• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.423-424
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• 2021

In this paper, we propose a system that collects data from sensors that detect the sleeping environment and adjusts the sleeping environment optimally based on the environment to help you get a good night's sleep. The sleep environment analysis is based on the determination of the sleep stage by detection of twisting through the load cell. In addition, based on data such as temperature, humidity, and illuminance, heat devices, humidifiers, blinds, etc. are controlled to create an environment in which to have a good sleep. The sleep environment control according to the sleep state can reduce fatigue when waking up by inducing a sleep state that is easy to wake up.

• KIPS Transactions on Computer and Communication Systems
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• v.7 no.7
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• pp.175-182
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• 2018

The purpose of this study is to analyze the effect of sleep environment on individual sleep and to calculate optimal sleep environment. The input and output data sets are selected and the optimized sleep environment information is calculated using the neuro-fuzzy technique. Provides optimal sleep environment considering sleep duration. The arousal ratio calculated by the proposed method is 12%, which is at least 5% lower than the previous studies.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.319-320
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• 2010

In this paper, provide the optimal sleep environment of individual by extracting the simulation model based on that collect sleep environment data of bedroom to sleeping, and analyzing the relationship between conditions with obtained data and sleep. In addition, it was to provide a more stable sleep solution by defining different and pattern from sleep situation according to physical condition such as fatigue ratio, alcohol ratio, fasting ratio, etc. depending on the sleep process. Therefore, it change the proper indoor environment and help to enjoy life more pleasant.

• Journal of the Korea Society of Computer and Information
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• v.16 no.1
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• pp.47-52
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• 2011

This paper collect sleep environment data of bedroom to sleeping, and analyzing the relationship between conditions with obtained data and sleep. We provide the optimal sleep environment of individual by extracting the simulation model based on it. The experiments was using temperature/humidity sensor(SHT11) and ambient light sensors(GL5507). For extraction of tossing and turning, we use difference image method in motion extraction from video. In addition, the information of weight can affect to sleep, it was entered such as ratio of fatigue, drinking, empty stomach. As a result, we are able to extract the optimal sleep environment. The future, we will try to improve to help to lead more pleasant daily life providing proper indoor environment changes depending on the situation even a partial of organic ubiquitous living environments such as eating, work ete. as well as certain sleep circumstances.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.11
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• pp.2485-2490
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• 2010

In this paper, gather the sleep environment data of bedroom to sleeping and analyze the relationship between the obtained conditional data and the sleep. Based on this, system provide the optimal sleep environment of individual person by extracting the simulation model. The experiments of system was using H-MOTE2420 sensor composed of temperature/humidity sensor and ambient light sensors. We use difference image method in motion extraction from video for extraction of tossing and turning. In addition, it was entered such as ratio of fatigue, ratio of drinking, ratio of empty stomach as the information of weight can affect to sleep. Resultingly of experience, we can extract the optimal sleep environment. From now on, we will try to enhance to help to lead more pleasant daily life providing proper indoor environment changes depending on the situation even a partial of organic living environments such as eating and work as well as special sleep circumstances.

• Journal of Korean Academy of Nursing
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• v.50 no.5
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• pp.646-657
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• 2020

Purpose: The purpose of this study was to identify the quality of sleep in novice and experienced shift work nurses and compare the factors associated with their quality of sleep. Methods: We analyzed the data of 192 and 256 novice and experienced nurses, respectively. The quality of sleep, sleep hygiene, job stress, and fatigue were measured using Insomnia Severity Index, Sleep Hygiene Practice Scale, the Korean Occupational Stress Scale, and Fatigue Severity Scale. Data were analyzed using SPSS 25.0 to calculate descriptive statistics and logistic regression. Results: Sleep quality was lower in experienced nurses (12.55 ± 5.71) than in novice nurses (11.18 ± 5.78). Fatigue was more severe in experienced nurses (4.47 ± 1.13) than in novice nurses (4.23 ± 1.12). In the logistic regression, factors related to sleep quality in novice nurses were sleep hygiene (odds ratio; OR = 1.06, p < .001) and fatigue (OR = 2.49, p < .001). Factors related to sleep quality in the experienced nurses were also sleep hygiene (OR = 1.04, p = .001) and fatigue (OR = 1.53, p = .012). Conclusion: Sleep quality of experienced nurses is lower than those of novice nurses. Factors associated with sleep quality in novice and experienced nurses are equally identified as sleep hygiene and fatigue. Therefore, personal efforts to improve sleep hygiene, such as providing comfortable sleep environment, are needed. Furthermore, organized efforts to decrease fatigue, such as constructing a working environment with a bright light at night and providing a fatigue-decreasing program that includes meditation, are required.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.21 no.4
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• pp.403-412
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• 2014

Purpose: Shift work disrupts the synchronization between the human biological clock and the environment. Sleep disturbances are common for shift work nurses, and may threaten patient safety. This study was done to investigate the sleep characteristics and medication errors (ME) of intensive care unit (ICU) nurses who work shifts, and ascertain if there is an association between these factors. Methods: Data were collected using a self-report questionnaire from 126 ICU nurses on three shifts. Collected data included their sleep characteristics including sleep patterns and sleep disturbances, and ME for the past 2 weeks. Results: There were significant differences in sleep duration and sleep latency according to shift. Day shift nurses had the shortest sleep duration, and their sleep latency was the longest (about 49 minutes) compared to nurses on evening and night shifts; 54% reported sleep disturbances, 16% experienced ME, and among these nurses 50% were on the night shift. Logistic regression analysis revealed significant associations between nurses' sleep duration and ME (adjusted OR 0.52 [95% CI 0.32-0.85]). Conclusions: The results confirmed that shift work nurses in the ICUs experience sleep disturbance, and that less sleep is associated with ME.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.663-668
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• 2022

As the number of people who experience sleep disorders is increasily growing, users' desire to improve their sleep quality has also increased. Acoordingly, the 'Sleeptech' market is showing a steady growth. This study designs and proposes a system after consideration of existing related research that can help modern people overcome sleep disorders, which is based on the necessity for customized sleep hygien service. This system analyzes user's sleep data collected through smartphone built-in sensors to calculate sleep patterns, provides customized sleep hygiene-based solutions to users through collaborative filtering, and provides an environment suitable for sleep through the automatic control of IoT devices. This method of using sleep data is expected to contribute to the improvement of the quality of life of modern people suffering from sleep disorders, which results from expansion to Sleeptech market as well as improvement of users' sleep habits.

• Korean Journal of Occupational Health Nursing
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• v.23 no.4
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• pp.235-244
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• 2014

Purpose: The purpose of this study was to identify quality of sleep and its influencing factor among middle-aged male workers. Methods: The subjects of this study were 411 middle-aged male workers living in Seoul and Gyeonggi-do. The data were based from self-reported using structured questionnaires asking about low urinary tract symptoms, circadian rhythm, quality of life and sleep quality including general characteristics. The data were collected from September 11 to October 31, 2013 and analyzed by t-test, one-way ANOVA, Pearson correlation coefficient and hierarchical regression. Results: Mean score of the sleep quality was $5.03{\pm}2.57$ (range: 0~21) and reported as bad sleep quality in 55.7%. Low urinary tract symptoms (${\beta}$=.30, p<.001), circadian rhythm (${\beta}$=-.17, p<.001), quality of life (${\beta}$=-.14, p<.001) were shown as significant association of sleep quality. Conclusion: Strategies to improve sleep quality in middle-aged male workers are necessary and nursing intervention should be developed to improve education program for prevention and management of low urinary tract symptoms. It is also necessary to legalize the institutional devices to upgrade work environment and to place regulations on overtime at work places in order for these workers to obtain sufficient sleep time for recovery of biological rhythms and improving sleep quality.

• International Journal of Internet, Broadcasting and Communication
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• v.11 no.4
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• pp.71-75
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• 2019

Sleep apnea is a disease that causes various complications, and the polysomnography is expensive and difficult to measure. The purpose of this study is to develop an unrestricted wearable monitoring system so that patients can be examined in a familiar environment. We used a method to detect sleep apnea events and to determine sleep satisfaction by non-constrained method using SpO2 measurement sensor and 3-axis acceleration sensor. Heart rate and SpO2 were measured at the finger using max30100. After acquiring the SpO2 data of the user in real time, the apnea measurement algorithm was used to transmit the number of apnea events of the user to the mobile phone using Bluetooth (HC-06) on the wrist. Using the three-axis acceleration sensor (mpu6050) attached to the upper body, the number of times of tossing and turning during sleep was measured. Based on this data, this algorithm evaluates the patient's tossing and turning during sleep and transmits the data to the mobile phone via Bluetooth. The power source used 9 volts battery to operate Arduino UNO and sensors for portability and stability, and the data received from each sensor can be used to check the various degree between sleep apnea and sleep tossing and turning on the mobile phone. Through thisstudy, we have developed a wearable sleep apnea measurement system that can be easily used at home for the problem of low sleep efficiency of sleep apnea patients.