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