Real-time brain-computer interfacing: A preliminary study using Bayesian learning

Roberts, S J and Penny, W D (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

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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: 27 Apr 2020 23:56
URI: https://ueaeprints.uea.ac.uk/id/eprint/64643
DOI: 10.1007/BF02344689

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