H
Haihong Zhang
Researcher at Agency for Science, Technology and Research
Publications - 118
Citations - 6874
Haihong Zhang is an academic researcher from Agency for Science, Technology and Research. The author has contributed to research in topics: Motor imagery & Mutual information. The author has an hindex of 33, co-authored 114 publications receiving 5938 citations. Previous affiliations of Haihong Zhang include Institute for Infocomm Research Singapore.
Papers
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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
Temporal classification of multichannel near-infrared spectroscopy signals of motor imagery for developing a brain-computer interface.
Ranganatha Sitaram,Haihong Zhang,Cuntai Guan,M. Thulasidas,Yoko Hoshi,Akihiro Ishikawa,Koji Shimizu,Niels Birbaumer +7 more
TL;DR: Results indicate potential application of NIRS in the development of BCIs and present results of signal analysis indicating that there exist distinct patterns of hemodynamic responses which could be utilized in a pattern classifier towards developing a BCI.
Journal ArticleDOI
A Brain Controlled Wheelchair to Navigate in Familiar Environments
Brice Rebsamen,Cuntai Guan,Haihong Zhang,Chuanchu Wang,Chee Leong Teo,Marcelo H. Ang,Etienne Burdet +6 more
TL;DR: The brain controlled wheelchair (BCW) described in this paper enabled the users to move to various locations in less time and with significantly less control effort than other control strategies proposed in the literature.
Journal ArticleDOI
An EEG-Based BCI System for 2-D Cursor Control by Combining Mu/Beta Rhythm and P300 Potential
TL;DR: This work proposes a new approach by combining two brain signals including Mu/Beta rhythm during motor imagery and P300 potential to address two-dimensional cursor control in EEG-based brain-computer interfaces.