Hong Wang
Northeastern University (China)
83 Papers
195 Citations
Hong Wang is an academic researcher from Northeastern University (China). The author has contributed to research in topics: Computer science & Feature extraction. The author has an hindex of 16, co-authored 77 publications. Previous affiliations of Hong Wang include Northeastern University & Leibniz Institute for Neurobiology.
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Papers
LTD and LTP induced by transcranial magnetic stimulation in auditory cortex.
TL;DR: Using a system capable of relatively localized and rapid- rate transcranial magnetic stimulation (rTMS), evoked trains of complex spikes were studied in rodent auditory cortex and resulted in long-term potentiation (LTP)-like, and more durable long- term depression (LTD)-like changes in evoked spike rate.
215
Automated Detection of Driver Fatigue Based on Entropy and Complexity Measures
Chi Zhang,Hong Wang,Rongrong Fu +2 more
TL;DR: A real-time method based on various entropy and complexity measures for detection and identification of driving fatigue from recorded electroencephalogram, electromyogram, and electrooculogram signals is presented and is valuable for the application of avoiding some traffic accidents caused by driver's fatigue.
214
Dynamic driver fatigue detection using hidden Markov model in real driving condition
Rongrong Fu,Hong Wang,Wenbo Zhao +2 more
TL;DR: A dynamic fatigue detection model based on Hidden Markov Model (HMM) provides an effective way in detecting driver fatigue and the posterior of fatigue can be gotten dynamically by this HMM-based fatigue recognition method.
207
Detection of driving fatigue by using noncontact emg and ecg signals measurement system
Rongrong Fu,Hong Wang +1 more
TL;DR: The results showed that the method proposed can give well performance in distinguishing the normal state and fatigue state in the noncontact, onboard vehicle drivers' fatigue detection system.
138
Real-time EEG-based detection of fatigue driving danger for accident prediction
TL;DR: A real-time electroencephalogram (EEG)-based detection method of the potential danger during fatigue driving, which shows the overall functional connectivity of the subjects is weakened after long time driving tasks.
97