Real-time brain-computer interfacing: A preliminary study using Bayesian learning
- 1 January 2000
- journal article
- research article
- Published by Springer Nature in Medical & Biological Engineering & Computing
- Vol. 38 (1) , 56-61
- https://doi.org/10.1007/bf02344689
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.Keywords
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