On relationship among pulse, electrocardiogram signals and drowsiness

Drowsiness is an important factor in a large number of accidents. While significant research has been done into the physiological mechanisms that underlie sleep and the wake state, the available methods to identify drowsiness had more difficulty in practical applications. An objective measurement to...

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Published in2012 5th International Conference on Biomedical Engineering and Informatics pp. 563 - 567
Main Author Wang, Qi
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2012
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Abstract Drowsiness is an important factor in a large number of accidents. While significant research has been done into the physiological mechanisms that underlie sleep and the wake state, the available methods to identify drowsiness had more difficulty in practical applications. An objective measurement to evaluate sleep-wake state was studied based on the hidden information among electrocardiogram (ECG) and pulse signals that might offer insights into the nature of sleep. Pulse transit time (PTT) and Wavelet entropy (WE) were computed for twenty sets data which come from self-designed experiments to distinguish the two different states of mental. A significant increase of PTT and decrease of WE ware correlated with the state of drowsiness, and both feature t-test results were p<0.01, thus showing that these features have significant differences between awake and sleep state. Furthermore, the two characteristics can be recommended as objective indicators for distinguishing the human mental states.
AbstractList Drowsiness is an important factor in a large number of accidents. While significant research has been done into the physiological mechanisms that underlie sleep and the wake state, the available methods to identify drowsiness had more difficulty in practical applications. An objective measurement to evaluate sleep-wake state was studied based on the hidden information among electrocardiogram (ECG) and pulse signals that might offer insights into the nature of sleep. Pulse transit time (PTT) and Wavelet entropy (WE) were computed for twenty sets data which come from self-designed experiments to distinguish the two different states of mental. A significant increase of PTT and decrease of WE ware correlated with the state of drowsiness, and both feature t-test results were p<0.01, thus showing that these features have significant differences between awake and sleep state. Furthermore, the two characteristics can be recommended as objective indicators for distinguishing the human mental states.
Author Wang, Qi
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Snippet Drowsiness is an important factor in a large number of accidents. While significant research has been done into the physiological mechanisms that underlie...
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StartPage 563
SubjectTerms Accuracy
drowsiness
Electroencephalography
Entropy
Fatigue
Feature extraction
Physiology
pulse transit time (PTT)
Sleep
Vehicles
wavelet entropy (WE)
Wheels
Title On relationship among pulse, electrocardiogram signals and drowsiness
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