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Yu-Kai Wang
Researcher at University of Technology, Sydney
Publications - 76
Citations - 1164
Yu-Kai Wang is an academic researcher from University of Technology, Sydney. The author has contributed to research in topics: Computer science & Electroencephalography. The author has an hindex of 15, co-authored 61 publications receiving 704 citations. Previous affiliations of Yu-Kai Wang include University System of Taiwan & National Chiao Tung University.
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Journal ArticleDOI
EEG-Based Attention Tracking During Distracted Driving
TL;DR: The empirical results of this study demonstrate the feasibility of a practical system to continuously estimating cognitive attention through EEG spectra, and revealed that participants' cognitive attention and strategies dynamically changed between tasks to optimize the overall performance.
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Effects of repetitive SSVEPs on EEG complexity using multiscale inherent fuzzy entropy
TL;DR: EE relative complexity increases with stimulus times, a finding that reflects the strong habituation of brain systems, and indicates that multiscale inherent fuzzy entropy is superior to other competingMultiscale-based entropy methods.
Journal ArticleDOI
An EEG-Based Fatigue Detection and Mitigation System.
Kuan-Chih Huang,Kuan-Chih Huang,Teng-Yi Huang,Chun-Hsiang Chuang,Jung-Tai King,Yu-Kai Wang,Chin-Teng Lin,Chin-Teng Lin,Chin-Teng Lin,Tzyy-Ping Jung +9 more
TL;DR: Analytical results clearly demonstrate and validate the efficacy of this online closed-loop EEG-based fatigue detection and mitigation mechanism to identify cognitive lapses that may lead to catastrophic incidents in countless operational environments.
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Brain Electrodynamic and Hemodynamic Signatures Against Fatigue During Driving.
Chun-Hsiang Chuang,Zehong Cao,Zehong Cao,Jung-Tai King,Bing Syun Wu,Yu-Kai Wang,Chin-Teng Lin +6 more
TL;DR: The electrodynamic and hemodynamic signatures of fatigue fighting contribute to the understanding of the brain dynamics of driving fatigue and address driving safety issues through the maintenance of attention and behavioral performance.
Journal ArticleDOI
Multimodal Fuzzy Fusion for Enhancing the Motor-Imagery-Based Brain Computer Interface
Li-Wei Ko,Yi-Chen Lu,Humberto Bustince,Yu-Cheng Chang,Yang Chang,Javier Ferandez,Yu-Kai Wang,José Antonio Sanz,Graçaliz Pereira Dimuro,Chin-Teng Lin +9 more
TL;DR: A novel concept for enhancing brain-computer interface systems that adopts fuzzy integrals, especially in the fusion for classifying brain- computer interface commands is presented.