Name
Title | ||
|---|---|---|
Relative Wavelet Entropy Complex Network for Improving EEG-Based Fatigue Driving Classification |
Abstract | ||
|---|---|---|
Detecting fatigue driving from electroencephalogram (EEG) signals constitutes a challenging problem of continuing interest since fatigue driving has caused the majority of traffic accidents. We carry out a simulated driving experiment for EEG data acquisition. Then, we calculate the wavelet entropy under the alert and fatigue state, respectively, and find that the wavelet entropy gets an acceptabl... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TIM.2018.2865842 | IEEE Transactions on Instrumentation and Measurement |
Keywords | Field | DocType |
Electroencephalography,Entropy,Fatigue,Complex networks,Feature extraction,Data acquisition,Energy resolution | Feature vector,Pattern recognition,Data acquisition,Communication channel,Electronic engineering,Feature extraction,Complex network,Artificial intelligence,Linear discriminant analysis,Electroencephalography,Mathematics,Wavelet entropy | Journal |
Volume | Issue | ISSN |
68 | 7 | 0018-9456 |
Citations | PageRank | References |
1 | 0.34 | 0 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhongke Gao | 1 | 30 | 8.64 |
| Shan Li | 2 | 15 | 2.34 |
| qing cai | 3 | 60 | 8.64 |
| Wei-Dong Dang | 4 | 13 | 3.24 |
| Yuxuan Yang | 5 | 63 | 5.78 |
| Chaoxu Mu | 6 | 271 | 18.80 |
| Pan Hui | 7 | 4577 | 309.30 |