• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.140-147
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• 2021

EEG(electroencephalogram) are measured to accurately determine the level of sleep in various sleep examinations. In general, measurements are more accurate as the number of sensor channels increases. EEG can interfere with sleep by attaching electrodes to the skin when measuring. It is necessary for self sleep care to select the minimum number of EEG channels that take into account both the user's discomfort and the accuracy of the measurement data. In this paper, we proposed a sleep stage analysis model based on machine learning and conducted experiments for using from one channel to four channels. We obtained estimation accuracy for sleep stage as following 82.28% for one channel, 85.77% for two channels, 80.33% for three channels and 68.87% for four channels. Although the measurement location is limited, the results of this study compare the accuracy according to the number of channels and provide information on the selection of channel numbers in the EEG sleep analysis.

• Journal of Korea Multimedia Society
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• v.21 no.12
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• pp.1370-1378
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• 2018

There is a problem to measure neutral bio-signals during sleep because of inconvenience of attaching lots of sensors. In this study, we measured single electrocardiogram(ECG) signal and analyzed the correlation with sleep. After R-peak detection from ECG signal, we extracted 9 features from time and frequency domain of heart rate variability(HRV). Mean of HRV, RR intervals differing more than 50ms(NN50), and divided by the total number of all RR intervals(pNN50) have significant differences in each sleep stage. Specially, the mean HRV has an average of 87.8% accuracy in classifying sleep and awake status. In the future, the measurement ECG signal minimizes inconvenience of attaching sensors during sleep. Also, it can be substituted for the standard sleep measurement method.

• Sleep Medicine and Psychophysiology
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• v.14 no.1
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• pp.42-48
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• 2007

Introduction: Detrended fluctuation analysis (DFA) is used as a way of studying nonlinearity of EEG. In this study, DFA is applied on sleep EEG of normal subjects to look into its nonlinearity in terms of EEG channels and sleep stages. Method: Twelve healthy young subjects (age：$23.8{\pm}2.5$ years old, male：female=7：5) have undergone nocturnal polysomnography (nPSG). EEG from nPSG was classified in terms of its channels and sleep stages and was analyzed by DFA. Scaling exponents (SEs) yielded by DFA were compared using linear mixed model analysis. Results: Scaling exponents (SEs) of sleep EEG were distributed around 1 showing long term temporal correlation and self-similarity. SE of C3 channel was bigger than that of O1 channel. As sleep stage progressed from stage 1 to slow wave sleep, SE increased accordingly. SE of stage REM sleep did not show significant difference when compared with that of stage 1 sleep. Conclusion: SEs of Normal sleep EEG showed nonlinear characteristic with scale-free fluctuation, long-range temporal correlation, self-similarity and self-organized criticality. SE from DFA differentiated sleep stages and EEG channels. It can be a useful tool in the research with sleep EEG.

• Korean Journal of Psychosomatic Medicine
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• v.31 no.2
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• pp.149-154
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• 2023

Objectives : Far-infrared (FIR) lights have been investigated for sleep quality intervention. We sought to measure the advantageous effects of FIR in sleep using polysomnographic data as the objective outcomes. Methods : The ten healthy volunteers were enrolled in a single-center, prospective, patient-blind, single-arm trial. Individuals slept on a sham mattress and a FIR emitting mattress with polysomnography for one night each. Results : Sleep efficiency showed an increasing trend but was not statistically significant. PSQI-K significantly decreased (p=0.013). The latency to REM of the baseline was shorter than that of the intervention (p=0.008). Though there was no statistical significance, Stage N1 and N2 were shortened, and Stage N3 was prolonged after the intervention compared to the baseline. Conclusions : The FIR-emitting mattresses improved sleep quality on self-reported insomnia. We suggested the candidate for the markers altered by the FIR therapy, such as the normalization of REM latency and increased N3 sleep.

• Journal of Life Science
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• v.12 no.4
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• pp.375-382
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• 2002

The purpose of this experiment was to examine influence of acute exercise on nocturnal sleep which had been disrupted by caffeine(400mg$\times$3) thought the daytime. Six healthy young males aged 21.0$\times$0.2 yr with a history of low caffeine use. Subjects completed three conditions in a within-subject. At three conditions Sleep EEG were investigated: (1) nocturnal following quiet rest, (2) nocturnal sleep following the consumption of 1200mg of caffeine (3) nocturnal sleep following cycling at 60 min of 60% V $O_{2peak}$ with 1200mg of caffeine consumption. Sleep data were calculated for REM sleep, REM latency, sleep onset latency, sleep efficiency, sleep stages, SWS. Those data were analyzed using repeated-measures ANOVA of change scores. A main effect to, drug(caffeine) indicated that caffeine elicited sleep disturbance that is, TST and sleep onset latency increase and sleep efficiency and stage 4 decrease. The effects of exercise on sleep following caffeine intake generally improve sleep that is, stage 2, 3 and SWS increase and sleep onset latency decrease. A condition effect for sleep indicated sleep improvement after exercise Therefore The data supported a restorative theory of slow-wave sleep and suggest that acute exercise may be useful in promoting sleep and reducing sleep disturbance elevated by a high dose of caffeine.

• Journal of Biomedical Engineering Research
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• v.36 no.5
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• pp.204-210
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• 2015

Although many studies have analyzed the relationship between electrodermal activity (EDA) and sleep stages, a practical method for detecting sleep stage using EDA has not been suggested. The aim of this study was to develop an algorithm for real-time automatic detection of deep sleep using the EDA signal. Simultaneously with overnight polysomnography (PSG), continuous measurement of skin conductance on the fingers was performed for ten subjects. The morphometric characteristics in the fluctuations of EDA signal were employed to establish the quantitative criteria for determining deep sleep. The 30-sec epoch-by-epoch comparison between the deep sleep detected by our method and that reported from PSG exhibited an average sensitivity of 74.6%, an average specificity of 98.0%, and an average accuracy of 96.1%. This study may address the growing need for a reliable and simple measure for identifying sleep stage without a PSG.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.3
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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.

• 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.

• Clinics in Shoulder and Elbow
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• v.26 no.2
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• pp.169-174
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• 2023

Background: Sleep quality, quantity, and efficiency have all been demonstrated to be adversely affected by rotator cuff pathology. Previous measures of assessing the impact of rotator cuff pathology on sleep have been largely subjective in nature. This study was undertaken to objectively analyze this relationship through the use of activity monitors. Methods: Patients with full-thickness rotator cuff tears at a single institution were prospectively enrolled between 2018 and 2020. Waist-worn accelerometers were provided for the patients to use each night for 14 days. Sleep efficiency was calculated using the ratio of the time spent sleeping to the total amount of time that was spent in bed. Retraction of the rotator cuff tear was classified using the Patte staging system. Results: This study included 36 patients: 18 with Patte stage 1 disease, 14 with Patte stage 2 disease, and 4 patients with Patte stage 3 disease. During the study, 25 participants wore the monitor on multiple nights, and ultimately their data was used for the analysis. No difference in the median sleep efficiency was appreciated amongst these groups (P>0.1), with each cohort of patients demonstrating a generally high sleep efficiency. Conclusions: The severity of retraction of the rotator cuff tear did not appear to correlate with changes in sleep efficiency for patients (P>0.1). These findings can better inform providers on how to counsel their patients who present with complaints of poor sleep in the setting of full-thickness rotator cuff tears.

• Sleep Medicine and Psychophysiology
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• v.19 no.2
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• pp.63-67
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• 2012

The reciprocal interaction between sleep and pain has been reported by numerous studies. Patients with acute or chronic pain often complain of difficulty falling asleep, frequent awakenings, shorter sleep duration, unrefreshing sleep, and poor sleep quality in general. According to the majority of the experimental human studies, sleep deprivation may produce hyperalgesic changes. The selective disruption of slow wave sleep has shown this effect more consistently, while results after selective REM sleep deprivation remain unclear. Patients with chronic pain have a marked alteration of sleep structure and continuity, such as frequent sleep-stage shifts, increased nocturnal awakenings, decreased slow wave sleep (SWS), decreased rapid eye movement (REM) sleep, and alpha-delta sleep. Many analgesic medications can alter sleep architecture in a manner similar to the effects of acute and chronic pain, suppressing SWS and REM sleep.