• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.18 no.7
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• pp.535-540
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• 2006

This study was performed In evaluate sleep efficiencies and conditions for comfortable sleep based on the analysis of Physiological signals under variations in thermal conditions. Five female subjects who have similar life cycle and sleep patterns were participated for the sleep experiment. It was checked whether they had a good sleep before the night of experiment. EEGs were obtained from C3-A2 and C4-A1 electrode sites and EOGs were acquired from LOC (left outer canthus) and ROC (right outer canthus) for REM sleep detection. Sleep stages were classified, then TST (total sleep time), SWS (slow wave sleep) latency and SWS/TST were calculated for the evaluation of sleep efficiencies on thermal conditions. TST was defined as an amount of time from sleep stage 1 to wakeup. SWS latency was from light off time to sleep stage 3 and percentage of SWS over TST was calculated for the evaluation of sleep quality and comfort sleep under thermal conditions. As result, the condition which raise a room temperature provided comfortable sleep.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.18 no.1
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• pp.1-6
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• 2006

This study was performed to evaluate sleep efficiencies and conditions for comfortable sleep based on the analysis of EEGs and MST under four thermals conditions. Five female subjects who have similar life cycle and sleep patterns were participated for the sleep experiment. Their age was from 20 to 22 years old. They were healthy, and had regular sleep with consistent bed and wakeup time. It was checked whether they had a good sleep before the night of experiment. Experiments were performed in an environmental chamber of $4.1\times4.9\times2.7m$ size. EEGs were obtained from C3-A2 and C4-Al electrode sites. Sleep stages were classified, then TST, SWS latency and SWS/TST were calculated for the evaluation for sleep efficiencies on thermal conditions. As results, it was concluded that indoor thermal environments of $24\~26^{\circ}C$ was the best for comfortable and deep sleep.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.19 no.4
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• pp.307-312
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• 2007

This study was performed to evaluate sleep efficiencies and conditions for comfortable sleep based on the analysis of sleep efficiency and MST under four thermals conditions ($22^{\circ}C,\;24^{\circ}C,\;26^{\circ}C,\;30^{\circ}C$). Five female subjects who have similar life cycle and sleep patterns were participated for the sleep experiment. Their age was from 20 to 22 years old. They were healthy, and had regular sleep with consistent bed and wakeup time. It was checked whether they had a good sleep before the night of experiment. Experiments were performed in an environmental chamber using thermo-hygrostat. The physiological signal (EEG) for sleep stage were obtained from C3-A2 and C4-Al electrode sites. Sleep stages were classified, then SWS latency and SWS/TST were calculated for the evaluation for sleep efficiencies on thermal conditions. As results, mean skin temperature for comfort sleeping was $34.5{\sim}35.4^{\circ}C$. Considering sleep efficiency and mean skin temperature, indoor room temperature of upper limit was $28.1^{\circ}C$.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.20 no.12
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• pp.808-813
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• 2008

The study was to evaluate the air-conditioning of sleep algorithm. The algorithm was developed through the analysis of brain waves and MST, the experiments using air conditioner was performed in a apartment bedroom. Five female subjects were participated for the experiment. Eight hours of data collection a day was performed under different algorithm, case A, case B and case C. Physiological signals, EEG, ECG, EOG, and EMG, were obtained using polygraph and converted into digital signal. Then, subjects were asked to answer the questionnaire about their thermal sensation after experiment in bedroom. Sleep stages were classified, then TST, Sleep latency and Sleep efficiency were calculated for the three different air conditioner algorithm. As results, TST, Sleep efficiency, questionnaire showed the higher values for Case B algorism than that for other algorism. On the other hand, SWS latency was lower than for other conditions. Therefore, it was concluded that Case B of the algorithm was the best for comfortable and deep sleep.

• Journal of Life Science
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• v.12 no.4
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• pp.375-382
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• 2002

The purpose of this experiment was to examine influence of acute exercise on nocturnal sleep which had been disrupted by caffeine(400mg$\times$3) thought the daytime. Six healthy young males aged 21.0$\times$0.2 yr with a history of low caffeine use. Subjects completed three conditions in a within-subject. At three conditions Sleep EEG were investigated: (1) nocturnal following quiet rest, (2) nocturnal sleep following the consumption of 1200mg of caffeine (3) nocturnal sleep following cycling at 60 min of 60% V $O_{2peak}$ with 1200mg of caffeine consumption. Sleep data were calculated for REM sleep, REM latency, sleep onset latency, sleep efficiency, sleep stages, SWS. Those data were analyzed using repeated-measures ANOVA of change scores. A main effect to, drug(caffeine) indicated that caffeine elicited sleep disturbance that is, TST and sleep onset latency increase and sleep efficiency and stage 4 decrease. The effects of exercise on sleep following caffeine intake generally improve sleep that is, stage 2, 3 and SWS increase and sleep onset latency decrease. A condition effect for sleep indicated sleep improvement after exercise Therefore The data supported a restorative theory of slow-wave sleep and suggest that acute exercise may be useful in promoting sleep and reducing sleep disturbance elevated by a high dose of caffeine.