Z
Zheng Yang Chin
Researcher at Agency for Science, Technology and Research
Publications - 37
Citations - 2972
Zheng Yang Chin is an academic researcher from Agency for Science, Technology and Research. The author has contributed to research in topics: Motor imagery & Randomized controlled trial. The author has an hindex of 19, co-authored 36 publications receiving 2464 citations. Previous affiliations of Zheng Yang Chin include Institute for Infocomm Research Singapore.
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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
A large clinical study on the ability of stroke patients to use an EEG-based motor imagery brain-computer interface.
Kai Keng Ang,Cuntai Guan,Karen Sui Geok Chua,Beng Ti Ang,Christopher Wee Keong Kuah,Chuanchu Wang,Kok Soon Phua,Zheng Yang Chin,Haihong Zhang +8 more
TL;DR: The majority of stroke patients could use EEG-based motor imagery BCI, and no correlation was found between the accuracies of detecting motor imagery and their motor impairment in terms of Fugl-Meyer Assessment.
Proceedings ArticleDOI
Clinical study of neurorehabilitation in stroke using EEG-based motor imagery brain-computer interface with robotic feedback
Kai Keng Ang,Cuntai Guan,Karen Sui Geok Chua,Beng Ti Ang,Christopher Wee Keong Kuah,Chuanchu Wang,Kok Soon Phua,Zheng Yang Chin,Haihong Zhang +8 more
TL;DR: It is showed that a majority of hemiparetic stroke patients can operate EEG-based MI-BCI, and that EEG- based MI- BCI with robotic feedback neurorehabilitation is effective in restoring upper extremities motor function in stroke.
Journal ArticleDOI
A self-training semi-supervised SVM algorithm and its application in an EEG-based brain computer interface speller system
TL;DR: A self-training semi-supervised support vector machine (SVM) algorithm and its corresponding model selection method, which are designed to train a classifier with small training data are presented and the convergence of this algorithm is proved.