MICROSLEEPS AND THEIR DETECTION FROM THE BIOLOGICAL SIGNALS
The result's identifiers
Result code in 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>
Alternative codes found
RIV/68407700:21730/17:00320855
Result on the web
<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>
Alternative languages
Result language
angličtina
Original language name
MICROSLEEPS AND THEIR DETECTION FROM THE BIOLOGICAL SIGNALS
Original language description
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.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
20104 - Transport engineering
Result continuities
Project
—
Continuities
V - Vyzkumna aktivita podporovana z jinych verejnych zdroju
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
DRIVE-CAR INTERACTION & SAFETY CONFERENCE
ISBN
978-80-01-06336-1
ISSN
—
e-ISSN
2336-5382
Number of pages
6
Pages from-to
32-37
Publisher name
České vysoké učení technické v Praze
Place of publication
Praha
Event location
Prague
Event date
Jun 16, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000431391000006