Maximum Signal Fraction Analysis for Enhancing Signal-to-Noise Ratio of EEG Signals in SSVEP-Based BCIs

Maximum Signal Fraction Analysis for Enhancing Signal-to-Noise Ratio of EEG Signals in SSVEP-Based BCIs

Various improved canonical correlation analysis (CCA) methods were developed for enhancing the performance of steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs). Among them, the method combining CCA spatial filters from sine-cosine references and individual templates...

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Bibliographic Details
Main Authors: Qingguo Wei, Shan Zhu, Yijun Wang, Xiaorong Gao, Hai Guo, Xuan Wu
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Brain-computer interface
steady-state visual evoked potential
maximum signal fraction analysis
canonical correlation analysis
signal-to-noise ratio
Online Access:https://ieeexplore.ieee.org/document/8746186/

Internet

https://ieeexplore.ieee.org/document/8746186/

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