• Title/Summary/Keyword: Somnography

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Gender-wise analysis of the cephalometric factors affecting obstructive sleep apnea (성별에 따른 폐쇄성 수면무호흡 환자의 측모 두부방사선계측학적 관련요인)

  • Hwang, Sang-Hee
    • The korean journal of orthodontics
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    • v.41 no.3
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    • pp.164-173
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    • 2011
  • Objective: The purpose of this study was to perform gender-wise analysis of the related cephalometric factors affecting Korean patients with obstructive sleep apnea (OSA). Methods: We examined 118 adults who had visited the Sleep Disorder Clinic Center in Keimyung university, Daegu, Korea, and evaluated them by using poly-somnography (PSG) and lateral cephalograms. The patients were divided into 4 groups (male simple snorers, male OSA patients, female simple snorers, and female OSA patients) according to AHI (apnea-hypopnea index) and sex. Results: The position of the hyoid bone in the female OSA group was inferior to that in the female simple snorer group. Multiple regression analysis showed that tongue length and soft palate width were significant determinants for the severity of AHI in male OSA patients. However, inferior position of the hyoid was a significant determinant only in women. Conclusions: From a cephalometric point of view, OSA in male and female adult patients may be characterized by different pathogeneses. In particular, in female OSA patients, they might be managed by individualized treatments such as hormone replacement therapy in addition to conventional treatment.

Automatic Detection of Stage 1 Sleep (자동 분석을 이용한 1단계 수면탐지)

  • 신홍범;한종희;정도언;박광석
    • 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.