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MICROSLEEPS AND THEIR DETECTION FROM THE BIOLOGICAL SIGNALS

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21460%2F17%3A00320855" target="_blank" >RIV/68407700:21460/17:00320855 - isvavai.cz</a>

  • Nalezeny alternativní kódy

    RIV/68407700:21730/17:00320855

  • Výsledek na webu

    <a href="https://ojs.cvut.cz/ojs/index.php/APP/article/view/4011" target="_blank" >https://ojs.cvut.cz/ojs/index.php/APP/article/view/4011</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.14311/APP.2017.12.0032" target="_blank" >10.14311/APP.2017.12.0032</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    MICROSLEEPS AND THEIR DETECTION FROM THE BIOLOGICAL SIGNALS

  • Popis výsledku v původním jazyce

    Microsleeps (MS) are a frequently discussed topic due to their fatal consequences. Their detection is necessary for the purpose of sleep laboratories, where they provide an option for the quantifying rate of sleep deprivation level and objective evaluation of subjective sleepiness. Many studies are dealing with this topic for automotive usage to design a fatigue countermeasure device. We made a research of recent attitude to the development of the automated MS detection methods. We created an overview of several MS detection approaches based on the measurement of biological signals. We also summarized the changes in EEG, EOG and ECG signals, which have been published over the last few years. The reproducible changes in the entire EEG spectrum, primarily with the increased activity of delta and theta, were noticed during a transition to fatigue. There were observed changes of blinking rate and reduction of eye movements during the fatigue tasks. MS correspond with variations in the autonomic regulation of the cardiovascular function, which can be quantified by HRV parameters. The decrease in HR, VLF, and LF/HF before falling asleep was revealed. EEG signal, especially its slow wave activity, considered to be the most predictive and reliable for the level of alertness. In spite of the detection from EEG signal is the most common method, EOG based approaches can also be very efficient and more driver-friendly. Besides, the signal processing in the time domain can improve the detection accuracy of the short events like MS.

  • Název v anglickém jazyce

    MICROSLEEPS AND THEIR DETECTION FROM THE BIOLOGICAL SIGNALS

  • Popis výsledku anglicky

    Microsleeps (MS) are a frequently discussed topic due to their fatal consequences. Their detection is necessary for the purpose of sleep laboratories, where they provide an option for the quantifying rate of sleep deprivation level and objective evaluation of subjective sleepiness. Many studies are dealing with this topic for automotive usage to design a fatigue countermeasure device. We made a research of recent attitude to the development of the automated MS detection methods. We created an overview of several MS detection approaches based on the measurement of biological signals. We also summarized the changes in EEG, EOG and ECG signals, which have been published over the last few years. The reproducible changes in the entire EEG spectrum, primarily with the increased activity of delta and theta, were noticed during a transition to fatigue. There were observed changes of blinking rate and reduction of eye movements during the fatigue tasks. MS correspond with variations in the autonomic regulation of the cardiovascular function, which can be quantified by HRV parameters. The decrease in HR, VLF, and LF/HF before falling asleep was revealed. EEG signal, especially its slow wave activity, considered to be the most predictive and reliable for the level of alertness. In spite of the detection from EEG signal is the most common method, EOG based approaches can also be very efficient and more driver-friendly. Besides, the signal processing in the time domain can improve the detection accuracy of the short events like MS.

Klasifikace

  • Druh

    D - Stať ve sborníku

  • CEP obor

  • OECD FORD obor

    20104 - Transport engineering

Návaznosti výsledku

  • Projekt

  • Návaznosti

    V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Ostatní

  • Rok uplatnění

    2017

  • Kód důvěrnosti údajů

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

Údaje specifické pro druh výsledku

  • Název statě ve sborníku

    DRIVE-CAR INTERACTION & SAFETY CONFERENCE

  • ISBN

    978-80-01-06336-1

  • ISSN

  • e-ISSN

    2336-5382

  • Počet stran výsledku

    6

  • Strana od-do

    32-37

  • Název nakladatele

    České vysoké učení technické v Praze

  • Místo vydání

    Praha

  • Místo konání akce

    Prague

  • Datum konání akce

    16. 6. 2016

  • Typ akce podle státní příslušnosti

    WRD - Celosvětová akce

  • Kód UT WoS článku

    000431391000006