A Single-Trial P300 Detector Based on Symbolized EEG and Autoencoded-(1D)CNN to Improve ITR Performance in BCIs

In this paper, we propose a breakthrough single-trial P300 detector that maximizes the information translate rate (ITR) of the brain–computer interface (BCI), keeping high recognition accuracy performance. The architecture, designed to improve the portability of the algorithm, demonstrated full impl...

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Bibliographic Details
Published in:	Sensors (Basel, Switzerland) Vol. 21; no. 12; p. 3961
Main Authors:	De Venuto, Daniela, Mezzina, Giovanni
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 08.06.2021 MDPI
Subjects:	Accuracy autoencoder Automobile driving brain–computer interface (BCI) CNN Cognition & reasoning Competition Deep learning Discriminant analysis Electroencephalography Neural networks Neuromuscular diseases P300 Principal components analysis single-trial detection Wavelet transforms
ISSN:	1424-8220, 1424-8220
Online Access:	Get full text
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