• Sleep Medicine and Psychophysiology
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• v.12 no.1
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• pp.27-31
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• 2005

Objectives: We attempted to compare the performance of 2 commercially available actigraphies with focus on sleep parameters, using polysomnography as standard comparison tool. Methods: Fourteen normal volunteers (5 males and 9 females, mean age of $28{\pm}4.6\;years$) participated in this study. All the participants went through one night of polysomnography, simultaneously wearing 2 different kinds of actigraphies on each wrist. Polysomnographic and actigraphic data were stored, downloaded, and processed according to standard protocols and then statistically compared. Results: Both $ActiWatch^{(R)}$ and $SleepWatch^{(R)}$ tended to overestimate the total sleep time, compared to the polysomnography. $SleepWatch^{(R)}$ tended to underestimate the sleep latency. The two actigraphs and the polysomnograph did not show significant difference of sleep efficiency, when compared with one another. In addition, all of the sleep parameters from the instruments showed linear correlations except in $SleepWatch^{(R)}'s$ sleep latency. The sleep parameters from the two actigraphs did not show much noteworthy difference, and linear relationships were found between the sleep parameters from the two actigraphs. There was no significant distinction in the results of the two different actigraphs. Conclusion: The results of two actigraphies can be used interchangeably since the sleep parameters of the two different actigraphies do not show significant differences statistically. Overall, it is not legitimate to use actigraphy as a substitute for polysomnography. However, since sleep parameters except sleep latency show linear correlations, actigraphy might possibly be used to follow up patients after polysomnography.

• Journal of the Korea Society of Computer and Information
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• v.25 no.7
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• pp.113-123
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• 2020

Obstructive sleep apnea (OSA) among sleep disorders is one of relatively common diseases. Patients can be checked for the disease through sleep polysomnography. However, as far as he diagnosis of OSA using polysomnography (PSG) is concerned, many practical problems such as an increasing number of patients, expensive testing cost, discomfort during examination, and the limited number of people for testing have been pointed out. Accordingly, for the purpose of substituting PSG researchers have been actively conducting studies on OSA diagnosis based on machine learning using bio signals. In this regard, we review a rich body of existing OSA diagnosis studies applying machine learning techniques based on bio-signal data. As a result, this paper presents a novel taxonomy of the reviewed studies and provides their comprehensive comparative analysis results. Also, we reveal various limitations of the studies using the bio signals and suggest several improvements about utilization of the used machine learning methods. Finally, this paper presents future research topics related to the application of machine learning techniques using bio signals.

• Korean Journal of Clinical Laboratory Science
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• v.52 no.3
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• pp.278-283
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• 2020

Central sleep apnea (CSA) is characterized by respiratory failure of at least 10 seconds without any effort of the chest and abdomen in the absence of upper airway resistance during sleep. In this case, the patient experiences respiratory failure that does not meet the CSA diagnostic criteria and CSA symptoms. Magnetic resonance imaging diffusion-weighted imaging (MRI DWI) scans revealed a lateral medullary infarction. Continuous positive airway pressure (CPAP) was applied as a primary treatment for CSA and respiratory failure. During the titration of CPAP, the apnea-hypopnea index (AHI) and arousal index (AI) were worse than the results before its use (AHI: 42.5/hr→82.8/hr, AI: 21.7/hr→40.8h). As a result, adaptive servo-ventilation (ASV) was chosen as the secondary treatment. Compared to the night-polysomnography results before the ASV treatment, the AHI improved (42.5/hr→8.6/hr). Therefore, ASV is a potential treatment for CSA and respiratory failure in these patients.

• Sleep Medicine and Psychophysiology
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• v.9 no.2
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• pp.106-114
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• 2002

Objectives: Daytime sleepiness is a common symptom and is associated with sleep behavior, sleep deprivation, and night shift, etc. It is also one of the most important symptoms of sleep disorders like obstructive sleep apnea (OSA). According to our survey on Korean literature, a few studies have dealt with daytime sleepiness, and we have not been able to locate any study comparing normal subjects with polysomnography-proven sleep disorder patients regarding daytime sleepiness. We aimed at comparing daytime sleepiness among normal healthy daytime workers, medical students being expected to have daytime sleepiness due to chronic sleep deprivation, and patients having sleep disorders diagnosed with polysomnography. We also studied the association between subjective daytime sleepiness and objective polysomnographic findings in patients with sleep disorders. Methods: One hundred three hospital workers, 137 medical students, and patients with sleep disorders were studied. Sleep disorders included OSA, periodic limb movements in sleep (PLMS), insomnia, and narcolepsy. The degree of subjective sleepiness in each group was measured by the Korean version of Epworth sleepiness scale and compared. The relationship between polysomnographic findings reflecting severity of sleep disorder in each patient group and subjective sleepiness was analyzed. As for patients with narcolepsy, the relationship between the mean sleep latency and subjective sleepiness was studied. Results: There was a significant difference of ESS score (F=68.190, dF=5.752, p<0.001) among daytime workers, medical students, and sleep disorder patients. In OSA patient group, the degree of the sleepiness had no significant correlation either with mean O2 satuaration (p=0.062) or with RDI (p=0.807). In PLMS patient group, there was no correlation between periodic limb movement index (PLMI) and subjective sleepiness (p=0.761). In narcolepsy patient group, the subjective sleepiness had no correlation with mean sleep latency measured with MSLT (p=0.055). Conclusion: We found a significant difference of subjective sleepiness among daytime workers, medical students, and patients with sleep disorders. However, no consistent correlation was found between severity of subjective sleepiness and objective polysomnographic findings reflecting severity of each sleep disorder. This research confirms that the evaluation of subjective sleepiness is important clinically, but it cannot substitute the objective measures such as nocturnal polysomnography and MSLT.

• Sleep Medicine and Psychophysiology
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• v.14 no.2
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• pp.92-98
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• 2007

Objectives: Obstructive sleep apnea syndrome (OSAS) is the most common form of sleep-disordered breathing and often presents with comorbid depressive symptoms. In this study, we evaluated the relationship between depressive symptoms and sleep parameters as measured by nocturnal polysomnography (NPSG) and simultaneous wrist actigraphy. Methods: Two hundred sixty-four subjects with clinically suspected cases of OSAS underwent one-night polysomnography, while simultaneously wearing a wrist actigraphy device. They also completed two questionnaires；the Epworth Sleepiness Scale-Korean version (ESS-K) and the Beck Depression Inventory (BDI). Of the cases studied, 105 subjects were proven by NSPG to have OSAS without other sleep disorders. NPSG and wrist actigraphy data from the subjects were analyzed. Pearson correlation and paired t-test were used in order to evaluate the relationship between depressive symptoms and sleep-parameters. Results: Mean age of the subjects was $46.1{\pm}13.1$ years. Means of the ESS-K score and BDI scores were $10.9{\pm}4.7$ and $12.8{\pm}8.1$, respectively. NPSG sleep parameters significantly differed from those of wrist actigraphy. There was no correlation found between subjects' respiratory disturbance index (RDI) and BDI scores. When directly comparing sleep parameters between subjects who were more depressed versus subjects who were less depressed, both total sleep time and sleep efficiency were decreased in the more depressed. A correlation between RDI and ESS-K scores was also found in the more depressed group. Conclusions: Although our findings suggest that there is no relationship between RDI and depressive symptoms, there are other significant differences in the sleep parameters between subjects who are more depressed versus those without depression. We recommend that patients with depression should also be evaluated for clinical symptoms of OSAS.

• Sleep Medicine and Psychophysiology
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• v.23 no.2
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• pp.61-67
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• 2016

Objectives: We aimed to evaluate the effects of mattress type on both objective and subjective sleep quality in healthy good sleepers. Methods: Fifteen healthy good sleepers with a mean age of 30.8 years participated in this study. A randomized crossover trial was carried out using two different mattress types: a standard mattress and a contour coil mattress. After a night of adaptation, all participants were randomized to either a standard mattress or a contour coil mattress. Then, nocturnal polysomnography was conducted for two consecutive nights. Subjective evaluations were obtained using a self-report questionnaire before and after the polysomnographic recording sessions. Results: The polysomnographic showed no differences in total sleep time, sleep stage, or wake time after sleep onset between the two mattress conditions. Of the polysomnographic variables, only sleep onset latency was significantly reduced for the contour coil mattress. Additionally, participants reported better subjective sleep quality when sleeping on the contour coil mattress, according to the questionnaires. Conclusion: The type of mattress might affect not only subjective, but also objective sleep quality, including sleep onset latency.

• Korean Journal of Health Psychology
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• v.16 no.3
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• pp.557-575
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• 2011

This study tried to examine the characteristics of attention deficits in patients with Obstructive Sleep Apenea(OSA) with different age levels, and to examine which indices of polysomnograms might be related to the indices of attention deficits in OSAs. Two age-level groups and a normal control group were subjected to two computerized attention tests, including a continuous performance test(CPT) and a change blindness task(CBT). In addition, the three groups were subjected to a Polysomnography to extract several sub-indicators of polysomnogram, and an Epworth Sleepiness Scale which measures subjective sleepiness. As results, the OSAs showed significantly more omission and commission errors in CPT, and they showed lower accuracy in CBT compared to the normal group. The results of a correlational analysis showed that attention deficits in OSA are significantly correlated with arterial oxygen saturation among sub-indicators of polysomnograms. In conclusion, OSAs seems to be less attentive, having difficulties in response inhibition, and having deficiencies in noticing important environmental changes. Age seems to make these deficiencies even worse. Especially, the relationship between attention deficiency and hypoxia which could cause irreversible cerebrum damage has an implication in cognitive impairment prevention through early treatment.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.243-245
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• 2012

대표적인 수면장애로 수면 무호흡증과 코골이가 있는데 수면다원검사를 통해 진단할 수 있다. 그러나 수면다원검사는 비용적, 공간적, 시간적 제약이 수반되기 때문에 이를 해결하려는 연구가 대두되고 있다. 수면장애와 그 요인을 검출하기 위해 가속도센서, 소음센서, 온도센서, 습도센서로 구성된 측정 장치에서 획득한 데이터와 건강, 운동, 생활습관 데이터를 활용하여 어떤 요인에 의해 수면장애의 정도가 악화되고 개선되는지를 사용자에게 제공하는 의사결정 지원시스템을 설계한다. 또한 홈 게이트웨이와 뷰어 역할에 스마트 폰을 사용하여 일반인이 보다 쉽게 측정하고 측정결과와 추론결과를 지속적으로 확인할 수 있는 시스템을 제안한다.

• Sleep Medicine and Psychophysiology
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• v.2 no.1
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• pp.73-81
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• 1995

Objective : Patients with sleep apnea should be diagnosed with polysomnography(PSG). However, it is not easy to recommend PSG for all patients suspected with sleep apnea in practice. Therefore, we tried to develop the screening test for referral of PSG. Method : 140 patients with snoring and sleep apnea syndrome were studied by the PSG. Sleep apnea questionnaire. Zung's scale for depression. Stanford Sleepiness Scale(SSS), insomnia scale and neuropsychological test were administered. Also, blood pressure, height, weight and neck circumference were measured and some histories were taken. Correlations between respiratory disturbance index(RDI) and various parameters mentioned above and discriminant coefficients of the parameters to RDI were computed. And, we investigated sensitivities of screening tests for selection of the patients with RDI above 20. Results : Using six parameters(neck circumference, systolic blood pressure before sleep, degree of alcohol drinking, frequency of breath-holding during sleep, degree of dry mouth during sleep, sleep apnea score), the patients with RDI above 20 could be discriminated in 92.8% sensitivity. In case of more than two among six parameters(neck circumference of above 40cm, systolic blood pressure of above 125mmHg, frequent alcohol drinking, frequent breath-holding during sleep, frequent dry mouth during sleep, sleep apnea score of above 35), same patients could be discriminated in 87.6% sensitivity. And, in case of more than one among four parameters(neck circumference of above 40cm. systolic blood pressure of above 125mmHg, frequent alcohol drinking, body weight of above 80kg), discrimination sensitivity was 83.5%. Conclusions : Patients with RDI above 20 could be discriminated by above parameters with high sensitivity. Therefore, the screening test using above parameters can be applied in selection of the patients with sleep apnea for PSG in practice.

• Sleep Medicine and Psychophysiology
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• v.9 no.1
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• pp.34-40
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• 2002

Objectives: The gold standard for diagnosing obstructive sleep apnea syndrome (OSAS) is nocturnal polysomnography (NPSG). This is rather expensive and somewhat inconvenient, however, and consequently simpler and cheaper alternatives to NPSG have been proposed. Oximetry is appealing because of its widespread availability and ease of application. In this study, we have evaluated whether oximetry alone can be used to diagnose or screen OSAS. The diagnostic performance of an analysis algorithm using arterial oxygen saturation ($SaO_2$) base on 'dip index', mean of $SaO_2$, and CT90 (the percentage of time spent at $SaO_2$<90%) was compared with that of NPSG. Methods: Fifty-six patients referred for NPSG to the Division of Sleep Studies at Seoul National University Hospital, were randomly selected. For each patient, NPSG with oximetry was carried out. We obtained three variables from the oximetry data such as the dip index most linearly correlated with respiratory disturbance index (RDI) from NPSG, mean $SaO_2$, and CT90 with diagnosis from NPSG. In each case, sensitivity, specificity and positive and negative predictive values of oximetry data were calculated. Results: Thirty-nine patients out of fifty-six patients were diagnosed as OSAS with NPSG. Mean RDI was 17.5, mean $SaO_2$ was 94.9%, and mean CT90 was 5.1%. The dip index [4%-4sec] was most linearly correlated with RDI (r=0.861). With dip index [4%-4sec]${\geq}2$ as diagnostic criteria, we obtained sensitivity of 0.95, specificity of 0.71, positive predictive value of 0.88, and negative predictive value of 0.86. Using mean $SaO_2{\leq}97%$, we obtained sensitivity of 0.95, specificity of 0.41, positive predictive value of 0.79, and negative predictive value of 0.78. Using $CT90{\geq}5%$, we obtained sensitivity of 0.28, specificity of 1.00, positive predictive value of 1.00, and negative predictive value of 0.38. Conclusions: The dip index [4%-4sec] and mean $SaO_2{\leq}97%$ obtained from nocturnal oximetry data are helpful in diagnosis of OSAS. CT90${\leq}$5% can be also used in excluding OSAS.