• 수면정신생리
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• 제29권1호
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• pp.1-3
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• 2022

Sleep is associated with Alzheimer's dementia. Many previous researches have shown that inadequate sleep is one of the risk factors that predict Alzheimer's dementia. The causal mechanism of this association is not clear. Slow wave sleep and REM sleep are critical stages in memory consolidation, and by sequential hypothesis both stages are important. Deposition of amyloid beta and tau, the main pathology of Alzheimer's dementia, are also associated with sleep. This review provides the association of sleep and Alzheimer's dementia, and future research is necessary to examine the specific mechanism of this association between sleep and Alzheimer's dementia, which may lead to an early intervention in sleep.

• Clinical and Experimental Pediatrics
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• 제50권8호
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• pp.711-717
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• 2007

Sleep is a vital, highly organized process regulated by complex systems of neuronal networks and neurotransmitters. Normal sleep comprises non-rapid eye movement (NREM) and REM periods that alternate through the night. Sleep usually begins in NREM and progresses through deeper NREM stages (2, 3, and 4 stages), but newborns enter REM sleep (active sleep) first before NREM (quiet sleep). A period of NREM and REM sleep cycle is approximately 90 minutes, but newborn have a shorter sleep cycle (50 minutes). As children mature, sleep changes as an adult pattern: shorter sleep duration, longer sleep cycles and less daytime sleep. REM sleep is approximately 50% of total sleep in newborn and dramatically decreases over the first 2 years into adulthood (20% to 25%). An initial predominant of slow wave sleep (stage 3 and 4) that peaks in early childhood, drops off abruptly after adolescence by 40% from preteen years, and then declines over the life span. The hypothalamus is recognized as a key area of brain involved in regulation of sleep and wakefulness. The basic function of sleep largely remains elusive, but it is clear that sleep plays an important role in the regulation of CNS and body physiologic processes. Understanding of the architecture of sleep and basic mechanisms that regulate sleep and wake cycle are essential to evaluate normal or abnormal development of sleep pattern changes with age. Reduction or disruption of sleep can have a significant impact on daytime functioning and development, including learning, growth, behavior, and emotional regulation.

• 여성건강간호학회지
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• 제20권3호
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• pp.195-203
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• 2014

Purpose: The objective of this study was to investigate the relationship between fatigue, sleep disturbance, and gestational stress in women during late stage of pregnancy. Methods: This study was conducted with 113 healthy pregnant women at gestational age greater than 27 weeks who were registered at community health centers and received prenatal care. A structured questionnaire regarding fatigue, sleep disturbance, and gestational stress was used. The data was analyzed using a t-test, an ANOVA, and Pearson correlation coefficients. Results: The subjects with unplanned pregnancies and irregular exercise patterns showed a higher level of fatigue than those with planned pregnancies and regular exercise patterns. Pregnant women with caffeine intake manifested higher levels of gestational stress and sleep disturbance than those without. The levels of sleep disturbance and gestational stress increased as the fatigue levels increased. The fatigue levels increased with increased levels of sleep disturbance. Conclusion: Planned pregnancy, regular exercise patterns, and caffeine intake were related with fatigue, sleep disturbance, and gestational stress in women during late stages of pregnancy. Fatigue, sleep disturbance, and gestational stress had close associations to each other. In the future, such results should guide development of nursing intervention programs for women in late stages of pregnancy.

• IEIE Transactions on Smart Processing and Computing
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• 제6권1호
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• pp.21-26
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• 2017

In this paper, we suggest an automated sleep scoring method using machine learning algorithms on accelerometer data from a wristband device. For an experiment, 36 subjects slept for about eight hours while polysomnography (PSG) data and accelerometer data were simultaneously recorded. After the experiments, the recorded signals from the subjects were preprocessed, and significant features for sleep stages were extracted. The extracted features were classified into each sleep stage using five machine learning algorithms. For validation of our approach, the obtained results were compared with PSG scoring results evaluated by sleep clinicians. Both accuracy and specificity yielded over 90 percent, and sensitivity was between 50 and 80 percent. In order to investigate the relevance between features and PSG scoring results, information gains were calculated. As a result, the features that had the lowest and highest information gain were skewness and band energy, respectively. In conclusion, the sleep stages were classified using the top 10 significant features with high information gain.

• 감성과학
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• 제6권4호
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• pp.9-14
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• 2003

수면단계는 수면감을 평가하는 데 있어서 중요한 생리지표로서 사용되어 왔다. 그러나 수면다원검사를 이용한 전통적 수면단계 분류방법은 뇌전도(electroencephalogram : EEG), 안전도(electrooculogram : EOG), 심전도(electrocardiogram : ECG), 근전도(electromyogram : EMG) 등을 종합적으로 측정하므로 수면단계를 비교적 정확히 분류할 수 있지만 피험자에게 심한 구속감을 주는 문제가 있다. 본 연구에서는, 각성상태에서 교감신경계가 지배적인 반면에 수면 중에는 부교감 신경계가 더 활동적인 점에 착안하여 수면단계를 간단히 분류할 수 있는 방법을 찾고자 수면단계에 따른 심박동변이도(heart rate variability : HRY)를 분석하였다. 이 실험에는 건강한 대학생 6명이 2일씩 전체 12회의 야간수면에 참여하였다. 수면다원검사 장치를 이용하여 피험자들이 수면을 취하고 있는 동안, EEG, EOG, ECG, EMG(턱 및 다리)를 측정하여 수면단계를 "Standard scoring system for sleep stage"에 따라 자동으로 분류하였다. 그런 뒤, 본 연구를 통하여 제작된 Sleep Data Acquisition/Analysis 시스템을 이용하여 수면다원검사 장치로부터 ECG신호만 추출하여 HRV의 전력스펙트럼을 3개의 영역[저주파수대역(low frequency : LF), 중간주파수대역(medium frequency : MF), 고주파수대역(high frequency : HF)]으로 나누어 분석하였다. 단일채널 ECG를 이용하여 수면단계별로 HRV의 LF/HF를 분석한 결과, W(wakefulness)단계가 2단계에 비하여 325%높게(p＜.05), 3단계에 비하여 628%높게(p＜.001), 4단계에 비하여 800%높게(p＜.001) 나타났으며, 4단계는 REM(rapid eye movement)단계에 비하여 427% 낮게(p＜.05), 1단계에 비하여 418% 낮게(p＜.05) 나타났다. 또한 LF/HF가 수면단계에 따라 변화하는 양상은 W, REM, 1, 2, 3, 4단계의 순으로 단조 감소하였다. 한편, 수면단계별 MF/(LF+HF)의 차이는 유의하지 않았으나 표본집단의 기술통계치를 살펴본 바 REM단계와 3단계의 평균치가 가장 높았다.치가 가장 높았다.

• 수면정신생리
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• 제14권1호
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• pp.42-48
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• 2007

목 적：뇌파의 비선형적 특성을 연구하는 방법으로 탈경향 변동분석이 사용되고 있다. 본 연구에서는 정상인 수면 뇌파에 탈경향변동분석을 적용하여 수면뇌파의 비선형적 특성, 채널 별 차이, 수면단계별 차이를 규명하고자 하였다. 방 법：정상인 12명($23.8{\pm}2.5$세, 남：여=7：5)를 대상으로 야간수면다원검사를 시행하였다. 수면다원검사를 통해 얻어진 뇌파를 채널 별, 수면단계별로 나누어 탈경향변동분석 시행 후 여기서 얻어진 축척지수(scaling exponent)를 선형혼합모형 분석을 통해 비교하였다. 결 과：정상인 수면다원검사에서 얻어진 뇌파의 축척지수는 1 내외의 값을 보여 장기-시간적연관성, 자기유사성을 보였다. C3 채널의 축적지수가 O1채널의 축적지수보다 높은 값을 보였다. 수면단계가 진행함에 따라 축적지수는 증가하였으며, 1단계 수면과 렘수면은 축적지수는 통계적 차이를 보이지 않았다. 결 론：정상인 수면 뇌파는 탈경향변동분석에서 무축척요동(scale-free fluctuation), 장기-시간적 관련성(long-range temporal correlation), 자기유사성(self-similarity) 및 스스로 짜여진 고비성(self-organized criticality) 등의 비선형적 특성을 보였다. 탈경향변동분석에서 얻어진 축적지수는 뇌파 채널 별, 수면단계별 차이를 보여 수면 뇌파를 연구하는 중요한 도구로 사용될 수 있다.

• 대한임상검사과학회지
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• 제43권4호
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• pp.188-193
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• 2011

Obstructive sleep apnea (OSA) is the most common type of sleep apnea and is caused by obstruction of the upper airway. Since it is closely related to sleep parameter and body indices, the study was focused on the relationship with them. The results of polysomnography (PSG) in obstructive sleep apnea was done at ENT department of Ewha women university Mokdong hospital from March to September 2010 with 52 subjects (male 35, female 17). The leads were placed to measure electroencephalogram (EEG), electrooculogram (EOG), mandibular and anterior tibialis electromyogram (EMG), airflow in nasal and oral cavity, chest and abdominal breathing pattern, snoring sound and arterial oxygen saturation ($SpO_2$) level. From sleep parameter and body indices of adult obstructive sleep apnea compared to normal adult revealed that age (p<0.01) and snoring sound (p<0.05) were increased, stage 1 sleep (p<0.01) was increased, the deeper stages (3&4) of sleep (p<0.05) were reduced. Respiratory disturbance index (RDI) (p<0.01), mean $SpO_2$ (p<0.05) and lowest $SpO_2$ (p<0.01) were also decreased. The correlation analysis from sleep parameter and body indices of OSA showed the positive correlation with age (r=0.463, p<0.001), snoring sound (r=0.278, p<0.05), stage 1 sleep (r=0.391, p<0.01) and RDI (r=0.409, p<0.01), but showed the negative correlation with the deeper stages (3&4) of sleep (r=-0.307, p<0.05), mean $SpO_2$=(r=-0.274, p<0.05) and lowest $SpO_2$ (r=-0.392, p<0.01). This study proves that obstructive sleep apnea and indices have closed related.

• Transactions on Control, Automation and Systems Engineering
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• 제4권3호
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• pp.239-243
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• 2002

Multi-valued decision making for transitional stochastic events was newly derived based on conditional probability of knowledge database which included experts'knowledge and experience. The proposed multi-valued decision making was successfully adopted to the determination of the five levels of the vigilance of a subject during the EEG (electroencephalogram) recording; awake stage (stage W), and sleep stages (stage REM (rapid eye movement), stage 1, stage 2, stage $\sfrac{3}{4}$). Innovative feature of the proposed method is that the algorithm of decision making can be constructed only by use of the knowledge database, inspected by experts. The proposed multi-valued decision making with a mathematical background of the probability can also be applicable widely, in industries and in other medical fields for purposes of the multi-valued decision making.

• 전기전자학회논문지
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• 제23권4호
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• pp.1273-1279
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• 2019

수면 질환에 사용되는 수면다원검사는 그 비용 및 시간적 제약으로 새로운 대안을 찾을 필요가 절실하다. 최근 웨어러블 헬스기기가 대중화 되면서 기존의 액티그래피를 이용한 수면분석을 대신하려는 다양한 연구가 되고 있으나 이들 기기의 데이터 및 알고리즘은 접근성 및 성능에 있어 매우 제한적인 상황이다 본 논문에서는 자체 제작된 가속도계 센서모듈을 이용한 수면 중 움직임 정보를 이용하여 AASM표준 방식 기준으로 분류된 수면 단계를 예측하고, 센서의 움직임 정보와 뇌파의 δ파와 θ파의 파워스펙트럼 비교를 통해 수면의 주기를 추정할 수 있는 방법을 제시했다. 31명의 공개된 PSG 분석결과를 이용한 수면 단계 예측 결과 85.26%의 정확도를 보였다. 움직임 신호의 특성과 δ파와 θ파의 파워 변화를 비교한 결과 REM수면과 NREM수면의 반복 주기를 제시한 알고리즘으로 찾을 수 있는 가능성이 있음을 보였다.

• 수면정신생리
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• 제5권1호
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• pp.18-33
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• 1998

Sleep and Epilepsy either represent the opposite and independent spectrum of episodic manifestations from brain or closely interact with each other. Sleep or sleep deprivation may provoke epileptic seizures or activate epileptiform discharges in epilepsy patients whereas epilepsy may alter the sleep structure. Sleep stages are also known to influence pathophysiology of seizures in terms of ictogenesis. In this review, the impact of sleep on epilepsy as well as that of epilepsy on sleep are presented. Additionally the interaction between sleep and epilepsy will be discussed. This review will also comment on the differential diagnosis between nocturnal or sleep-related epilepsy and various sleep disorders. Finally, clinical application of the above perspectives of sleep and epilepsy will be suggested for the purpose of a better management of epilepsies.