• Journal of Korea Society of Industrial Information Systems
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• v.22 no.1
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• pp.41-51
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• 2017

This Paper Describes a Method for the Evaluation of Sleep Apnea, Namely, the Peak Signal-to-noise ratio (PSNR) of Wavelet Transformed Electroencephalography (EEG) Data. The Purpose of this Study was to Investigate EEG Properties with Regard to Differences between Sleep Spindles and K-complexes and to Characterize Obstructive Sleep Apnea According to Sleep Stage. We Examined Non-REM and REM Sleep in 20 Patients with OSA and Established a New Approach for Detecting Sleep Apnea Base on EEG Frequency Changes According to Sleep Stage During Sleep Apnea Events. For Frequency Bands Corresponding to A3 Decomposition with a Sampling Applied to the KC and the Sleep Spindle Signal. In this Paper, the KC and Sleep Spindle are Ccalculated using MSE and PSNR for 4 Types of Mother Wavelets. Wavelet Transform Coefficients Were Obtained Around Sleep Spindles in Order to Identify the Frequency Information that Changed During Obstructive Sleep Apnea. We also Investigated Whether Quantification Analysis of EEG During Sleep Apnea is Valuable for Analyzing Sleep Spindles and The K-complexes in Patients. First, Decomposition of the EEG Signal from Feature Data was Carried out using 4 Different Types of Wavelets, Namely, Daubechies 3, Symlet 4, Biorthogonal 2.8, and Coiflet 3. We Compared the PSNR Accuracy for Each Wavelet Function and Found that Mother Wavelets Daubechies 3 and Biorthogonal 2.8 Surpassed the other Wavelet Functions in Performance. We have Attempted to Improve the Computing Efficiency as it Selects the most Suitable Wavelet Function that can be used for Sleep Spindle, K-complex Signal Processing Efficiently and Accurate Decision with Lesser Computational Time.

• Korean Journal of Clinical Laboratory Science
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• v.53 no.4
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• pp.333-341
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• 2021

Benzodiazepines (BDZs) drugs act on the GABA_A receptor, function as nerve suppressors, and are used to treat anxiety, insomnia, and panic disorder. We analyzed the data of 30 individuals to determine any differences in the sleep-electroencephalogram findings among individuals varying in age, benzodiazepine use, and duration of benzodiazepine use. Comparisons between users and non-users of benzodiazepines, short-term and long-term users, older and younger users, and older short-term and older long-term users, were achieved using electroencephalographic findings obtained through polysomnography. The parameters evaluated included sleep latency, sleep efficiency, sleep-stage percentages, number of sleep spindles, and average frequency of sleep-spindle. The difference between benzodiazepine users and non-users was significant with respect to sleep-stage percentages and average frequency of sleep-spindle. Older and younger users differed significantly with respect to sleep efficiency and sleep-stage percentages, whereas significant difference for sleep efficiency was obtained between long-term and short-term users. Taken together, our results indicate that BDZ consumption suppresses slow-wave sleep and increases the frequency of sleep spindles.

• Sleep Medicine and Psychophysiology
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• v.8 no.1
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• pp.67-71
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• 2001

Independent Component Analysis (ICA) is a blind source separation method using unsupervised learning and mutual information theory created in the late eighties and developed in the nineties. It has already succeeded in separating eye movement artifacts from human scalp EEG recording. Several characteristic sleep waves such as sleep spindle, K-complex, and positive occipital sharp transient of sleep (POSTS) can be recorded during sleep EEG recording. They are used as stage determining factors of sleep staging and might be reflections of unknown neural sources during sleep. We applied the ICA method to sleep EEG for sleep waves separation. Eighteen channel scalp longitudinal bipolar montage was used for the EEG recording. With the sampling rate of 256Hz, digital EEG data were converted into 18 by n matrix which was used as a original data matrix X. Independent source matrix U (18 by n) was obtained by independent component analysis method ($U=W{\timex}X$, where W is an 18 by 18 matrix obtained by ICA procedures). ICA was applied to the original EEG containing sleep spindle, K-complex, and POSTS. Among the 18 independent components, those containing characteristic shape of sleep waves could be identified. Each independent component was reconstructed into original montage by the product of inverse matrix of W (inv(W)) and U. The reconstructed EEG might be a separation of sleep waves without other components of original EEG matrix X. This result (might) demonstrates that characteristic sleep waves may be separated from original EEG of unknown mixed neural origins by the Independent Component Analysis (ICA) method.

• Proceedings of the ESK Conference
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• 1997.10a
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• pp.386-390
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• 1997

SAC 847 컴퓨터를 통해서 뇌파를 기본으로 턱과 다리의 근전도, 몸의 뒤척임, 심전도, 혈중 산소 농 도, 안전도 등을 동시에 기록하는 다원수면검사(polysomnogram)를 전자기가 차폐된 수면실에서 실시하 였고 수면단계기록 국제기준에 의한 수면단계와 최근 새롭게 제시되고 있는 수면의 경과에 따른 수면방 추파(sleep spindle)의 변동추적에 의한 수면단계 판정방법을 비교 분석하였다. 또한, 수면경과에 따른 .beta. .alpha. .theta. .delta. 파형의 발생빈도를 제시하고 평가하였다. 이러한 수면단계 분석은 종합 수면생리신호의 일환으로 인간공학적인 쾌적침대개발에 활용될 수 있을 것이다.

• Sleep Medicine and Psychophysiology
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• v.12 no.1
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• pp.5-10
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• 2005

Study in the field of sleep and memory has greatly expanded recently and the number of publications supporting the association between sleep and memory consolidation is rapidly growing. This study presents evidence related to sleep-dependent memory consolidation, ranging from behavioral task-performing studies to molecular studies, and several arguments against the association. Basic researches show that many genes are upwardly regulated during sleep and patterns of brain activation seen during daytime task training are repeated during subsequent REM sleep. Several electrophysiological studies demonstrate the correlation between spindle density increase following training and subsequent improvement in performing the training task. Overnight improvement or deterioration in task performance correlates with REM or SWS sleep. In the end, a lot of issues remain to be studied and discussed further in the future in spite of supporting evidence now available.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.257-260
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• 1993

A new method of spindle waveform detection is presented for the automated analysis of sleep EEG. The method is based on the combined application of signal conditioning in the time-domain and local spectrum analyzing in the frequency-domain. The overall detection system is implemented and, tested in real-time with a total of 24 hour data obtained from four subjects. The result shows an average agreement of 86.7% with the visually inspected result.

• Perspectives in Nursing Science
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• v.2 no.1
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• pp.37-47
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• 2005

Biobehavioral nursing research is focused on generating knowledge that examines relations among biological, behavioral, and social dimensions of health to improve outcomes. In this paper we review the findings of a biobehavioral nursing study of individuals with fibromyalgia (FM) that was framed from the perspective of an individual human response model, the FM literature, and our previous studies in midlife women. We were particularly interested in the studying the role of 'arousal' secondary to pain or to dysregulated hypothalamic-pituitary-adrenal (HPA) axis hormones during sleep and the impact on symptom expression. Unexpectedly, we did not find evidence of, arousal' or abnormal amounts of HPA axis hormones but we did find reduced amounts of growth hormone (GH) and prolactin (PRL) and of sleep spindle activity, a biomarker of sleep maintenance. We discuss these new findings and how our thinking was re-shaped to better understand the role that disturbed sleep plays in symptom expression in FM. It is argued that disturbed sleep maintenance mechanisms coupled with dysregulated somatotrophic-growth hormone axis and sleep-related PRL render individuals vulnerable to the development of or exacerbations of FM symptoms.