• Quality Improvement in Health Care
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• v.1 no.1
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• pp.124-131
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• 1994

Polysomnography is an essential methodology for diagnosing and following up sleep disorders and doing researches on human sleep. Sleep medicine, mainly with the utilization of polysomnographic techniques, has developed itself as one of the promising fields in the 21st century medicine. Korea is not an exception in importing and developing sleep medicine into the conventional medicine. However, it still remains to be clarified what polysomnography is for and how it should be done, considering the relatively recent introduction of sleep medicine into Korea. The author, being a board-certified sleep medicine specailist, having experienced spreading out sleep medicine within Korea for the past four years, and having recently set up a major sleep study facility in Korea at Seoul National University Hospital, attempts in this introductory critical article to review the essential issues related to quality assurance in polysomnographic study of human sleep. Also, unconditional introduction of "automated" sleep scoring system, which has been found to have significantly reduced reliability in various studies including the author's own, is critically reviewed. The author suggests that quality assurance and training program should be initiated and established by a responsible sleep medicine-related organization such as the Korean Association of Sleep Medicine and Psychophysiology.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.395-397
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• 1997

We have applied the neural network method for the neural networkmethod for the automatic scoring of the sleep stage. 17 features are extracted from the recorded EEG, EOG and EMG signals. These features are inputed to tile multilayer perceptron model. Neural network was trained with error-back propagation method. Results are compared with manual scoring of the experts, and show the possibility of application of automatic method in sleep stage scoring.

• Korean Journal of Otorhinolaryngology-Head and Neck Surgery
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• v.61 no.11
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• pp.593-599
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• 2018

Background and Objectives Respiratory scoring guidelines for children and adults have been used for evaluating adolescents both in the 2007 and 2012 American Academy of Sleep Medicine (AASM) scoring manuals. We compared the scoring methods of polysomnography used in these scoring manuals, where pediatric and adult scoring rules were adopted for the diagnosis of sleep apnea in adolescents. Subjects and Method 106 Korean subjects aged between 13 and 18 years were enrolled. All subjects underwent overnight polysomnography in a sleep laboratory. Data were scored according to both pediatric and adult guidelines in the 2007 and 2012 AASM scoring manuals. Results Both pediatric and adult apnea hypopnea index (AHI) using the 2012 method were significantly higher than those using the 2007 method. The difference in AHI compared between pediatric and adult scores with the 2012 AASM scoring system was markedly decreased from that with the 2007 method. There was a significant discordance in sleep apnea diagnosis between pediatric and adult scoring rules in the 2012 method. Conclusion Both pediatric and adult rules were used for the diagnosis of adolescent sleep apnea in the 2012 method. However, there was significant discordance in the diagnosis between pediatric and adult scoring guidelines in the 2012 AASM manual, probably due to different cut-off values of AHI for the diagnosis of sleep apnea in pediatric (${\geq}1$) and adult (${\geq}5$) patients. Further studies are needed to determine a more reasonable cut-off value for the diagnosis of sleep apnea in adolescents.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.199-202
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• 1997

We are developing computer integrated polysomnography system. This system integrates conventional polysomnography with computer for data management, automatic analysis, scoring, and data transmission. In the first stage, we have developed the signal interface and user interface for the manual scoring and data management. For the automatic scoring of sleep stage, we have developed the protocol and have applied the analytic method in its primitive form. In the second stage we will develope a partially automatic scoring system, and finalize the fully automatic system in the final third stage.

• Sleep Medicine and Psychophysiology
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• v.10 no.1
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• pp.52-60
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• 2003

Objectives: 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. The lack of prominent sleep events characterizing stage 1 sleep is a major obstacle in automatic sleep stage scoring. In this study, utilization of simultaneous EEG and EOG processing and analyses to detect stage 1 sleep automatically were attempted. Methods: Relative powers of the alpha waves and the theta waves were calculated from spectral estimation. A relative power of alpha waves less than 50% or 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 was also regarded as stage 1 sleep. If one of these three criteria was met, the epoch was regarded as stage 1 sleep. Results were compared to the manual rating results done by two polysomnography experts. Results: A total of 169 epochs were analyzed. The 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. Conclusion: Generally, digitally-scored sleep staging shows accuracy up to 70%. Considering potential difficulty in stage 1 sleep scoring, accuracy of 79.3% in this study seems to be strong enough. Simultaneous analysis of EOG differentiates this study from previous ones which mainly depended on EEG analysis. The issue of close relationship between SEM and stage 1 sleep raised by Kinnari remains a valid one in this study.

• 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.