A New Discriminative Common Spatial Pattern Method for Motor Imagery Brain–Computer Interfaces

By Kavitha P. Thomas, Cuntai Guan, Chiew Tong Lau, A. P. Vinod, Kai Keng Ang. IEEE Transactions on Biomedical Engineering, 2009

309 citations recorded by the source corpus.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/4dc326e976e8efa84ab4f1f76075f946ffb132a8

How researchers see this paper

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

In Cellular and Molecular Neuroscience

1. Jinchang Ren
2. Jaime Zabalza
3. Huimin Zhao
4. Natasha M. J. Padfield
5. Valentin Masero Vargas

In Cognitive Neuroscience

1. Jinchang Ren
2. Jaime Zabalza
3. Huimin Zhao
4. Natasha M. J. Padfield
5. Valentin Masero Vargas

In Electrical and Electronic Engineering

1. Jinchang Ren
2. Jaime Zabalza
3. Huimin Zhao
4. Natasha M. J. Padfield
5. Valentin Masero Vargas

Citations in the corpus

• EEG-Based Brain-Computer Interfaces Using Motor-Imagery: Techniques and Challenges (2019, methodology): “To decrease the computational demands of FBCSP, discriminant filter bank CSP (DFBCSP) [88,92] was developed, which considers various overlapping frequency bands, and uses the Fisher ratio to analyze the band power of each sub-band in order to identify the most discriminant sub-bands.”