Filter bank canonical correlation analysis for implementing a high-speed SSVEP-based brain–computer interface

By Xiaogang Chen, Shangkai Gao, Tzyy-Ping Jung, Xiaorong Gao. Journal of Neural Engineering, 2015

727 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Neurology, Human-Computer Interaction

View Paper: https://www.semanticscholar.org/paper/ab5f4a6c431ba17e7a80bb914b82e3b8ac1b90e4

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

1. Tzyy-Ping Jung
2. Xiaogang Chen
3. Masaki Nakanishi
4. Yu-Te Wang
5. Xiaorong Gao
6. Yijun Wang
7. Bifta Sama Bari
8. Sabira Khatun

In Human-Computer Interaction

1. Tzyy-Ping Jung
2. Xiaorong Gao

Citations in the corpus

• Current Status, Challenges, and Possible Solutions of EEG-Based Brain-Computer Interface: A Comprehensive Review (2020, methodology): “The CORRCA approach performs substantially better than the state-of-art CCA process.”
• EEG Conformer: Convolutional Transformer for EEG Decoding and Visualization (2022, background): “The filter bank is further embedded for frequency rhythms in MI and steady-state visually evoked potential (SSVEP) classification [9].”
• Enhancing Detection of SSVEPs for a High-Speed Brain Speller Using Task-Related Component Analysis (2017, methodology): “study [30], the lower and upper cut-off frequencies of the m-th sub-band were set to m × 8 Hz and 90 Hz, respectively.”