188 related articles for article (PubMed ID: 35249601)
1. 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]
2. 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]
3. Sensitivity and specificity of the driver sleepiness detection methods using physiological signals: A systematic review.
Watling CN; Mahmudul Hasan M; Larue GS
Accid Anal Prev; 2021 Feb; 150():105900. PubMed ID: 33285449
[TBL] [Abstract][Full Text] [Related]
4. Convergent validity of video-based observer rating of drowsiness, against subjective, behavioral, and physiological measures.
Uchiyama Y; Sawai S; Omi T; Yamauchi K; Tamura K; Sakata T; Nakajima K; Sakai H
PLoS One; 2023; 18(5):e0285557. PubMed ID: 37155637
[TBL] [Abstract][Full Text] [Related]
5. 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]
6. A hybrid approach for driver drowsiness detection utilizing practical data to improve performance system and applicability.
Khanehshenas F; Mazloumi A; Nahvi A; Nickabadi A; Sadeghniiat K; Rahimiforoushani A; Aghamalizadeh A
Work; 2024; 77(4):1165-1177. PubMed ID: 38007634
[TBL] [Abstract][Full Text] [Related]
7. The detection of drowsiness using a driver monitoring system.
Schwarz C; Gaspar J; Miller T; Yousefian R
Traffic Inj Prev; 2019; 20(sup1):S157-S161. PubMed ID: 31381433
[No Abstract] [Full Text] [Related]
8. Drowsiness measures for commercial motor vehicle operations.
Sparrow AR; LaJambe CM; Van Dongen HPA
Accid Anal Prev; 2019 May; 126():146-159. PubMed ID: 29704947
[TBL] [Abstract][Full Text] [Related]
9. 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]
10. Multi-sensor driver monitoring for drowsiness prediction.
Schwarz C; Gaspar J; Yousefian R
Traffic Inj Prev; 2023; 24(sup1):S100-S104. PubMed ID: 37267009
[TBL] [Abstract][Full Text] [Related]
11. 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]
12. Feeling sleepy? stop driving-awareness of fall asleep crashes.
Anderson C; Cai AWT; Lee ML; Horrey WJ; Liang Y; O'Brien CS; Czeisler CA; Howard ME
Sleep; 2023 Nov; 46(11):. PubMed ID: 37158173
[TBL] [Abstract][Full Text] [Related]
13. A Review of EEG Signal Features and their Application in Driver Drowsiness Detection Systems.
Stancin I; Cifrek M; Jovic A
Sensors (Basel); 2021 May; 21(11):. PubMed ID: 34070732
[TBL] [Abstract][Full Text] [Related]
14. The utility of automated measures of ocular metrics for detecting driver drowsiness during extended wakefulness.
Jackson ML; Kennedy GA; Clarke C; Gullo M; Swann P; Downey LA; Hayley AC; Pierce RJ; Howard ME
Accid Anal Prev; 2016 Feb; 87():127-33. PubMed ID: 26687538
[TBL] [Abstract][Full Text] [Related]
15. Effects of scheduled manual driving on drowsiness and response to take over request: A simulator study towards understanding drivers in automated driving.
Wu Y; Kihara K; Takeda Y; Sato T; Akamatsu M; Kitazaki S
Accid Anal Prev; 2019 Mar; 124():202-209. PubMed ID: 30665055
[TBL] [Abstract][Full Text] [Related]
16. Drowsiness Detection Based on Intelligent Systems with Nonlinear Features for Optimal Placement of Encephalogram Electrodes on the Cerebral Area.
Hong S; Baek HJ
Sensors (Basel); 2021 Feb; 21(4):. PubMed ID: 33578747
[TBL] [Abstract][Full Text] [Related]
17. Adapting artificial neural networks to a specific driver enhances detection and prediction of drowsiness.
Jacobé de Naurois C; Bourdin C; Bougard C; Vercher JL
Accid Anal Prev; 2018 Dec; 121():118-128. PubMed ID: 30243040
[TBL] [Abstract][Full Text] [Related]
18. I think I'm sleepy, therefore I am - Awareness of sleepiness while driving: A systematic review.
Cai AWT; Manousakis JE; Lo TYT; Horne JA; Howard ME; Anderson C
Sleep Med Rev; 2021 Dec; 60():101533. PubMed ID: 34461582
[TBL] [Abstract][Full Text] [Related]
19. System and Method for Driver Drowsiness Detection Using Behavioral and Sensor-Based Physiological Measures.
Bajaj JS; Kumar N; Kaushal RK; Gururaj HL; Flammini F; Natarajan R
Sensors (Basel); 2023 Jan; 23(3):. PubMed ID: 36772333
[TBL] [Abstract][Full Text] [Related]
20. Prediction of drowsiness events in night shift workers during morning driving.
Liang Y; Horrey WJ; Howard ME; Lee ML; Anderson C; Shreeve MS; O'Brien CS; Czeisler CA
Accid Anal Prev; 2019 May; 126():105-114. PubMed ID: 29126462
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
