• Journal of Sensor Science and Technology
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• v.26 no.4
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• pp.280-285
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• 2017

This paper presents a respiration measurement sleeping pillow based on pressure sensors. The respiration measurement sleeping pillow system consists of a sleeping pillow, an interface circuit, a respiration measurement system, and four force-sensitive resistor(FSR) sensors attached at the bottom of the sleeping pillow. The FSR sensors are used to detect the respiration signals induced by the body movement while breathing. The respiration signals of a twenty health man were measured and analyzed by utilizing the respiration measurement sleeping pillow system. The pillow system could detect the respiration signals and had similar characteristics to the chest type BIOPAC respiration sensor used by medical doctors. The respiration rates of ten subjects were also measured. The average measurement accuracy was about 98.8%. The research results showed that this pillow system can be used to detect and analyze the respiration signal when sleeping for the better sleep management.

• Fashion & Textile Research Journal
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• v.8 no.6
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• pp.713-720
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• 2006

Heat conductivity, height, size, elasticity of pillow, stability of shape, hygroscopicity, ventilation, temperature and easy movability, and so on, are considered to be some of major conditions that affect the comfortable sleep. Considering those factors together, the thermal properties, height, shape and feeling of touch, etc, of pillow must be taken into account. Though studies have been conducted to figure out the physical properties of mattress or pillows from the perspective of factors related to the environment of sleep, they are not enough to be used as an index to evaluate the qualitative aspect of sleep. This study tries to consider the effect of pillow filling materials on the comfortable sleep, for which EEG, ECG, EOG, EMG, RT, etc, are to be measured in an attempt to provide the basic data required in proposing the condition that may lead to a sound and comfortable sleep. Three types of pillows that are sold in the market were used for this research in order to evaluate the quality of sleep depending on the filling materials of pillow. All data were statistically processed and the following conclusions were drawn. It was found that the pillow with feathers provided the best comfort as the pillow A turned out to have the shortest sleeping latency(SL) from the perspective of comfort. The pillow B which used the polyethylene is deemed to be suitable for fatigue relieving purpose as it turned out to have the highest slow wave sleep(SWS), but no statistically significant difference was validated. Moreover, the pillow C which used the natural wool was found to have the narrowest contacting area of the pillow and head and provide a great warm heat comfort that may led to a sound sleep because the temperature below the pillow took the longest time to rise.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.2
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• pp.223-228
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• 2016

People try to maintain optimal sleep activity to a changing attitude 20-30 times while sleeping 7-8 hours a day. In order to provide optimal sleep, we need to develop sensing device for apply effective various sleep data acquired through display device that can provide program and information which process and analyze information printed out from sensor and sensing system. In this paper, we analyze sleep pattern to detect the toss and turn while a person's sleeping and we develop a wellness pillow that can be active on sleep health management based on the analyzed data for sleep patterns.

• Journal of Sensor Science and Technology
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• v.27 no.6
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• pp.407-413
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• 2018

Most sleep apnea patients exhibit severe snoring, and long-lasting sleep apnea may cause insomnia, hypertension, cardiovascular diseases, stroke, and other diseases. Although polysomnography is the typical sleep diagnostic method to accurately diagnose sleep apnea by measuring a variety of bio-signals that occur during sleep, it is inconvenient as the patient has to sleep with attached electrodes at the hospital for the diagnosis. In this study, a diagnostic pillow is designed to measure respiration, heart rate, and snoring during sleep, using only one polyvinylidene fluoride (PVDF) sensor. A PVDF sensor with piezoelectric properties was inserted into a specially made instrument to extract accurate signals regardless of the posture during sleep. Wavelet analysis was used to identify the extractability and frequency domain signals of respiration, heart rate, and snoring from the signals generated by the PVDF sensor. In particular, to separate the respiratory signal in the 0.2~0.5 Hz frequency region, wavelet analysis was performed after removing 1~2 Hz frequency components. In addition, signals for respiration, heart rate, and snoring were separated from the PVDF sensor signal through a Butterworth filter and median filter based on the information obtained from the wavelet analysis. Moreover, the possibility of measuring sleep apnea from these separated signals was confirmed. To verify the usefulness of this study, data obtained during sleeping was used.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.4
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• pp.212-217
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• 2019

In this paper, a sleep management pillow system for snoring detection and respiration measurement is investigated. The sleep management pillow system consists of four force sensing resistor(FSR) sensors, two microphones(MIC), a pillow, a measurement system. Four FSR sensors attached at the bottom part of the pillow are used for respiration measurement and snoring detection. Two microphones located at the middle left and right of the pillow are utilized for only snoring detection. The respiration and the snoring of ten young people were measured using the sleep management pillow system composed of a data acquisition board, interface circuit, and personal computer. The measurement accuracy of the respiration was about 98% and the measurement accuracy of the snoring was about 97%. The experiment results show that the sleep management pillow system can be used for snoring detection and respiration rate measurement during sleeping.

• The Journal of the Convergence on Culture Technology
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• v.4 no.1
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• pp.331-335
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• 2018

A pillow was fabricated through CAE(Computer Aided Engineering) and 3D printing, which can adjust automatically the height of the pillow when lying sideways and backwards according to the sleeping posture. The target height difference of the pillow was about 1.0 cm ~ 1.5 cm when the head weight difference was about 1.2 kg. Instead of using a complex mechanical device, it was based on an arch structure made of TPU. From the simulation, the optimum model was designed through series combination and the results were compared with the experimental ones. The final product had a height difference of about 2 cm according to the lying posture.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.425-427
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• 2021

Entering the modern society, due to changes in daily life as well as social life, the sleep deprivation and unsatisfactory sleep environment that modern people have, ranked the lowest in the sleep deprivation nation in the world and the lowest in the nation considered to be sleep deprivation. This is about 'sleep pillows using Arduino,' which can improve the 'sleep environment', which is the 2nd largest cause of sleep deprivation. The few minutes before you go to sleep, the moment of time, can determine the quality of your sleep, and the quality of your sleep determines the satisfaction of your daily life. Using Arduino, you can improve the quality of your sleep through various functions. Through Arduino, you can create a sleeping environment for the sleeper by adjusting the sleeper's breathing measurement, lighting, and Bluetooth speaker and create an environment that suits you. Through this, we will be able to improve the sleep deprivation of modern people and have a more prosperous life.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.2
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• pp.105-110
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• 2019

People sleep about one-third of their lives and their sleep time varies according to age. Adult usually sleep 8 hours a day. However, that dose not guarantee good sleep. The cause of this is due to sleep disorders like snoring and sleep apnea. In this paper, the smart pillow for detecting snoring among sleep disorders is investigated. This pillow consists of two microphones located on the left and right side of the pillow. For simple detecting, the snoring signal was converted into the pulse using a peak detection circuit. The decision of the snoring occurrence was by pulse duration. The accuracy of the snoring detection was about 97%. The research results show that the smart pillow can be use to detect the snoring during sleeping.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.3
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• pp.603-610
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• 2020

The sleep measurement system is important to detect sleep disturbances as early as possible to be diagnosed and treat the diseases quickly. This paper presents design of system to measure the quality of sleep by using nine accelerometer sensors embedded in the pillow to detect the acceleration of limb movement, e.g. head movements. The participants were asked to sleep using a smart pillow for five days. While sleeping, participants are recorded using a camera on a computer. After awakening, participants were asked to fill out a post-sleep questionnaire. Spearman's correlation was performed to test the correlation of gross body movement per minute rate with post-sleep questionnaire questions. Finally, the seven score of sleep quality were tested with gross body movement per minute rate. The result is the higher gross body movement per minute during sleep represented lower sleep quality.

• Journal of Korean Neurosurgical Society
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• v.55 no.3
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• pp.148-151
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• 2014

Objective : Posture-induced radial neuropathy, known as Saturday night palsy, occurs because of compression of the radial nerve. The clinical symptoms of radial neuropathy are similar to stroke or a herniated cervical disk, which makes it difficult to diagnose and sometimes leads to inappropriate evaluations. The purpose of our study was to establish the clinical characteristics and diagnostic assessment of compressive radial neuropathy. Methods : Retrospectively, we reviewed neurophysiologic studies on 25 patients diagnosed with radial nerve palsy, who experienced wrist drop after maintaining a certain posture for an extended period. The neurologic presentations, clinical prognosis, and electrophysiology of the patients were obtained from medical records. Results : Subjects were 19 males and 6 females. The median age at diagnosis was 46 years. The right arm was affected in 13 patients and the left arm in 12 patients. The condition was induced by sleeping with the arms hanging over the armrest of a chair because of drunkenness, sleeping while bending the arm under the pillow, during drinking, and unknown. The most common clinical presentation was a wrist drop and paresthesia on the dorsum of the 1st to 3rd fingers. Improvement began after a mean of 2.4 weeks. Electrophysiologic evaluation was performed after 2 weeks that revealed delayed nerve conduction velocity in all patients. Conclusion : Wrist drop is an entrapment syndrome that has a good prognosis within several weeks. Awareness of its clinical characteristics and diagnostic assessment methods may help clinicians make diagnosis of radial neuropathy and exclude irrelevant evaluations.