• Journal of Korean Biological Nursing Science
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• v.23 no.2
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• pp.151-158
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• 2021

Purpose: The purpose of this study was to investigate sleep quality in older adults in nursing home with objective data collection. Methods: Participants included 74 older adults in nursing homes in Korea aged 65 years or above. Data were collected using a wearable device (Fitbit), salivary melatonin level and Sleep Disorder Inventory (SDI). The Pearson correlation coefficient was calculated to examine whether there was any correlation between sleep-related variables such as Total Sleep Time (TST), Rapid Eye Movement (REM) sleep, shallow sleep, deep sleep, salivary melatonin level and SDI. Results: There were distortion of sleep structure, as TST comprised short REM sleep (15.93±5.47%), long shallow sleep (74.18±8.08%) and short deep sleep (9.89±5.03%). Also, salivary melatonin levels were low (15.06±7.77 pg/mL). Moreover, we found than melatonin was significantly associated with TST (r = .251, p= .044), REM sleep (r= .294, p= .020) and deep sleep (r= .391, p= .002). But there was no correlation between SDI and other sleeprelated variables. Conclusion: These findings highlight that insufficient sleep structure is associated with the salivary melatonin level among older adults in nursing home. We suggest developing programs to promote sleep quality of older adults in nursing homes.

• Journal of Korea Multimedia Society
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• v.25 no.8
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• pp.1109-1121
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• 2022

As the demand for quality sleep increases in modern society, the importance of sleep technology has increased. Recently, development of sleep environment improvement products and research on the user's sleep improvement have been activated. Representatively, user sleep pattern analysis research is being conducted through the existing polysomnography, but it is difficult to use it in the sleep environment of daily life. Therefore, in this paper, we propose a system design that can provide a customized deep sleep service to users by detecting sleep disturbance factors in a motion bed environment. In order to improve the user's sleep satisfaction, a logistic regression-based sleep pattern analysis model is proposed and accuracy and significance are verified through experiments. And to improve user's sleep satisfaction, we propose a logistic regression-based sleep pattern analysis model and verify accuracy and significance through experiments. The proposed system is expected to improve the user's sleep quality and effectively prevent and manage sleep disorders.

• 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.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.181-185
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• 2002

The purpose of this study was to find out the relationship between sleep physiological signals data and subjective feeling of sleep quality. Sixteen subjective were investigated and they slept on both comfortable mattress and uncomfortable mattress. Information of sleep stage is one of the most important clues for sleep quality. Polysomnography is basically the recording of sleep. The several channels of brain waves (EEG), eyes (EOG), chin movements (EMG) and heart (ECG) were monitored. Sixteen subjects spent 6 days and nights in the laboratory and the data of sleeping 7h for each of 3 nights was analyzed. Percentage of deep sleep (III and IV, sleep efficiency, WASO, stage 1 and subjective feeling of sleep quality were significantly affected with mattress types (comfortable and uncomfortable mattress). When subjects slept on comfortable beds, percentage of deep sleep and sleep efficiency were higher than those of uncomfortable bed. The percentages of wake after sleep onset and stage 1 were lower when subject slept in a comfortable bed. The subjective feeling of sleep quality agreed with the recorded sleep data also.

• Journal of Society of Preventive Korean Medicine
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• v.27 no.1
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• pp.89-98
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• 2023

Objectives : This study collected sleep information by wearable device in the Korean medicine Daejeon citizen cohort (KDCC). It was measured based on the sleep record information measured by wearing a Fitbit, and the possibility of clinical use was examined for compliance with objective sleep collection. Based on compliance, the possibility of clinical use was examined. Methods : After surveying personal information and PSQI(Pittsburgh Sleep Quality Index), sleep information was collected by Fitbit for 14 days. Compliance was measured based on sleep record information by Fitbit. Compliance was analyzed by sex, age, BMI(Body Mass Index), and sleep group(deep/poor). Results : The number of participants was 730, and the compliance was 94.3%, and the compliance group was 675(92.5%). The age of the participants varied from 30 to 60 years old, and the average age was 46±6.7 years. There were 218 males and 512 females. Young people have high compliance. Males are more compliance than females. As the BMI score decreased in the 30s, the compliance was higher. The underweight group in all age groups had 100 compliance. The underweight group was all female. The low compliance groups were that 30 years males (obesity level2), 50 years females (overweight group), and 50 years females (obesity level2). There was no significant difference in compliance between deep sleep group and poor sleep group. In deep sleep group, females showed higher compliance. In poor sleep group, males showed higher compliance. The average duration of Fitbit usage among participants was 20.1 days. The compliant group wore the device for an average of 21.3 days, while the non-compliant group wore it for only 5.2 days. Of the compliant group, 86.9% (73.8% of all participants) continued to wear the Fitbit after the recommended 14-day period, and 50.8% wore it for more than 20 days. Conclusions : This study showed the possibility of adaptation for wearing a Fitbit for collecting objective sleep information. It is judged that the compliance is high because it was worn for more than 13.2 days out of the 14 days required. It is considered meaningful because the compliance was measured based on the sleep information by Fitbit, not the questionnaire. As the data on objective sleep time is collected automatically, we believe that the burden on participants after the study period is not significant for a certain period. Compliance may be even higher for cohorts related to illnesses and with doctor's orders, rather than for the general population.

• Proceedings of the ESK Conference
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• 1992.10a
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• pp.96-103
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• 1992

To get a comfortable sleep, the most improtant thing is how well we do thermorgulate during the rest in bed before sleeping as well as during sleep. In other works, the ambient temperature of the sleeping room is very improtant in the organization of human sleep. In recent years, the effect of ambient temperature on human sleep has been increasingly stueided. These studies were primarily concerned with the relation between thermorgulatory processes and sleep, and more precisely with the findings that various thermoregulatory processes are inactivated or severly curtailed during REM sleep in a number of animals, also that panting and shivering in heat and cold, respectively, cease during REM sleep in cats. Haskel et al. noted that although REM sleep latency was increased at thigh and low temperature. REM sleep was depressed to a greater extent by lower than by higher temperatures whereas the reverse was obseved for SWS. It has also been found that a load omposed upon thermoregulatory mechanisms should markedly affect sleep processes, and that conversely, sleep in conditions of thermic stress should interfere with adequate thermorgulatory reactions. Sleep in an animala under thermic stress is, on the whole, both shorter and less deep than under normal thermic conditions.

• Progress in Medical Physics
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• v.5 no.2
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• pp.69-76
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• 1994

The disturbance of sleep is usually only one of many factors considered in most studies of noise. When exposed to noise during sleep, the general response of human according to stages of sleep is investigated. The percentage of deep sleep and the number of wakings are studied for continuous traffic noise.

• The Journal of Korean Physical Therapy
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• v.34 no.5
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• pp.272-277
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• 2022

Purpose: This study compared the subjective and objective sleep quality between subjects with and without thoracic hyper-kyphosis. Methods: Forty participants were divided into a hyper-kyphosis (n=17) and normal group (n=17) by thoracic spinal angle measurement. The subjective sleep quality was measured using PSQI, a self-report, and objective sleep quality was measured using an actigraphy that measures time according to sleep patterns. Results: The PSQI scores of subjects with thoracic hyper-kyphosis were significantly higher than those with normal thoracic curvature (p=0.013). The total sleep time and real sleep time were less in subjects with hyper-kyphosis than in normal subjects (p=0.006; p=0.029). The light sleep time was less in subjects with excessive spondylolisthesis than in normal subjects (p=0.010). Light sleep time was less in those with hyper-kyphosis, but deep sleep time was similar to the subjects with a normal thoracic curvature (p=0.003; p=0.140). Conclusion: Subjects with thoracic hyper-kyphosis had a decrease in subjective sleep quality, such as sleep discomfort, and objective sleep quality, such as a decrease in sleep time compared to normal subjects.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.57-58
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• 2022

Sleep apnea (SA) is a common chronic sleep disorder that disrupts breathing during sleep. Clinically, the standard for diagnosing SA involves nocturnal polysomnography (PSG). However, this requires expert human intervention and considerable time, which limits the availability of SA diagnoses in public health sectors. Therefore, ECG-based methods for SA detection have been proposed to automate the PSG procedure and reduce its discomfort. We propose a preprocessing method to convert the one-dimensional time series of ECG into two-dimensional images using the Gramian Angular Field (GAF) algorithm, extract temporal features, and use a two-dimensional convolutional neural network for classification. The results of this study demonstrated that the proposed method can perform SA detection with specificity, sensitivity, accuracy, and area under the curve (AUC) of 88.89%, 81.50%, 86.11%, and 0.85, respectively. Our experimental results show that SA is successfully classified by extracting preprocessing transforms with temporal features.

• Sleep Medicine and Psychophysiology
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• v.2 no.2
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• pp.138-145
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• 1995

The causes of complicated chronic insomnia are very various and interact with vicious circle. Patient with this insomnia has generally a strong fear and frustration about failing to control of sleep and a deep mistrust toward doctor. To solve this complicated problems detailed history taking and sleep questionnaires are needed with objective polysomnography. Through these procedures, doctor should clarify causes of insomnia and explain them to patient in details and kindly. This process would be very helpful to restore the mistrustful relationship between patient and doctor and reduce patient's vague fear for insomnia. In treatment of complicated chronic insomnia, it is most important for patient to understand his problems and participate in the treatment schedule actively with assurance. Also doctor should encourage patient persistently not to be drop out. Most important factor for prognosis is patient's personality. Causes of complicated chronic insomnia are like these, overdose of hypnotics and sedatives, daily drinking alcohol with hypnotics, insomnia associated depression, delayed sleep phase syndrome, sleep state misperception, marked fear for insomnia, hyperarousal at bed, insomnia associated periodic leg movement and sleep apnea, chronic hypnotic insomnia, and immature personality. And possible treatments of these insomnias were discussed.