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 in | 2012 5th International Conference on Biomedical Engineering and Informatics pp. 563 - 567 |
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Main Author | |
Format | Conference Proceeding |
Language | English |
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. |
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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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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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