Nothing Special   »   [go: up one dir, main page]

Soares et al., 2020 - Google Patents

Driving simulator experiments to study drowsiness: A systematic review

Soares et al., 2020

Document ID
658516431649914671
Author
Soares S
Ferreira S
Couto A
Publication year
Publication venue
Traffic injury prevention

External Links

Snippet

Abstract Objective: The National Highway Traffic Safety Administration in the USA estimated that the effects of drowsiness while driving led to approximately 72,000 crashes, 44,000 injuries, and 800 deaths in 2013. Keeping this in mind, the risk and injuries of drowsy driving …
Continue reading at www.tandfonline.com (other versions)

Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/16—Devices for psychotechnics; Testing reaction times; Devices for evaluating the psychological state
    • A61B5/165—Evaluating the state of mind, e.g. depression, anxiety
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/16—Devices for psychotechnics; Testing reaction times; Devices for evaluating the psychological state
    • A61B5/18—Devices for psychotechnics; Testing reaction times; Devices for evaluating the psychological state for vehicle drivers or machine operators
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/16—Devices for psychotechnics; Testing reaction times; Devices for evaluating the psychological state
    • A61B5/168—Evaluating attention deficit, hyperactivity
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/34—Computer-assisted medical diagnosis or treatment, e.g. computerised prescription or delivery of medication or diets, computerised local control of medical devices, medical expert systems or telemedicine
    • G06F19/345—Medical expert systems, neural networks or other automated diagnosis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/34—Computer-assisted medical diagnosis or treatment, e.g. computerised prescription or delivery of medication or diets, computerised local control of medical devices, medical expert systems or telemedicine
    • G06F19/3487—Medical report generation
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/16—Devices for psychotechnics; Testing reaction times; Devices for evaluating the psychological state
    • A61B5/164—Lie detection
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/04—Detecting, measuring or recording bioelectric signals of the body of parts thereof
    • A61B5/0476—Electroencephalography
    • A61B5/0484—Electroencephalography using evoked response

Similar Documents

Publication Publication Date Title
Soares et al. Driving simulator experiments to study drowsiness: A systematic review
Ma et al. The relationship between drivers’ cognitive fatigue and speed variability during monotonous daytime driving
Heikoop et al. Effects of platooning on signal-detection performance, workload, and stress: A driving simulator study
Howard et al. Specific sleepiness symptoms are indicators of performance impairment during sleep deprivation
Brown Driver fatigue
Schleicher et al. Blinks and saccades as indicators of fatigue in sleepiness warnings: looking tired?
Morris et al. Lane heading difference: An innovative model for drowsy driving detection using retrospective analysis around curves
Jackson et al. Slow eyelid closure as a measure of driver drowsiness and its relationship to performance
Hassib et al. Detecting and influencing driver emotions using psycho-physiological sensors and ambient light
Körber et al. Potential individual differences regarding automation effects in automated driving
Anund et al. Observer rated sleepiness and real road driving: an explorative study
Caponecchia et al. Drowsiness and driving performance on commuter trips
Yan et al. Driver’s mental workload prediction model based on physiological indices
Bier et al. How to measure monotony-related fatigue? A systematic review of fatigue measurement methods for use on driving tests
McDonnell et al. This is your brain on autopilot: Neural indices of driver workload and engagement during partial vehicle automation
Wang et al. Can variations in visual behavior measures be good predictors of driver sleepiness? A real driving test study
Song et al. Fatigue in younger and older drivers: effectiveness of an alertness-maintaining task
Lee et al. Individual differences in ocular level empathic accuracy ability: The predictive power of fantasy empathy
Zhang et al. Electrophysiological frequency domain analysis of driver passive fatigue under automated driving conditions
Li et al. Physiological signal analysis for fatigue level of experienced and inexperienced drivers
Abbood et al. Prediction of driver fatigue: Approaches and open challenges
Murata Proposal of a method to predict subjective rating on drowsiness using physiological and behavioral measures
Bashiri et al. Quantitative EEG features selection in the classification of attention and response control in the children and adolescents with attention deficit hyperactivity disorder
Shi et al. Assessment of combination of automated pupillometry and heart rate variability to detect driving fatigue
Hidalgo-Gadea et al. Towards better microsleep predictions in fatigued drivers: exploring benefits of personality traits and IQ