150 related articles for article (PubMed ID: 37838152)
1. Real driving environment EEG-based detection of driving fatigue using the wavelet scattering network.
Wang F; Chen D; Yao W; Fu R
J Neurosci Methods; 2023 Dec; 400():109983. PubMed ID: 37838152
[TBL] [Abstract][Full Text] [Related]
2. Classifying Driving Fatigue by Using EEG Signals.
Zeng C; Mu Z; Wang Q
Comput Intell Neurosci; 2022; 2022():1885677. PubMed ID: 35371255
[TBL] [Abstract][Full Text] [Related]
3. End-to-end fatigue driving EEG signal detection model based on improved temporal-graph convolution network.
Jia H; Xiao Z; Ji P
Comput Biol Med; 2023 Jan; 152():106431. PubMed ID: 36543007
[TBL] [Abstract][Full Text] [Related]
4. A novel deep-learning model based on τ-shaped convolutional network (τNet) with long short-term memory (LSTM) for physiological fatigue detection from EEG and EOG signals.
He L; Zhang L; Lin X; Qin Y
Med Biol Eng Comput; 2024 Jun; 62(6):1781-1793. PubMed ID: 38374416
[TBL] [Abstract][Full Text] [Related]
5. Exploring the fatigue affecting electroencephalography based functional brain networks during real driving in young males.
Chen J; Wang H; Wang Q; Hua C
Neuropsychologia; 2019 Jun; 129():200-211. PubMed ID: 30995455
[TBL] [Abstract][Full Text] [Related]
6. Using long short term memory and convolutional neural networks for driver drowsiness detection.
Quddus A; Shahidi Zandi A; Prest L; Comeau FJE
Accid Anal Prev; 2021 Jun; 156():106107. PubMed ID: 33848710
[TBL] [Abstract][Full Text] [Related]
7. EEG-Based Spatio-Temporal Convolutional Neural Network for Driver Fatigue Evaluation.
Gao Z; Wang X; Yang Y; Mu C; Cai Q; Dang W; Zuo S
IEEE Trans Neural Netw Learn Syst; 2019 Sep; 30(9):2755-2763. PubMed ID: 30640634
[TBL] [Abstract][Full Text] [Related]
8. AGL-Net: An Efficient Neural Network for EEG-Based Driver Fatigue Detection.
Fang W; Tang L; Pan J
J Integr Neurosci; 2023 Oct; 22(6):146. PubMed ID: 38176922
[TBL] [Abstract][Full Text] [Related]
9. Application of Graph Neural Network in Driving Fatigue Detection Based on EEG Signals.
Mu Z; Jin L; Yin J; Wang Q
Comput Intell Neurosci; 2022; 2022():9775784. PubMed ID: 36052050
[TBL] [Abstract][Full Text] [Related]
10. A Novel Fatigue Driving State Recognition and Warning Method Based on EEG and EOG Signals.
Liu L; Ji Y; Gao Y; Ping Z; Kuang L; Li T; Xu W
J Healthc Eng; 2021; 2021():7799793. PubMed ID: 34853672
[TBL] [Abstract][Full Text] [Related]
11. Research on the Relationship between Reaction Ability and Mental State for Online Assessment of Driving Fatigue.
Guo M; Li S; Wang L; Chai M; Chen F; Wei Y
Int J Environ Res Public Health; 2016 Nov; 13(12):. PubMed ID: 27886139
[No Abstract] [Full Text] [Related]
12. Automated Detection of Driver Fatigue Based on AdaBoost Classifier with EEG Signals.
Hu J
Front Comput Neurosci; 2017; 11():72. PubMed ID: 28824409
[No Abstract] [Full Text] [Related]
13. InstanceEasyTL: An Improved Transfer-Learning Method for EEG-Based Cross-Subject Fatigue Detection.
Zeng H; Zhang J; Zakaria W; Babiloni F; Gianluca B; Li X; Kong W
Sensors (Basel); 2020 Dec; 20(24):. PubMed ID: 33348823
[TBL] [Abstract][Full Text] [Related]
14. Real-time EEG-based detection of fatigue driving danger for accident prediction.
Wang H; Zhang C; Shi T; Wang F; Ma S
Int J Neural Syst; 2015 Mar; 25(2):1550002. PubMed ID: 25541095
[TBL] [Abstract][Full Text] [Related]
15. A LightGBM-Based EEG Analysis Method for Driver Mental States Classification.
Zeng H; Yang C; Zhang H; Wu Z; Zhang J; Dai G; Babiloni F; Kong W
Comput Intell Neurosci; 2019; 2019():3761203. PubMed ID: 31611912
[TBL] [Abstract][Full Text] [Related]
16. A recurrence network-based convolutional neural network for fatigue driving detection from EEG.
Gao ZK; Li YL; Yang YX; Ma C
Chaos; 2019 Nov; 29(11):113126. PubMed ID: 31779352
[TBL] [Abstract][Full Text] [Related]
17. ADTIDO: Detecting the Tired Deck Officer with Fusion Feature Methods.
Li C; Fu Y; Ouyang R; Liu Y; Hou X
Sensors (Basel); 2022 Aug; 22(17):. PubMed ID: 36080966
[TBL] [Abstract][Full Text] [Related]
18. A generative adaptive convolutional neural network with attention mechanism for driver fatigue detection with class-imbalanced and insufficient data.
He L; Zhang L; Sun Q; Lin X
Behav Brain Res; 2024 Apr; 464():114898. PubMed ID: 38382711
[TBL] [Abstract][Full Text] [Related]
19. Mobile healthcare for automatic driving sleep-onset detection using wavelet-based EEG and respiration signals.
Lee BG; Lee BL; Chung WY
Sensors (Basel); 2014 Sep; 14(10):17915-36. PubMed ID: 25264954
[TBL] [Abstract][Full Text] [Related]
20. Partial directed coherence based graph convolutional neural networks for driving fatigue detection.
Zhang W; Wang F; Wu S; Xu Z; Ping J; Jiang Y
Rev Sci Instrum; 2020 Jul; 91(7):074713. PubMed ID: 32752838
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
