163 related articles for article (PubMed ID: 36991654)
1. An Electro-Oculogram (EOG) Sensor's Ability to Detect Driver Hypovigilance Using Machine Learning.
Murugan S; Sivakumar PK; Kavitha C; Harichandran A; Lai WC
Sensors (Basel); 2023 Mar; 23(6):. PubMed ID: 36991654
[TBL] [Abstract][Full Text] [Related]
2. Detection and analysis: driver state with electrocardiogram (ECG).
Murugan S; Selvaraj J; Sahayadhas A
Phys Eng Sci Med; 2020 Jun; 43(2):525-537. PubMed ID: 32524437
[TBL] [Abstract][Full Text] [Related]
3. Drowsiness Detection Using Ocular Indices from EEG Signal.
Tarafder S; Badruddin N; Yahya N; Nasution AH
Sensors (Basel); 2022 Jun; 22(13):. PubMed ID: 35808261
[TBL] [Abstract][Full Text] [Related]
4. Driver drowsiness detection based on classification of surface electromyography features in a driving simulator.
Mahmoodi M; Nahvi A
Proc Inst Mech Eng H; 2019 Apr; 233(4):395-406. PubMed ID: 30823855
[TBL] [Abstract][Full Text] [Related]
5. Driver Drowsiness Detection: A Machine Learning Approach on Skin Conductance.
Amidei A; Spinsante S; Iadarola G; Benatti S; Tramarin F; Pavan P; Rovati L
Sensors (Basel); 2023 Apr; 23(8):. PubMed ID: 37112345
[TBL] [Abstract][Full Text] [Related]
6. A Hybrid Approach to Detect Driver Drowsiness Utilizing Physiological Signals to Improve System Performance and Wearability.
Awais M; Badruddin N; Drieberg M
Sensors (Basel); 2017 Aug; 17(9):. PubMed ID: 28858220
[TBL] [Abstract][Full Text] [Related]
7. Physiological signal-based drowsiness detection using machine learning: Singular and hybrid signal approaches.
Hasan MM; Watling CN; Larue GS
J Safety Res; 2022 Feb; 80():215-225. PubMed ID: 35249601
[TBL] [Abstract][Full Text] [Related]
8. Validation and interpretation of a multimodal drowsiness detection system using explainable machine learning.
Hasan MM; Watling CN; Larue GS
Comput Methods Programs Biomed; 2024 Jan; 243():107925. PubMed ID: 38000319
[TBL] [Abstract][Full Text] [Related]
9. Event-related driver stress detection with smartphones among young novice drivers.
Zhou X; Ma L; Zhang W
Ergonomics; 2022 Aug; 65(8):1154-1172. PubMed ID: 34919031
[TBL] [Abstract][Full Text] [Related]
10. Multimodal analysis of electroencephalographic and electrooculographic signals.
ElSayed NE; Tolba AS; Rashad MZ; Belal T; Sarhan S
Comput Biol Med; 2021 Oct; 137():104809. PubMed ID: 34517160
[TBL] [Abstract][Full Text] [Related]
11. Non-Invasive Driver Drowsiness Detection System.
Siddiqui HUR; Saleem AA; Brown R; Bademci B; Lee E; Rustam F; Dudley S
Sensors (Basel); 2021 Jul; 21(14):. PubMed ID: 34300572
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. Information fusion and multi-classifier system for miner fatigue recognition in plateau environments based on electrocardiography and electromyography signals.
Chen S; Xu K; Yao X; Ge J; Li L; Zhu S; Li Z
Comput Methods Programs Biomed; 2021 Nov; 211():106451. PubMed ID: 34644668
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. 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]
16. Detecting slow eye movement for recognizing driver's sleep onset period with EEG features.
Yingying Jiao ; Bao-Liang Lu
Annu Int Conf IEEE Eng Med Biol Soc; 2016 Aug; 2016():4658-4661. PubMed ID: 28269313
[TBL] [Abstract][Full Text] [Related]
17. Detection of driver drowsiness level using a hybrid learning model based on ECG signals.
Xiong H; Yan Y; Sun L; Liu J; Han Y; Xu Y
Biomed Tech (Berl); 2024 Apr; 69(2):151-165. PubMed ID: 37823389
[TBL] [Abstract][Full Text] [Related]
18. Sleep stage classification using single-channel EOG.
Rahman MM; Bhuiyan MIH; Hassan AR
Comput Biol Med; 2018 Nov; 102():211-220. PubMed ID: 30170769
[TBL] [Abstract][Full Text] [Related]
19. Cross-Subject Zero Calibration Driver's Drowsiness Detection: Exploring Spatiotemporal Image Encoding of EEG Signals for Convolutional Neural Network Classification.
Paulo JR; Pires G; Nunes UJ
IEEE Trans Neural Syst Rehabil Eng; 2021; 29():905-915. PubMed ID: 33979288
[TBL] [Abstract][Full Text] [Related]
20. 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]
[Next] [New Search]