• Science of Emotion and Sensibility
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• v.6 no.4
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• pp.9-14
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• 2003

Sleep stages have been useful indicator to check a person's comfortableness in a sleep, But the traditional method of scoring sleep stages with polysomnography based on the integrated analysis of the electroencephalogram(EEG), electrooculogram(EOG), electrocardiogram(ECG), and electromyogram(EMG) is too restrictive to take a comfortable sleep for the participants, While the sympathetic nervous system is predominant during a wakefulness, the parasympathetic nervous system is more active during a sleep, Cardiovascular function is controlled by this autonomic nervous system, So, we have interpreted the heart rate variability(HRV) among sleep stages to find a simple method of classifying sleep stages, Six healthy male college students participated, and 12 night sleeps were recorded in this research, Sleep stages based on the "Standard scoring system for sleep stage" were automatically classified with polysomnograph by measuring EEG, EOG, ECG, and EMG(chin and leg) for the six participants during sleeping, To extract only the ECG signals from the polysomnograph and to interpret the HRV, a Sleep Data Acquisition/Analysis System was devised in this research, The power spectrum of HRV was divided into three ranges; low frequency(LF), medium frequency(MF), and high frequency(HF), It showed that, the LF/HF ratio of the Stage W(Wakefulness) was 325% higher than that of the Stage 2(p＜.05), 628% higher than that of the Stage 3(p＜.001), and 800% higher than that of the Stage 4(p＜.001), Moreover, this ratio of the Stage 4 was 427% lower than that of the Stage REM (rapid eye movement) (p＜.05) and 418% lower than that of the Stage l(p＜.05), respectively, It was observed that the LF/HF ratio decreased monotonously as the sleep stage changes from the Stage W, Stage REM, Stage 1, Stage 2, Stage 3, to Stage 4, While the difference of the MF/(LF+HF) ratio among sleep Stages was not significant, it was higher in the Stage REM and Stage 3 than that of in the other sleep stages in view of descriptive statistic analysis for the sample group.

• Sleep Medicine and Psychophysiology
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• v.18 no.2
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• pp.82-86
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• 2011

Objectives: The Berlin Questionnaire (BQ) has been used to help identify patients at high risk of having sleep apnea in primary care. But it has not been validated in a sleep clinic for Korean patients. The aim of this study is to evaluate the usefulness of the BQ as a screening tool for obstructive sleep apnea (OSA) for Korean patients in a sleep clinic. Methods: The BQ was prospectively applied to 121 subjects with OSA suspicion who visited to our sleep clinic. All subjects performed overnight polysomnography. OSA was defined as an apnea-hypopnea index (AHI) ${\geq}5$. We investigated the sensitivity, specificity, positive and negative predictive values of the BQ according to severity by AHI. Results: In 121 subjects, 73.6% were males, with a mean age of $48.8{\pm}13.0$ years. Twenty-five (20.6%) patients did not have OSA (AHI<5), 30 (25%) patients had mild OSA ($AHI{\geq}5$ and <15), 26 (21.4%) had moderate ($AHI{\geq}15$ and <30), and 40 (33%) had severe OSA ($AHI{\geq}30$). The BQ identified 69.4% of the patients as being at high risk for having OSA. The sensitivity and specificity of the BQ were 71.9% and 40%, for $AHI{\geq}5$, 75.8% and 38.2% for $AHI{\geq}15$, 77.5% and 34.6% for $AHI{\geq}30$, respectively. The positive and negative predictive values of the BQ were 82.1% and 27.0% for $AHI{\geq}5$, respectively. Positive and negative likelihood ratios were 1.2 and 0.7, and the overall diagnostic accuracy of the BQ was 65.3%, using an AHI cut-off of 5. Conclusion: Due to modest sensitivity and low specificity, the BQ does not seem to be an appropriate tool for identifying patients with obstructive sleep apnea in a sleep clinic population.

• Sleep Medicine and Psychophysiology
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• v.18 no.2
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• pp.76-81
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• 2011

Objectives: This study aims to analyze the association between the severity of sleep apnea, sleep and mood related scales, and activity during sleep in obstructive sleep apnea syndrome (OSAS) patients. Methods: 176 drug-free male patients confirmed as OSAS (average age=$43{\pm}11$ years) were selected through nocturnal polysomnography (NPSG). OSAS was diagnosed with apnea-hypopnea index (AHI) >5, mean AHI was $39.6{\pm}26.0$. Sleep related scales were Stanford Sleepiness Scale (SSS), Epworth Sleepiness Scale (ESS), Pittsburg Sleep Quality Index (PSQI) and Morningness-Eveningness Scale (MES). Mood related scales were Beck Depression Inventory (BDI), Beck Anxiety Inventory (BAI), State-Trait Anxiety Inventory (STAI) I, II and Profile of Mood States (POMS). NPSG was performed overnight with both wrist actigraphy (WATG). Parameters produced from WATG were total activity score, mean activity score and fragmentation index. We analyzed the correlation between each scale, AHI scored from NPSG and activity score analyzed from WATG. Results: ESS showed significant positive correlation with PSQI, BDI, BAI and STAI I, II, respectively (p<0.01). SSS showed significant positive correlation with PSQI and BAI (p<0.05, p<0.01). BAI showed significant positive correlation with total activity score, mean activity score and fragmentation index (p<0.05, p<0.01, p<0.05).Total activity score showed significant positive correlation with ESS and BAI, respectively (p<0.05). Fragmentation index showed significant positive correlation with ESS, PSQI and BAI (p<0.05, p<0.01, p<0.05). AHI, indicator of sleep apnea is showed no significant correlation with each sleep and mood related scale. Conclusion: The degree of daytime sleepiness tends to be associated with night sleep satisfaction, depression and anxiety, and the activity during sleep rather than the severity of sleep apnea.

• Journal of Biomedical Engineering Research
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• v.25 no.1
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• pp.11-19
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• 2004

Stage 1 sleep provides important information regarding interpretation of nocturnal polysomnography, particularly sleep onset. It is a short transition period from wakeful consciousness to sleep. Lack of prominent sleep events characterizing stage 1 sleep is a major obstacle in automatic sleep stage scoring. In this study, we attempted to utilize simultaneous EEC and EOG processing and analyses to detect stage 1 sleep automatically. Relative powers of the alpha waves and the theta waves were calculated from spectral estimation. Either the relative power of alpha waves less than 50％ or the relative power of theta waves more than 23％ was regarded as stage 1 sleep. SEM (slow eye movement) was defined as the duration of both eye movement ranging from 1.5 to 4 seconds and regarded also as stage 1 sleep. If one of these three criteria was met, the epoch was regarded as stage 1 sleep. Results f ere compared to the manual rating results done by two polysomnography experts. Total of 169 epochs was analyzed. Agreement rate for stage 1 sleep between automatic detection and manual scoring was 79.3％ and Cohen's Kappa was 0.586 (p＜0.01). A significant portion (32％) of automatically detected stage 1 sleep included SEM. Generally, digitally-scored sleep s1aging shows the accuracy up to 70％. Considering potential difficulties in stage 1 sleep scoring, the accuracy of 79.3％ in this study seems to be robust enough. Simultaneous analysis of EOG provides differential value to the present study from previous oneswhich mainly depended on EEG analysis. The issue of close relationship between SEM and stage 1 sleep raised by Kinnariet at. remains to be a valid one in this study.

• Sleep Medicine and Psychophysiology
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• v.13 no.2
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• pp.45-51
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• 2006

Obstructive sleep apnea (OSA) syndrome disrupts normal sleep. However, there were few studies to evaluate the asymmetric distribution, the one of the important factors of normal sleep in OSA subjects. We hypothesized that asymmetry would be broken in OSA patients. 49 male subjects with the complaint of heavy snoring were studied with polysomnography. We divided them into two groups based on the apnea-hypopnea index (AHI) fifteen: 13 simple snoring group (SSN, average AHI $5.9{\pm}4.4$) and 32 OSA group (average AHI $47.3{\pm}23.9$). We compared split sleep variables between the first half and the second half of sleep within each group with paired t-test for the evaluation of asymmetry. Changes of sleep architecture of OSA were higher stage 1 sleep% (S1), total arousal index (TAI), AHI, and mean heart rate (HR) and lower stage 2 sleep% (S2), REM sleep%, and mean arterial O2 saturation (SaO2) than SSN subjects. SWS and wake time after sleep onset (WASO) were not different between two groups. In split-night analysis, OSA subjects showed higher S2, slow wave sleep% (SWS), spontaneous arousal index (SAI), and mean HR in the first half, and higher REM sleep% and mean SaO2 in the second half. Those were same pattern as in SSN subjects. Mean apnea duration and longest apnea duration were higher in the second half only in the OSA. No differences of AHI, ODI, WASO, and S1 were found between the first and the second half of sleep in both groups. TAI was higher in the first half only in the SSN. SWS and WASO seemed to be influenced sensitively by simple snoring as well as OSA. Unlike our hypothesis, asymmetric distributions of major sleep architecture variables were preserved in OSA group. Losing asymmetry of TAI might be related to pathophysiology of OSA. We need more studies that include large number of subjects in the future.

• Sleep Medicine and Psychophysiology
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• v.13 no.2
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• pp.67-74
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• 2006

Introduction: Excessive daytime sleepiness and cataplexy are key features of narcolepsy. Modafinil is psychostimulant used in the treatment of narcolepsy. In this study, we evaluated effects of modafinil on nocturnal sleep structure and sleep latency in multiple sleep latency test and clinical features. Methods: Twelve narcoleptic patients (7 male, age: $22.9{\pm}2.6\;yrs$) were participated in the study. All of them had done nocturnal polysomnography (nPSG), multiple sleep latency test (MSLT), clinical symptoms scales and have repeated same procedure after taking 200 mg of modafinil. We have done linear mixed model analysis to describe effects of group, medication and nap time on these measures. Results: Modafinil did not affect clinical scales except PSQI which had been reduced after medication. In this study, Modafinil reduced total sleep time, sleep efficiency and increased wake after sleep onset and percent of arousal during sleep in nocturnal polysomnography and prolonged mean sleep latency in multiple sleep latency tests in both group. Discussion: Modafinil has stimulant effect of central nervous system but its effect on night sleep is less than other psychostimulants such as methylphenidate. We ascertained that modafinil affected total sleep time, sleep efficiency and percent of wake during sleep but did not effect on sleep structure. Modafinil was effective in the management of day time sleepiness. Modafinil can enhance alertness of control group without day time sleepiness.

• Sleep Medicine and Psychophysiology
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• v.23 no.1
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• pp.16-24
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• 2016

Background and Objectives: Obstructive sleep apnea (OSA) is often undiagnosed but is an important risk factor affecting the health of an individual. The level of awareness of the illness among patients with OSA is low and is not correlated with severity of the illness. This study was conducted to compare awareness of OSA symptoms and illness between patients with OSA and simple snorers. Materials and Methods: Two hundred eighty-two patients who were suspected of having OSA participated in this study. All subjects underwent overnight polysomnography. Those with an apnea-hypopnea index (AHI) ${\geq}5$ were classified as the OSA group, while those with an AHI < 5 were classified as the simple snoring group. A sleep questionnaire, which included items on awareness of the illness, OSA, and sleep symptoms, was administered to all subjects and their bed-partners. Results: Simple snorers were much more aware of their symptoms such as snoring, irregular breathing, and apnea than were patients with OSA. Bed-partners of simple snorers were also more aware of the participants' sleep symptoms than were partners of patients with OSA. However, the duration of OSA symptoms was longer in the OSA group. In the correlation analysis, the level of awareness of OSA symptoms was negatively correlated with AHI, age, body mass index, and Epworth Sleepiness Scale score. Among the sleep questionnaire and polysomnography results, only Pittsburgh Sleep Quality Index was positively correlated with level of awareness of OSA symptoms. The minority of the respondents had heard about the treatment methods of continuous positive airway pressure and oral appliance and preferred them as treatment options. Conclusion: This study suggests that simple snorers are more aware of their symptoms than are patients with OSA. A higher severity of OSA, represented by a higher AHI, is correlated with lower awareness of one's OSA symptoms.

• Sleep Medicine and Psychophysiology
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• v.15 no.1
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• pp.25-32
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• 2008

Objectives: A few studies have compared REM sleep-dependent obstructive sleep apnea syndrome (REM-OSA) with sleep stage non-dependent apnea syndrome (SND-OSA). Despite that REM-OSA might be more common in women than men, no studies have examined the probable characteristics of women patients with obstructive sleep apnea syndrome (OSAS). This study aimed at finding out the characteristics of REM-OSA in women by comparing it with SND-OSA. Methods: Fifty-three subjects diagnosed as OSAS (AHI>5 ; AHI : apnea-hypopnea index) with nocturnal polysomnography at the Center for Sleep and Chronobiology of the Seoul National University Hospital between October 2004 and February 2006 were studied. Of them, 44 subjects with OSAS severity of mild (52 and AHI-NR<15 (AHI-R : AHI during REM sleep, AHI-NR : AHI during non-REM sleep). We compared REM-OSA group with SND-OSA as well as the criteria-determined REM-OSA cases with the visually-determined ones. Results: Among 44 subjects, 28 persons (63.6%) turned out to have REM-OSA by our criteria and 24 persons (54.5%) by visual determination. Statistically significant differences (p<0.05) were found between REM-OSA and SND-OSA groups in AHI, hypopnea index, total sleep time, total wake time, sleep efficiency index, percents of stage 1, 2 and REM sleep, and REM latency. Percent of stage REM sleep (%REM) turned out to have influence on AHI ratio (AHI-R/AHI-NR) (B=0.537, p=0.002). REM-OSA was likely to be diagnosed in milder severity of OSAS (${\chi}^2=13.117$, p<0.001) and those with higher %REM (${\chi}^2=11.325$, p=0.001). There was no significant difference between the criteria-determined and the visually-determined cases of REM-OSA. Conclusion: We suggest that REM-OSA and SND-OSA patients be differentiated in terms of pathophysiology and treatment strategies. Visual determination of REM-OSA might be useful as the screening procedure of REM-OSA. Further studies on women with OSAS and REM-OSA need to be done.

• Sleep Medicine and Psychophysiology
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• v.21 no.1
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• pp.14-20
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• 2014

Objectives: Several studies suggest that nocturia may be related to obstructive sleep apnea syndrome (OSAS). The mechanism by which OSAS develops nocturia has not been determined. The present study aimed to determine the prevalence of nocturia among adults with OSAS and to identify factors that may be predictive in this regard. Methods: Retrospective review of clinical and polysomnographic data obtained from patients evaluated at the sleep clinics of the St. Paul's Hospital between 2009 and 2012. The urinary symptoms were assessed on the basis of the International Prostate Symptom Score (IPSS). Pathologic nocturia was defined as two or more urination events per night. OSAS was defined as apnea-hypopnea index (AHI) ${\geq}5$. A multivariate analysis using logistic regression was performed to examine the relationship between polysomnographic variables and the presence of pathologic nocturia, while controlling for confounding factor. Results: A total of 161 men >18 years of age (mean age $46.7{\pm}14.1$), who had been referred to a sleep laboratory, were included in the present study. Among these, 27 patients with primary snoring and 134 patients with obstructive sleep apnea were confirmed by polysomnography. Nocturia was found in 53 patients with OSAS (39.6%) and 8 patients with primary snoring (29.6%). The AHI was higher in patients with nocturia than in those without nocturia (p=0.001). OSAS patients with nocturia had higher arousal index (p=0.044), and lower nadir oxyhemoglobin saturation (p=0.001). Multiple regression analysis showed that age (${\beta}$=0.227, p=0.003), and AHI (${\beta}$=0.258, p=0.001) were associated with nocturia, and that the presence of pathologic nocturia was predicted by age (OR 1.04 ; p=0.004) and AHI (OR 1.02 ; p=0.001). Conclusion: Nocturia is common among patients with OSAS. The strongest predictors of nocturia are age and AHI in patients with OSAS.

• Sleep Medicine and Psychophysiology
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• v.21 no.1
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• pp.5-13
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• 2014

Objectives: Depression, sleep complaints and cognitive impairments are commonly observed in the elderly. Elderly subjects with depressive symptoms have been found to show both poor cognitive performances and sleep disturbances. However, the relationship between sleep complaints and cognitive dysfunction in elderly depression is not clear. The aim of this study is to identify the association between sleep disturbances and cognitive decline in late-life depression. Methods: A total of 282 elderly people who underwent nocturnal polysomnography in a sleep laboratory were enrolled in the study. The Korean version of the Neuropsychological Assessment Battery developed by the Consortium to Establish a Registry for Alzheimer's Disease (CERAD-K) was applied to evaluate cognitive function. Depressive symptoms were assessed with the geriatric depression scale (GDS) and subjective sleep quality was measured using the Pittsburg sleep quality index (PSQI). Results: The control group ($GDS{\leq}9$) when compared with mild ($10{\leq}GDS{\leq}16$) and severe ($17{\leq}GDS$) depression groups, had significantly different scores in the Trail making test part B (TMT-B), Benton visual retention test part A (BVRT-A), and Stroop color and word test (SCWT)(all tests p<0.05). The PSQI score, REM sleep duration, apnea-hypopnea index and oxygen desaturation index were significantly different across the three groups (all indices, p<0.05). A stepwise multiple regression model showed that educational level, age and GDS score were predictive for both TMT-B time (adjusted $R^2$=35.6%, p<0.001) and BVRT-A score (adjusted $R^2$=28.3%, p<0.001). SCWT score was predicted by educational level, age, apnea-hypopnea index (AHI) and GDS score (adjusted $R^2$=20.6%, p<0.001). Poor sleep quality and sleep structure alterations observed in depression did not have any significant effects on cognitive deterioration. Conclusion: Older adults with depressive symptoms showed mild sleep alterations and poor cognitive performances. However, we found no association between sleep disturbances (except sleep apnea) and cognitive difficulties in elderly subjects with depressive symptoms. It is possible that the impact of sleep disruptions on cognitive abilities was hindered by the confounding effect of age, education and depressive symptoms.