Literature DB >> 32199560

Detecting fatigue in car drivers and aircraft pilots by using non-invasive measures: The value of differentiation of sleepiness and mental fatigue.

Xinyun Hu1, Gabriel Lodewijks2.   

Abstract

INTRODUCTION: Fatigue is one of the most crucial factors that contribute to a decrease of the operating performance of aircraft pilots and car drivers and, as such, plays a dangerous role in transport safety. To reduce fatigue-related tragedies and to increase the quality of a healthy life, many studies have focused on exploring effective methods and psychophysiological indicators for detecting and monitoring fatigue. However, those fatigue indicators rose many discrepancies among simulator and field studies, due to the vague conceptualism of fatigue, per se, which hinders the development of fatigue monitoring devices.
METHOD: This paper aims to give psychological insight of the existing non-invasive measures for driver and pilot fatigue by differentiating sleepiness and mental fatigue. Such a study helps to improve research results for a wide range of researchers whose interests lie in the development of in-vehicle fatigue detection devices. First, the nature of fatigue for drivers/pilots is elucidated regarding fatigue types and fatigue responses, which reshapes our understanding of the fatigue issue in the transport industry. Secondly, the widely used objective neurophysiological methods, including electroencephalography (EEG), electrooculography (EOG), and electrocardiography (ECG), physical movement-based methods, vehicle-based methods, fitness-for-duty test as well as subjective methods (self-rating scales) are introduced. On the one hand, considering the difference between mental fatigue and sleepiness effects, the links between the objective and subjective indicators and fatigue are thoroughly investigated and reviewed. On the other hand, to better determine fatigue occurrence, a new combination of measures is recommended, as a single measure is not sufficient to yield a convincing benchmark of fatigue. Finally, since video-based techniques of measuring eye metrics offer a promising and practical method for monitoring operator fatigue, the relationship between fatigue and these eye metrics, that include blink-based, pupil-based, and saccade-based features, are also discussed. To realize a pragmatic fatigue detector for operators in the future, this paper concludes with a discussion on the future directions in terms of methodology of conducting operator fatigue research and fatigue analysis by using eye-related parameters.
Copyright © 2020 National Safety Council and Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Driver fatigue; EEG; Eye metrics; Fatigue detection; Pilot fatigue

Year:  2020        PMID: 32199560     DOI: 10.1016/j.jsr.2019.12.015

Source DB:  PubMed          Journal:  J Safety Res        ISSN: 0022-4375


  9 in total

1.  An Evaluation of the EEG Alpha-to-Theta and Theta-to-Alpha Band Ratios as Indexes of Mental Workload.

Authors:  Bujar Raufi; Luca Longo
Journal:  Front Neuroinform       Date:  2022-05-16       Impact factor: 3.739

2.  Increased Serum Levels of Proinflammatory Cytokines Are Accompanied by Fatigue in Military T-6A Texan II Instructor Pilots.

Authors:  Elizabeth G Damato; Seth J Fillioe; Seunghee P Margevicius; Ryan S Mayes; Jonathan E Somogyi; Ian S Vannix; Alireza Abdollahifar; Anthony M Turner; Lidia S Ilcus; Michael J Decker
Journal:  Front Physiol       Date:  2022-04-28       Impact factor: 4.755

3.  Cardiac Autonomic Control and Neural Arousal as Indexes of Fatigue in Professional Bus Drivers.

Authors:  Luigi I Lecca; Paolo Fadda; Gianfranco Fancello; Andrea Medda; Michele Meloni
Journal:  Saf Health Work       Date:  2022-02-05

Review 4.  Effects of Nutritional Interventions on Accuracy and Reaction Time with Relevance to Mental Fatigue in Sporting, Military, and Aerospace Populations: A Systematic Review and Meta-Analysis.

Authors:  Liam S Oliver; John P Sullivan; Suzanna Russell; Jonathan M Peake; Mitchell Nicholson; Craig McNulty; Vincent G Kelly
Journal:  Int J Environ Res Public Health       Date:  2021-12-28       Impact factor: 3.390

5.  Fatigue Monitoring Through Wearables: A State-of-the-Art Review.

Authors:  Neusa R Adão Martins; Simon Annaheim; Christina M Spengler; René M Rossi
Journal:  Front Physiol       Date:  2021-12-15       Impact factor: 4.566

6.  Assessment of Combination of Automated Pupillometry and Heart Rate Variability to Detect Driving Fatigue.

Authors:  Lin Shi; Leilei Zheng; Danni Jin; Zheng Lin; Qiaoling Zhang; Mao Zhang
Journal:  Front Public Health       Date:  2022-02-21

7.  Fatigue and Arousal Modulations Revealed by Saccade and Pupil Dynamics.

Authors:  Jui-Tai Chen; Ying-Chun Kuo; Tzu-Yu Hsu; Chin-An Wang
Journal:  Int J Environ Res Public Health       Date:  2022-07-28       Impact factor: 4.614

8.  An Explainable Machine Learning Approach Based on Statistical Indexes and SVM for Stress Detection in Automobile Drivers Using Electromyographic Signals.

Authors:  Olivia Vargas-Lopez; Carlos A Perez-Ramirez; Martin Valtierra-Rodriguez; Jesus J Yanez-Borjas; Juan P Amezquita-Sanchez
Journal:  Sensors (Basel)       Date:  2021-05-01       Impact factor: 3.576

Review 9.  Application of Eye Tracking Technology in Aviation, Maritime, and Construction Industries: A Systematic Review.

Authors:  Daniel Martinez-Marquez; Sravan Pingali; Kriengsak Panuwatwanich; Rodney A Stewart; Sherif Mohamed
Journal:  Sensors (Basel)       Date:  2021-06-23       Impact factor: 3.576

  9 in total

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