• 제목/요약/키워드: sleep interval

검색결과 122건 처리시간 0.17초

비만 폐쇄수면무호흡 환자에서 기계학습을 통한 적정양압 예측모형 (Predictive Model of Optimal Continuous Positive Airway Pressure for Obstructive Sleep Apnea Patients with Obesity by Using Machine Learning)

  • 김승수;양광익
    • Journal of Sleep Medicine
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    • 제15권2호
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    • pp.48-54
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    • 2018
  • Objectives: The aim of this study was to develop a predicting model for the optimal continuous positive airway pressure (CPAP) for obstructive sleep apnea (OSA) patient with obesity by using a machine learning. Methods: We retrospectively investigated the medical records of 162 OSA patients who had obesity [body mass index (BMI) ≥ 25] and undertaken successful CPAP titration study. We divided the data to a training set (90%) and a test set (10%), randomly. We made a random forest model and a least absolute shrinkage and selection operator (lasso) regression model to predict the optimal pressure by using the training set, and then applied our models and previous reported equations to the test set. To compare the fitness of each models, we used a correlation coefficient (CC) and a mean absolute error (MAE). Results: The random forest model showed the best performance {CC 0.78 [95% confidence interval (CI) 0.43-0.93], MAE 1.20}. The lasso regression model also showed the improved result [CC 0.78 (95% CI 0.42-0.93), MAE 1.26] compared to the Hoffstein equation [CC 0.68 (95% CI 0.23-0.89), MAE 1.34] and the Choi's equation [CC 0.72 (95% CI 0.30-0.90), MAE 1.40]. Conclusions: Our random forest model and lasso model ($26.213+0.084{\times}BMI+0.004{\times}$apnea-hypopnea index+$0.004{\times}oxygen$ desaturation index-$0.215{\times}mean$ oxygen saturation) showed the improved performance compared to the previous reported equations. The further study for other subgroup or phenotype of OSA is required.

수면무호흡을 가진 성인환자들의 주요인자 진단을 위한 융합 심박변이도 해석 (A Convergence HRV Analysis for Significant Factor Diagnosing in Adult Patients with Sleep Apnea)

  • 김민수;정종혁;조영창
    • 한국융합학회논문지
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    • 제9권1호
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    • pp.387-392
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    • 2018
  • 이 연구의 목적은 폐쇄성수면무호흡환자들의 수면단계, AHI, 연령대 간 심박변이도의 통계적 유의성을 결정하는 것이다. 이 연구는 수면무호흡 성인 환자 40명을 대상으로 시간영역 및 주파수 영역에서 심박변이도의 주요 파라메타를 평가하였다. 비 램수면 단계는 3개 그룹 수면무호흡증 환자의 AHI 등급을 비교하여 통계적으로 검증되었다. NN50(p=0.043), pNN50(p=0.044), VLF peak(p=0.022) 및 LF/HF(p=0.028) 매개변수들은 대조군에서 수면무호흡증환자의 R-R 간격에서 통계적으로 유의하였다. 수면무호흡 환자들의 비 램수면(수면2단계)과 램수면 사이의 LF/HF(p=0.045)과 HF power(p=0.0395)파라메타들은 대조군 그룹에서 통계적 유의하였다. 우리는 이 연구에서 폐쇄성 수면무홉증환자들의 AHI, 수면단계 및 연령이 심박변이도 상관관계를 이해하는데 근거를 제시 할 수 있을 것이다.

Sleep Quality and Poor Sleep-related Factors Among Healthcare Workers During the COVID-19 Pandemic in Vietnam

  • Thang Phan;Ha Phan Ai Nguyen;Cao Khoa Dang;Minh Tri Phan;Vu Thanh Nguyen;Van Tuan Le;Binh Thang Tran;Chinh Van Dang;Tinh Huu Ho;Minh Tu Nguyen;Thang Van Dinh;Van Trong Phan;Binh Thai Dang;Huynh Ho Ngoc Quynh;Minh Tran Le;Nhan Phuc Thanh Nguyen
    • Journal of Preventive Medicine and Public Health
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    • 제56권4호
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    • pp.319-326
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    • 2023
  • Objectives: The coronavirus disease 2019 (COVID-19) pandemic has increased the workload of healthcare workers (HCWs), impacting their health. This study aimed to assess sleep quality using the Pittsburgh Sleep Quality Index (PSQI) and identify factors associated with poor sleep among HCWs in Vietnam during the COVID-19 pandemic. Methods: In this cross-sectional study, 1000 frontline HCWs were recruited from various healthcare facilities in Vietnam between October 2021 and November 2021. Data were collected using a 3-part self-administered questionnaire, which covered demographics, sleep quality, and factors related to poor sleep. Poor sleep quality was defined as a total PSQI score of 5 or higher. Results: Participants' mean age was 33.20±6.81 years (range, 20.0-61.0), and 63.0% were women. The median work experience was 8.54±6.30 years. Approximately 6.3% had chronic comorbidities, such as hypertension and diabetes mellitus. About 59.5% were directly responsible for patient care and treatment, while 7.1% worked in tracing and sampling. A total of 73.8% reported poor sleep quality. Multivariate logistic regression revealed significant associations between poor sleep quality and the presence of chronic comorbidities (odds ratio [OR], 2.34; 95% confidence interval [CI], 1.17 to 5.24), being a frontline HCW directly involved in patient care and treatment (OR, 1.59; 95% CI, 1.16 to 2.16), increased working hours (OR, 1.84; 95% CI,1.37 to 2.48), and a higher frequency of encountering critically ill and dying patients (OR, 1.42; 95% CI, 1.03 to 1.95). Conclusions: The high prevalence of poor sleep among HCWs in Vietnam during the COVID-19 pandemic was similar to that in other countries. Working conditions should be adjusted to improve sleep quality among this population.

Association between Self-Reported Sleep Duration and Diabetes Mellitus: Data from a 7-Year Aggregated Analysis

  • Kim, Jae-Hyun;Park, Eun-Cheol
    • 보건행정학회지
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    • 제29권1호
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    • pp.68-76
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    • 2019
  • Background: This study investigates the association between sleep duration and diabetes mellitus (DM) in a large representative population-based survey in South Korea. Methods: The fourth (2007-2009), fifth (2010-2012), and sixth (2013) Korea National Health and Nutrition Examination Survey data sets were used. A total of 37,989 individuals were selected for the study. Chi-square tests and multivariate logistic regression analyses were used to analyze whether general characteristics, health status, and health risk behaviors were associated with DM. Results: After adjusting for confounders, the odds of DM in short sleepers (${\leq}5hr/day$) and long sleepers (${\geq}9hr/day$) were 1.033-times higher (95% confidence interval [CI], 0.913-1.169) and 1.334-times higher (95% CI, 1.140-1.562), respectively, compared with individuals who slept 7 hr/day. Subgroup analysis according to gender showed a U-shaped association for both genders, although it appeared stronger in men. Conclusion: This study identified a U-shaped association between sleep duration and the risk for DM. Additional studies should help clarify the important information in this study.

Discrete-time Survival Analysis of Risk Factors for Early Menarche in Korean Schoolgirls

  • Yong Jin Gil;Jong Hyun Park;Joohon Sung
    • Journal of Preventive Medicine and Public Health
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    • 제56권1호
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    • pp.59-66
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    • 2023
  • Objectives: The aim of this study was to evaluate the effect of body weight status and sleep duration on the discrete-time hazard of menarche in Korean schoolgirls using multiple-point prospective panel data. Methods: The study included 914 girls in the 2010 Korean Children and Youth Panel Study who were in the elementary first-grader panel from 2010 until 2016. We used a Gompertz regression model to estimate the effects of weight status based on age-specific and sex-specific body mass index (BMI) percentile and sleep duration on an early schoolchild's conditional probability of menarche during a given time interval using general health condition and annual household income as covariates. Results: Gompertz regression of time to menarche data collected from the Korean Children and Youth Panel Study 2010 suggested that being overweight or sleeping less than the recommended duration was related to an increased hazard of menarche compared to being average weight and sleeping 9 hours to 11 hours, by 1.63 times and 1.38 times, respectively, while other covariates were fixed. In contrast, being underweight was associated with a 66% lower discrete-time hazard of menarche. Conclusions: Weight status based on BMI percentiles and sleep duration in the early school years affect the hazard of menarche.

무선 센서 네트워크에서 클러스터링 기반 Sleep Deprivation Attack 탐지 모델 (Sleep Deprivation Attack Detection Based on Clustering in Wireless Sensor Network)

  • 김숙영;문종섭
    • 정보보호학회논문지
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    • 제31권1호
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    • pp.83-97
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    • 2021
  • 무선 센서 네트워크를 구성하는 무선 센서는 일반적으로 전력 및 자원이 극히 제한적이다. 무선 센서는 전력을 보존하기 위해 일정 주기마다 sleep 상태로 진입한다. Sleep deprivation attack은 무선 센서의 sleep 상태 진입을 막음으로써 전력을 소진 시키는 치명적인 공격이지만 이에 대한 뚜렷한 대응책이 없다. 이에 본 논문에서는 클러스터링 기반 이진 탐색 트리 구조의 Sleep deprivation attack 탐지 모델을 제안한다. 본 논문에서 제안하는 sleep deprivation attack 탐지 모델은 기계학습을 통해 분류한 공격 센서 노드와 정상 센서 노드의 특징을 사용한다. 이때 탐지 모델에 사용한 특징은 Long Short-Term Memory(LSTM), Decision Tree(DT), Support Vector Machine(SVM), K-Nearest Neighbor(K-NN)을 이용하여 결정하였다. 결정된 특징은 본 논문에서 제안한 알고리즘에 사용하여 공격 탐지를 위한 값들을 계산하였으며, 계산한 값을 판정하기 위한 임계값은 SVM을 적용하여 도출하였다. 본 논문에서 제안하는 탐지 모델은 기계학습으로 도출된 특징과 임계값을 본 논문에서 제안한 탐지 알고리즘에 적용하여 구성하였으며, 실험을 통해 전체 센서 노드 20개 중 공격 센서 노드의 비율이 0.35일 때 94%의 탐지율을 갖고 평균 에너지 잔량은 기존 연구보다 최대 26% 향상된 결과를 보였다.

The Effects of Non-pharmacological Interventions on Sleep among Older Adults in Korean Long-term Care Facilities: A Systematic Review and Meta-analysis

  • Jung, Sun Ok;Kim, Hyeyoung;Choi, Eunju
    • 지역사회간호학회지
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    • 제33권3호
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    • pp.340-355
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    • 2022
  • Purpose: This study aimed to examine the effects of non-pharmacological sleep intervention programs in improving sleep quality among older adults in long-term care facilities. Methods: A literature search and selection was performed on nine different databases using the guidelines of PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). Overall, 14 studies met the inclusion criteria and were systematically reviewed. For the meta-analysis, the effect size was estimated using the random-effects model in Review Manager (RevMan) desktop version 5.4 of the Cochrane Library. Results: The meta-analysis of overall non-pharmacological interventions obtained a total effect size of 1.0 (standardized mean difference [SMD]=1.0, 95% confidence interval [CI]: 0.64~1.35), which was statistically significant (Z=5.55, p<.001). The most frequently studied non-pharmacological intervention was aroma therapy, with an effect size of 0.61 (SMD=0.61, 95% CI: 0.14~1.08), which was statistically significant (Z=2.55, p=.010). In the subgroup analysis, group-based interventions, interventions for >4 weeks, and untreated control studies were more effective. Conclusion: This study confirms that non-pharmacological interventions are effective in improving sleep quality among older adults in long-term care facilities. However, the sample size was small and the risk of bias in assessing the interventions of individual studies was unclear or high, thereby limiting the generalizability of the results. Further reviews that evaluate randomized control trials, evidence-based interventions that consider older adult participants' physical activity levels, different intervention methods and durations, and different control group intervention types are needed to obtain more conclusive evidence.

폐쇄성 수면무호흡 증후군과 일차성 불면증에서 심박동률 변이도 지수의 비교 (Comparison of Heart Rate Variability Indices between Obstructive Sleep Apnea Syndrome and Primary Insomnia)

  • 남지원;박두흠;유재학;유승호;하지현
    • 수면정신생리
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    • 제19권2호
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    • pp.68-76
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    • 2012
  • 목 적: 수면 장애는 자율신경계의 변화를 유발하여 심혈관계에 영향을 준다. 일차성 불면증(primary insomnia, 이하 PI)은 수면부족 및 각성으로, 폐쇄성 수면무호흡 증후군(obstructive sleep apnea syndrome, 이하 OSAS)은 수면 중 빈번한 각성, 저산소증 등으로 교감신경계 항진을 유발한다. 이에 OSAS와 PI 사이에서 심박동률 변이도(heart rate variability, 이하 HRV) 분석을 통해 자율신경계의 변화 정도를 비교하고자 하였다. 방 법: 임상병력 및 야간수면다원검사(nocturnal polysomnography, 이하 NPSG)로 선택된 PI와 OSAS 전체 315 명의 대상자 중 OSAS는 무호흡-저호흡 지수(apnea-hypopnea index, 이하 AHI)에 따라서 경도, 중등도, 중증도 OSAS로 분류하여 PI를 포함하여 4개의 군으로 분류되었다. 이후 연령, 성별, 군간 개체수를 고려하여 최종적으로 110명의 대상자가 선택되었고, PI군(평균나이 41.50, 표준편차 13.16, AHI <5, n=20), 경도 OSAS군(평균나이 43.67, 표준편차 12.11, AHI 5~15, n=30), 중등도 OSAS군(평균나이 44.93, 표준편차 12.38, AHI 16~30, n=30), 중증도 OSAS군(평균 나이 45.87, 표준편차 12.44, AHI >30, n=30)의 4개 군으로 나누었다. 이후 NPSG를 통해 얻은 각 군의 HRV 지수 비교를 위하여 연령과 체질량지수(body weight index, BMI)를 공변량으로 하여 공분산분석(analysis of covariance, ANCOVA)를 실시한 후 사후분석으로 Sidak test를 실시하였다. 결 과: HRV 지수의 비교 결과 PI군과 경도, 중등도의 OSAS군 간에 유의한 차이는 없었다. 그러나 PI군과 중증도 OSAS군 사이에는 유의한 차이가 있었다. 군간비교에서 통계적으로 가장 현저한 차이를 보인 PI군과 중증도 OSAS군에서 HRV 지수 중 통계적으로 의미 있는 각각의 값은 다음과 같았다. Average RR interval은 $991.1{\pm}27.1$$875.8{\pm}22.0$ ms(p=0.016), standard deviation of NN interval(SDNN)은 $85.4{\pm}6.6$$112.8{\pm}5.4$ ms(p=0.022), SDNN index는 $57.5{\pm}5.2$$87.6{\pm}4.2$(p<0.001), total power는 $11893.5{\pm}1359.9$$8097.0{\pm}1107.2ms^2$(p=0.008), very low frequency(VLF)는 $7534.8{\pm}1120.1$$11883.8{\pm}912.0ms^2$(p=0.035), low frequency(LF)는 $2724.2{\pm}327.8$$4351.6{\pm}266.9ms^2$였다(p=0.003). 결 론: 본 연구에서는 PI군에 비해 중증도의 OSAS군에서 HRV 지수 중 교감신경계의 영향을 많이 받는 VLF, LF 등이 상승하는 양상을 보였고, 이를 통해 PI에 비해 중증도의 OSAS가 교감신경계 활동증가에 보다 더 큰 영향을 끼치는 것을 알 수 있었다.

불면증이 동반된 여성 갱년기 환자의 심박변이도 특성 분석 : 후향적 차트리뷰 (Analysis on Heart Rate Variability (HRV) Characteristics of Patients with Insomnia during Perimenopause and Postmenopause: A Retrospective Chart Review)

  • 안수연;박은지;이지연;유정은
    • 대한한방부인과학회지
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    • 제30권3호
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    • pp.54-64
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    • 2017
  • Objectives: The purpose of this study is to demonstrate Heart Rate Variability characteristics of menopausal patients with insomnia. Methods: From March 1, 2014 to June 20, 2017, Heart Rate Variability was measured in 102 menopausal patients who visited Cheonan Korean Medicine Hospital of Daejeon University. We compared accompanying symptoms and Heart Rate Variability values depending on sleep quality in menopausal women. Results: The accompanying symptoms of menopausal patients were as follows: hot flushes (45.1%), tiredness (25.49%), chest discomfort and palpitations (23.53%), headache (17.65%), arthralgia and muscular pain (17.65%), cold sensitivity of hands and feet (15.69%), urinary frequency (14.71%) and anxiety (10.78%). The frequency of chest discomfort and palpitation was significantly higher in the menopausal insomnia group than in normal sleep group. Comparing Heart Rate Variability between two groups, Standard deviation of the NN interval (SDNN), Total Power (TP), and Low Frequency (LF) values were significantly lower in insomnia group. Conclusions: Chest discomfort and palpitations were more frequent in insomnia patients in menopausal women than normal sleep group, and Standard deviation of the NN interval (SDNN), Total Power (TP), Low Frequency (LF) were significantly lower in HRV values.

에너지 생산이 가능한 무선 센서 네트워크에서 잔여 에너지 인지 듀티-사이클 스케줄링 기법 (Residual Energy-Aware Duty-Cycle Scheduling Scheme in Energy Harvesting Wireless Sensor Networks)

  • 이성원;유홍석;김동균
    • 한국통신학회논문지
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    • 제39B권10호
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    • pp.691-699
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    • 2014
  • 네트워크 수명을 연장시키기 위해 무선 센서 네트워크에서는 idle listening에 소비되는 에너지를 줄일 수 있는 듀티-사이클 MAC 프로토콜들이 제안되었다. 일반적인 듀티-사이클 MAC 프로토콜에서 각 센서 노드는 잔여 에너지양을 기반으로 듀티-사이클 주기를 계산한다. 그러나 에너지 수집이 가능한 센서 네트워크에서 기존 듀티-사이클 주기는 에너지 수집률이 높은 센서 노드에 불필요한 sleep 지연을 발생시킨다. 따라서 우리는 이전 연구에서 잔여 에너지양과 에너지 수집률을 함께 고려하여 듀티 사이클-주기를 조절하는 듀티-사이클 스케줄링 기법을 제안하였다. 그러나 이러한 듀티-사이클 MAC 프로토콜들은 듀티 사이클-주기 변화에 따른 성능 차이를 고려하지 않고 듀티-사이클 주기를 항상 선형적으로 조절하므로, 응용의 요구사항에 맞는 최적의 듀티 사이클 주기를 얻지 못한다. 본 논문에서는 듀티-사이클 주기를 계산하는 세 가지 기법들을 제안하고 그 결과에 대해 분석한다. 실험을 통해 제안된 기법들이 기존 듀티-사이클 스케줄링 기법에 비해 네트워크 수명, 단대단 패킷 전송 시간과 패킷 전송률을 각각 최대 23%, 44%, 31% 증가시킴을 확인하였다.