BCI competition 2003-data set IIb: enhancing P300 wave detection using ICA-based subspace projections for BCI applications

By Neng Xu, Xiaorong Gao, Bo Hong, Xiaobo Miao, Shangkai Gao, Fusheng Yang. IEEE Transactions on Biomedical Engineering, 2004

299 citations recorded by the source corpus.

How researchers see this paper

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

Review of the BCI Competition IV (2012, methodology): “This worked very well in the BCI competition II where all winner articles have been published in volume 51 of IEEE Trans Biomed Eng (Blanchard and Blankertz, 2004; Bostanov, 2004; Kaper et al., 2004; Lemm et al., 2004; Mensh et al., 2004; Wang et al., 2004; Xu et al., 2004).”
Visual and Auditory Brain–Computer Interfaces (2014, methodology): “Another widely used spatial filtering method is Independent Component Analysis (ICA) [64, 128].”
xDAWN Algorithm to Enhance Evoked Potentials: Application to Brain–Computer Interface (2009, methodology): “Several methods, based on independent component analysis (ICA) [14]–[16], were thus proposed to enhance the SNR and remove the artifacts, e.g., [10] and [17].”