shown that uncertainty in decisions is taken into account under such a formalism and that this may be used to reject uncertain samples, thus dramatically improving system performance. Using the strictest rejection method, a classification performance of 86.5 +/- 6.9% is achieved over a set of seven subjects in two-way cursor movement experiments.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | bayes theorem,brain,electroencephalography,humans,computer-assisted signal processing,user-computer interface |
| Faculty \ School: | Faculty of Social Sciences > School of Psychology |
| Depositing User: | Pure Connector |
| Date Deposited: | 23 Aug 2017 05:04 |
| Last Modified: | 19 Apr 2023 22:33 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/64643 |
| DOI: | 10.1007/BF02344689 |
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