MICROSLEEPS AND THEIR DETECTION FROM THE BIOLOGICAL SIGNALS
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...
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Czech Technical University in Prague
2017-12-01
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| Series: | Acta Polytechnica CTU Proceedings |
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| Online Access: | https://ojs.cvut.cz/ojs/index.php/APP/article/view/4011 |
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| author | Martin Holub Martina Šrutová Lenka Lhotská |
| author_facet | Martin Holub Martina Šrutová Lenka Lhotská |
| author_sort | Martin Holub |
| collection | DOAJ |
| 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. |
| format | Article |
| id | doaj-art-a2d4de52790e41db9ae470f0a64493bd |
| institution | Kabale University |
| issn | 2336-5382 |
| language | English |
| publishDate | 2017-12-01 |
| publisher | Czech Technical University in Prague |
| record_format | Article |
| series | Acta Polytechnica CTU Proceedings |
| spelling | doaj-art-a2d4de52790e41db9ae470f0a64493bd2025-08-20T03:35:55ZengCzech Technical University in PragueActa Polytechnica CTU Proceedings2336-53822017-12-01120323710.14311/APP.2017.12.00323535MICROSLEEPS AND THEIR DETECTION FROM THE BIOLOGICAL SIGNALSMartin Holub0Martina Šrutová1Lenka Lhotská2Department of Cybernetics, FEE CTU in Prague Karlovo nám. 13, Praha 2, 121 35, Czech RepublicDepartment of Cybernetics, FEE CTU in Prague Karlovo nám. 13, Praha 2, 121 35, Czech RepublicDepartment of Cybernetics, FEE CTU in Prague Karlovo nám. 13, Praha 2, 121 35, Czech RepublicMicrosleeps (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.https://ojs.cvut.cz/ojs/index.php/APP/article/view/4011microsleep, automatic detection, detection methods, EOG, EEG, EKG |
| spellingShingle | Martin Holub Martina Šrutová Lenka Lhotská MICROSLEEPS AND THEIR DETECTION FROM THE BIOLOGICAL SIGNALS Acta Polytechnica CTU Proceedings microsleep, automatic detection, detection methods, EOG, EEG, EKG |
| title | MICROSLEEPS AND THEIR DETECTION FROM THE BIOLOGICAL SIGNALS |
| title_full | MICROSLEEPS AND THEIR DETECTION FROM THE BIOLOGICAL SIGNALS |
| title_fullStr | MICROSLEEPS AND THEIR DETECTION FROM THE BIOLOGICAL SIGNALS |
| title_full_unstemmed | MICROSLEEPS AND THEIR DETECTION FROM THE BIOLOGICAL SIGNALS |
| title_short | MICROSLEEPS AND THEIR DETECTION FROM THE BIOLOGICAL SIGNALS |
| title_sort | microsleeps and their detection from the biological signals |
| topic | microsleep, automatic detection, detection methods, EOG, EEG, EKG |
| url | https://ojs.cvut.cz/ojs/index.php/APP/article/view/4011 |
| work_keys_str_mv | AT martinholub microsleepsandtheirdetectionfromthebiologicalsignals AT martinasrutova microsleepsandtheirdetectionfromthebiologicalsignals AT lenkalhotska microsleepsandtheirdetectionfromthebiologicalsignals |