Improve P300 Speller Performance by Changing Stimulus Onset Asynchrony (SOA) Without Retraining the Subject-Independent Model

Improve P300 Speller Performance by Changing Stimulus Onset Asynchrony (SOA) Without Retraining the Subject-Independent Model

P300 speller is a famous brain-computer interface (BCI) method, which translates mental attention by identifying the event-related potentials evoked by target stimulus. To improve its efficiency, subject-independent classification models and dynamical stopping strategies have been introduced into P3...

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Bibliographic Details
Main Authors: Yuqi Xue, Jiabei Tang, Feng He, Minpeng Xu, Hongzhi Qi
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Brain Computer Interface
P300 Speller
Stimulus Onset Asynchrony
Subject-Independent Model
Online Access:https://ieeexplore.ieee.org/document/8830444/

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