K
Kai Keng Ang
Researcher at Nanyang Technological University
Publications - 195
Citations - 8986
Kai Keng Ang is an academic researcher from Nanyang Technological University. The author has contributed to research in topics: Motor imagery & Brain–computer interface. The author has an hindex of 38, co-authored 184 publications receiving 7046 citations. Previous affiliations of Kai Keng Ang include Institute for Infocomm Research Singapore & Tan Tock Seng Hospital.
Papers
More filters
Proceedings ArticleDOI
Filter Bank Common Spatial Pattern (FBCSP) in Brain-Computer Interface
TL;DR: A novel filter bank common spatial pattern (FBCSP) is proposed to perform autonomous selection of key temporal-spatial discriminative EEG characteristics and shows that FBCSP, using a particular combination feature selection and classification algorithm, yields relatively higher cross-validation accuracies compared to prevailing approaches.
Journal ArticleDOI
Filter Bank Common Spatial Pattern Algorithm on BCI Competition IV Datasets 2a and 2b.
TL;DR: The FBCSP algorithm performed relatively the best among the other submitted algorithms and yielded a mean kappa value of 0.569 and 0.600 across all subjects in Datasets 2a and 2b of the BCI Competition IV.
Journal ArticleDOI
A Randomized Controlled Trial of EEG-Based Motor Imagery Brain-Computer Interface Robotic Rehabilitation for Stroke.
Kai Keng Ang,Karen Sui Geok Chua,Kok Soon Phua,Chuanchu Wang,Zheng Yang Chin,Christopher Wee Keong Kuah,Wilson Low,Cuntai Guan +7 more
TL;DR: BCI-Manus therapy is effective and safe for arm rehabilitation after severe poststroke hemiparesis and the correlation of rBSI with motor improvements suggests that the rBSi can be used as a prognostic measure for BCI-based stroke rehabilitation.
Journal ArticleDOI
Optimizing the Channel Selection and Classification Accuracy in EEG-Based BCI
TL;DR: The proposed SCSP channel selection algorithm significantly reduced the number of channels, and outperformed existing channel selection methods based on Fisher criterion, mutual information, support vector machine, common spatial pattern, and regularized common spatialpattern in classification accuracy.
Journal ArticleDOI
A New Discriminative Common Spatial Pattern Method for Motor Imagery Brain–Computer Interfaces
TL;DR: A new discriminative filter bank (FB) common spatial pattern algorithm to extract subject-specific FB for MI classification enhances the classification accuracy in BCI competition III dataset IVa and competition IV dataset IIb.