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- W3021164131 abstract "Although many attempts have been made to detect driver’s drowsiness by ECG and pulse wave signals, it is not easy to record stable bio-signals while driving. In this study, we examined whether the driver's drowsiness can be detected from the respiration signal that can be acquired relatively easily with wearable clothing sensor. In 7 healthy subjects (five males and two females; age, 45 ± 9 y), respiration, ECG, and acceleration signals were recoded for a total of 2,359 min (137-468 min per subject) of driving with a smart shirt biometric sensor (Hexoskin). Minute-to-minute respiration amplitude and frequency and their variability were analyzed by complex demodulation between 0.05 and 0.45 Hz. The changes in the respiration parameters were analyzed in relation to the Dip & Waves, which are known to be a characteristic ECG R-R interval pattern associated with driver’s drowsiness. Neither respiratory amplitude nor frequency showed significant changes with Dip & Wave, but respiratory frequency variability increased progressively from 4 minutes before, peaked at Dip & Waves, and then decreased shortly thereafter. Our observations suggest the possibility that respiration signal obtained by wearable garment sensor may be used to detect driver’s drowsiness." @default.
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- W3021164131 date "2020-01-01" @default.
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- W3021164131 title "Changes in Respiration Pattern Preceding Drowsiness During Driving" @default.
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- W3021164131 doi "https://doi.org/10.5057/isase.2020-c000018" @default.
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