• 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.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 Biomedical Engineering Research
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• v.24 no.6 s.81
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• pp.487-494
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• 2003

The sleep stages provides the most basic evidence for diagnosing a variety of sleep diseases. for staging sleep by analysis of EEG(electroencephalogram), it is especially important to detect the characteristic waveforms from EEG. In this paper, sleep EEG signals were analyzed using Fourier transform and continuous wavelet transform as well as discrete wavelet transform. Proposeed system methods. Fourier and wavelet for detecting of important characteristic waves(hump, sleep spindles. K-complex, hill wave, ripple wave) in sleep EEG. Sleep EEG data were analysed using Daubechies wavelet transform method and FFT method. As a result of simulation, we suggest that our neural network system attain high performance in classification of characteristic waves.

• Sleep Medicine and Psychophysiology
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• v.1 no.2
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• pp.172-181
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• 1994

Obstructive sleep apnea syndrome(OSAS) is most frequently diagnosed in the sleep laboratories and its severity is objectively estimated. In terms of treatment, the most prevalent method is the continuous positive airway pressure(CPAP) application as of now. However, in Korea, CPAP is still not sufficiently known and it is attributable to the fact that sleep study facilities have not been popularized. In this article, the authors present their own experience with CPAP in nine subjects with OSAS. In this study, CPAP was found to decrease stage 1 sleep and to increase stage 2 sleep, with increasing mean oxygen saturation and decreasing lowest oxygen saturation during nocturnal sleep. Also, it tended to increase sleep continuity and generally to improve sleep architecture. Rebound slow wave and/or REM sleep stages during CPAP were also noted in 8 out of 9 cases. The authors suggest that CPAP should be considered as the primary mode of treatment for patients with obstructive sleep apnea syndrome and related educational programs for physicians should be developed and provided by sleep specialists.

• Journal of Biomedical Engineering Research
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• v.35 no.3
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• pp.55-61
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• 2014

In sleep monitoring system, polysomnography (PSG) is the gold-standard but previous studies revealed that attaching numerous amount of sensors disturb sleep during the test which is the fundamental disadvantage of PSG. We suggest an unconstrained rapid-eye-movement (REM) sleep monitoring method measured with polyvinylidene (PVDF) film-based sensor for the normal and the obstructive sleep apnea (OSA) patients. Nine normal subjects and seventeen OSA patients have participated in the study. During REM sleep, rate and variability of respiration are known to be greater than in other sleep stages. Based on this phenomena, respiratory signals of participants were unconstrainedly measured using the PVDF-based sensor with the PSG and REM sleep were extracted from the average rate and variability of respiration. In epoch-by-epoch REM sleep detection, proposed method classified REM sleep with an average sensitivity of 72.3%, specificity of 92.5%, accuracy of 88.9%, and kappa statistic of 0.60 compared to the results of PSG. Student's t-test showed no significant difference between the results of normal and OSA group. This method is potentially applicable to REM sleep detection in homing environment or ambulatory monitoring.

• Journal of Biomedical Engineering Research
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• v.35 no.6
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• pp.211-218
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• 2014

The objective of this research is to develop an automatic algorithm based on electrocardiogram (ECG) to estimate slow-wave sleep (SWS). An algorithm is based on 7 indices extracted from heart rate on ECG which simultaneously recorded with standard full night polysomnography from 31 subjects. Those 7 indices were then applied to independent component analysis to extract a feature that discriminates SWS and other sleep stages. Overall Cohen's kappa, accuracy, sensitivity and specificity of the algorithm to detect 30s epochs of SWS were 0.52, 0.87, 0.70 and 0.90, respectively. The automatic SWS detection algorithm could be useful combining with existing REM and wake estimation technique on unattended home-based sleep monitoring.

• Journal of Oriental Neuropsychiatry
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• v.23 no.4
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• pp.11-36
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• 2012

Objectives : Sleep Disorders are very common in clinical stages and there are many reports and papers regarding this subject. I try to understand the present state of sleep research in JON (The Journal of Oriental Neuropsychiatry) for the benefits of clinical practice. Methods : We searched and read every article on JON from 1990 to 2012 and selected ones that are related to Sleep Disorder; then analyzed the data to 5 categories, like literature study, case study, Clinical Data-Analysis study, experimental study, and clinical trial. Results : 1. We Found 41 articles relating to sleep disorder in JON form 1999 to 2012, and there were 9 literature studies, 13 case studies, 13 Clinical Data-Analysis studies, 4 experimental studies, and 2 clinical trials. 2. There were Sa-Am Acupuncture Method, Pharmacopuncture, electroacupuncture, and Auricular acupuncture to treat Sleep Disorder. 3. There were many additional treatments like Purgative Therapy, etc. 4. They reported the ordinary sleep pattern of Soeumin and Soyangin, too. 5. In the experimental study, they reported several herbs, herbal prescription on the expression of melatonin receptors, and Punsimgeimgamibang on insomnia, anxiety, emotionality in rats. 6. There were 2 clinical trials, one for Hwabyung-patient with insomnia by acupuncture treatment and another for insomnia in the elderly by ETF-I program. 7. There were 2 case of other sleep disorder (enuresis, sleepwalking) and 2 literature study of dream. Conclusions : In JON regarding sleep disorder, the majority was due to insomnia. Therefore, we also have to expand our sight into other sleep diseases. We need more clinical trials and experimental researches for the construction of EBM Sleep Disorder in Oriental Neuropsychiatry.

• Journal of Ginseng Research
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• v.32 no.3
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• pp.220-225
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• 2008

The present investigation was performed to evaluate the homeostatic regulation of sleep architecture by the ethanol extract of Korea red ginseng (KRG), since the available data were often controversial. In addition, it was also interested in whether the sleep-wake stages were differently affected by low and high doses of KRG. Each adult Wistar male rat was implanted with a transmitter for recording EEG and activity via telemetry. After one week of surgery, polygraphic signs of undisturbed sleep-wake activities were recorded for 12 h (between 9:00 am and 9:00 pm) after KRG administration. KRG (10 and 100 mg/kg) increased non-rapid eye movement (NREM) sleep as well as total sleep. The total percentages of wakefulness were decreased comparably. KRG (10 mg/kg) decreased the power density of the ${\delta}-wave$ (0.75-4.5 Hz) and increased ${\alpha}-wave$ (8.0-13.0 Hz) in the NREM and rapid eye movement (REM) sleep. KRG also decreased ${\delta}-wave$ power density in wake time. However, KRG (100 mg/kg) increased ${\delta}-wave$ and decreased ${\theta}-wave$ (5.0-9.0 Hz) power density in wake time, while showed little effect on the power density in NREM and REM sleep. In conclusion, low and high doses of KRG increase spontaneous sleep and NREM sleep and differently regulate the EEG spectra in REM and NREM sleep.

• Journal of Biomedical Engineering Research
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• v.36 no.5
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• pp.204-210
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• 2015

Although many studies have analyzed the relationship between electrodermal activity (EDA) and sleep stages, a practical method for detecting sleep stage using EDA has not been suggested. The aim of this study was to develop an algorithm for real-time automatic detection of deep sleep using the EDA signal. Simultaneously with overnight polysomnography (PSG), continuous measurement of skin conductance on the fingers was performed for ten subjects. The morphometric characteristics in the fluctuations of EDA signal were employed to establish the quantitative criteria for determining deep sleep. The 30-sec epoch-by-epoch comparison between the deep sleep detected by our method and that reported from PSG exhibited an average sensitivity of 74.6%, an average specificity of 98.0%, and an average accuracy of 96.1%. This study may address the growing need for a reliable and simple measure for identifying sleep stage without a PSG.

• Sleep Medicine and Psychophysiology
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• v.4 no.2
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• pp.191-200
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• 1997

Objectives : Periodic limb movements during sleep (PLMS) may cause arousals that may lead to non-restorative sleep. PLMS is characterized by long sleep latency, sleep fragmentation, frequent stage shifts, and rarity of stages 3/4 NREM sleep on polysomnography. However, controversies have existed and it still remains to be elaborated whether PLMS actually causes insomnia, since normal persons happen to have PLMS. Clinically, it would be crucial to know factors which might disturb sleep in PLMS. We became interested in Coleman's theory(1980) that invariant periodic movements disturb patients' sleep less. Though, Coleman's study seems to have been confounded by including PLMS patients with various co-morbid sleep disorders. Therefore, we attempted to study in patients only with PLMS the effects of movement patterns on sleep architecture. Methods : In 27 patients diagnosed as having PLMS only with clinical interview and nocturnal polysomnography, we studied the relationship between the movement patterns such as mean duration and variability of periodic limb movement's interval and the sleep architecture variables. Results : The shorter and the more regular the limb movement intervals were, the fewer arousals followed. The movement intervals of the older patients were shorter and more regular than the younger patients. The probability of the accompanying arousal with each limb movement increased as the duration and variance of the movement intervals increased. It decreased as the age and the frequency of limb movements increased. Among these factors the most significant one was the mean duration of the movement intervals. In other words, the shorter the movement intervals were, the less disturbed sleep was. Conclusion : PLMS frequency increases with aging but the probability of the accompanying arousal with each movement decreases with aging. Sleep-disturbing effects of PLMS depends more on the duration and variability of movement intervals than the PLMS frequency.