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Multimodal Features for Detection of Driver Stress and Fatigue: Review

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F20%3APU135930" target="_blank" >RIV/00216305:26220/20:PU135930 - isvavai.cz</a>

  • Alternative codes found

    RIV/61989592:15210/20:73600827

  • Result on the web

    <a href="https://ieeexplore.ieee.org/document/9031734" target="_blank" >https://ieeexplore.ieee.org/document/9031734</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/TITS.2020.2977762" target="_blank" >10.1109/TITS.2020.2977762</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Multimodal Features for Detection of Driver Stress and Fatigue: Review

  • Original language description

    Driver fatigue and stress significantly contribute to higher number of car accidents worldwide. Although, different detection approaches have been already commercialized and used by car producers (and third party companies), research activities in this field are still needed in order to increase the reliability of these alert systems. Also, in the context of automated driving, the driver mental state assessment will be an important part of cars in future. This paper presents state-of-the-art review of different approaches for driver fatigue and stress detection and evaluation. We describe in details various signals (biological, car and video) and derived features used for these tasks and we discuss their relevance and advantages. In order to make this review complete, we also describe different datasets, acquisition systems and experiment scenarios.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20201 - Electrical and electronic engineering

Result continuities

  • Project

    <a href="/en/project/TL01000216" target="_blank" >TL01000216: Complex physiological monitoring of the driver with respect to psychological factors affecting driving behavior</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2021

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS

  • ISSN

    1524-9050

  • e-ISSN

    1558-0016

  • Volume of the periodical

    22

  • Issue of the periodical within the volume

    6

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    20

  • Pages from-to

    3214-3233

  • UT code for WoS article

    000658360600001

  • EID of the result in the Scopus database

    2-s2.0-85107408203