These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

150 related articles for article (PubMed ID: 33126235)

  • 1. Feature extraction of EEG signals based on functional data analysis and its application to recognition of driver fatigue state.
    Shangguan P; Qiu T; Liu T; Zou S; Liu Z; Zhang S
    Physiol Meas; 2021 Jan; 41(12):125004. PubMed ID: 33126235
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. 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]  

  • 4. 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]  

  • 5. EEG and ECG-Based Multi-Sensor Fusion Computing for Real-Time Fatigue Driving Recognition Based on Feedback Mechanism.
    Wang L; Song F; Zhou TH; Hao J; Ryu KH
    Sensors (Basel); 2023 Oct; 23(20):. PubMed ID: 37896480
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Driving behavior recognition using EEG data from a simulated car-following experiment.
    Yang L; Ma R; Zhang HM; Guan W; Jiang S
    Accid Anal Prev; 2018 Jul; 116():30-40. PubMed ID: 29174606
    [TBL] [Abstract][Full Text] [Related]  

  • 7. EEG-based driver fatigue detection using hybrid deep generic model.
    Phyo Phyo San ; Sai Ho Ling ; Rifai Chai ; Tran Y; Craig A; Hung Nguyen
    Annu Int Conf IEEE Eng Med Biol Soc; 2016 Aug; 2016():800-803. PubMed ID: 28268447
    [TBL] [Abstract][Full Text] [Related]  

  • 8. [Research on a successively increasing feature selection algorithm of EEG signal for driving fatigue based on SVM].
    Xie H; Yang S; Xia B; Yang W; Zhou N
    Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2013 Dec; 30(6):1321-5. PubMed ID: 24645619
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Driving fatigue detection based on brain source activity and ARMA model.
    Nadalizadeh F; Rajabioun M; Feyzi A
    Med Biol Eng Comput; 2024 Apr; 62(4):1017-1030. PubMed ID: 38117429
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Driving Fatigue Detection from EEG Using a Modified PCANet Method.
    Ma Y; Chen B; Li R; Wang C; Wang J; She Q; Luo Z; Zhang Y
    Comput Intell Neurosci; 2019; 2019():4721863. PubMed ID: 31396270
    [TBL] [Abstract][Full Text] [Related]  

  • 11. 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]  

  • 12. A cross-scenario and cross-subject domain adaptation method for driving fatigue detection.
    Luo Y; Liu W; Li H; Lu Y; Lu BL
    J Neural Eng; 2024 Jul; 21(4):. PubMed ID: 38838664
    [No Abstract]   [Full Text] [Related]  

  • 13. Research on Recognition Method of Driving Fatigue State Based on Sample Entropy and Kernel Principal Component Analysis.
    Ye B; Qiu T; Bai X; Liu P
    Entropy (Basel); 2018 Sep; 20(9):. PubMed ID: 33265790
    [TBL] [Abstract][Full Text] [Related]  

  • 14. 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]  

  • 15. 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]  

  • 16. Assessment of driver drowsiness using electroencephalogram signals based on multiple functional brain networks.
    Chen J; Wang H; Hua C
    Int J Psychophysiol; 2018 Nov; 133():120-130. PubMed ID: 30081067
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Comparison of Different Features and Classifiers for Driver Fatigue Detection Based on a Single EEG Channel.
    Hu J
    Comput Math Methods Med; 2017; 2017():5109530. PubMed ID: 28255330
    [TBL] [Abstract][Full Text] [Related]  

  • 18. 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]  

  • 19. 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]  

  • 20. EEG feature selection method based on decision tree.
    Duan L; Ge H; Ma W; Miao J
    Biomed Mater Eng; 2015; 26 Suppl 1():S1019-25. PubMed ID: 26405856
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.