• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.183-184
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• 1998

Respiration monitoring is important in many clinical situations due to its relationship to vitality. But present commercial monitoring systems are bulky and expensive, so they are inadequate to be used for long term recording or out-patients application. We have developed a low cost, low power, handhold respiration monitoring system based on airflow measurement. Respiration flow is indirectly detected using a thermister or a themocouple sensor. Real time recording of respiration rate, abnormality detection and apnea alarming are available.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.05a
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• pp.514-517
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• 2003

Oxygen supply is one of the most basic things in human body. Breathing is controlled by the lungs' stationary function and the respiratory center which is in the mesulla oblongata. Nothing but, the external breathing that air movement between the lungs and atmosphere and the internal breathing that cellular air movement between the hemoglobin and a single cell. The adult's number of times of the respirations is about 15∼20 per 1 minute, but it depends ages, exercise, temperature, disease, etc. The important thing in detecting the respiration is that doing it in object person's resting time. Detecting the respiration have to be done without attracting any attention of object person. In present using method is detecting the pulse with catching an object person's wrist and observing the object person's movement. In this paper, we propose the mobile respiration detection diagnostic system using ultrasound sensing method that does not be influenced by the inertia error and the pressure error.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.357-359
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• 2009

In this paper, the 2.4GHz doppler radar system consisting of the doppler radar module and a baseband module were designed to detect heartbeat and respiration signal without direct skin contact. A bio-radar system emits continuous RF signal of 2.4GHz toward human chest, and then detects the reflected signal so as to investigate cardiopulmonary activities. The heartbeat and respiration signals acquired from quadrature signal of the doppler radar system are applied to the pre-processing circuit, amplification circuit, and the offset circuit of the baseband module. ECG(electrocardiogram) and reference respiration signals are measured simultaneously to evaluate the doppler radar system. As a result, the respiration signal of doppler radar signal is detected to 1m without complex digital signal processing. The sensitivity and calculated from I/Q respiration signal were $98.29{\pm}1.79%$, $97.11{\pm}2.75%$, respectively, and positive predictivity were $98.11{\pm}1.45%$, $92.21{\pm}10.92%$, respectively. The sensitivity and positive predictivity calculated from phase and magnitude of the doppler radar were $95.17{\pm}5.33%$, $94.99{\pm}5.43%$, respectively. In this paper, we confirmed that noncontact real-time heartbeat and respiration detection using the doppler radar system has the possibility and limitation.

• Journal of Biomedical Engineering Research
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• v.38 no.4
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• pp.153-162
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• 2017

The present study proposes a system that can detect sleep-disordered breathing automatically using an air mattress and oxygen saturation. A thin air mattress was fabricated to reduce discomfort during sleep, and respiration signals were acquired. The system was configured to be synchronized with a polysomnography to receive signals simultaneously with other bio-signals. The present study has been conducted with nine adult male and female patients with sleep-disordered breathing, and sleep-disordered breathing events have been detected by applying the signals acquired from the subjects to the rule-based detection algorithm. The sensitivity and positive predictive values were found to evaluate the performance of the system, which are 91.4% and 89.7% for all events, respectively. The comparison of apnea hypopnea index(AHI) between the polysomnography and the proposed method showed squared R-value of 0.9. This study presents the possibility of detecting sleep-disordered breathing at hospitals or homes using the proposed system.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.10
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• pp.733-740
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• 2004

In this paper, an improved algorithm for the extraction of respiration signal from the electrocardiogram (ECG) is proposed. The whole system consists of two-lead electrocardiogram acquisition (lead Ⅰ and Ⅱ), baseline fluctuation elimination, R-wave detection, adjustment of sudden change in R-wave area using moving average, and optimal lead selection. In order to solve the problem of previous algorithms for the ECG-derived respiration (EDR) signal acquisition, we proposed a method for the optimal lead selection. An optimal EDR signal among the three EDR signals derived from each lead (and arctangent of their ratio) is selected by estimating the instantaneous frequency using the Hilbert transform, and then choosing the signal with minimum variation of the instantaneous frequency. The proposed algorithm was tested on 15 subjects, and we could obtain satisfactory respiration signals that shows high correlation (r>0.9) with the signal acquired from the chest-belt respiration sensor.

• Journal of electromagnetic engineering and science
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• v.3 no.1
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• pp.45-49
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• 2003

Wireless life signal detecting system is implemented with using the mechanism of Doppler Effect. This system can measure the respiration and heart rates with the periodic movement of skin and muscle near the heart. The system is consisted of antenna, RF transmitter, receiver, and display part. We did use two operating frequencies at 1.9 ㎓ and 10 ㎓. Firstly, the link budget about detecting system is analyzed and the signal detected from the system is compared with electrocardiogram(ECG) of monitor which is using for patient monitoring in hospital. Secondly, the detection of vital sign is also performed according to the different distances, and including behind the wall.

• Journal of Biomedical Engineering Research
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• v.36 no.2
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• pp.48-53
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• 2015

Sudden infant death syndrome(SIDS) continues to be general cause of infant death. Also, apnea is supposed to be one of the main risk factor of SIDS. Therefore, Infant's respiratory monitoring and real-time apnea detection is very important to prevent SIDS. In this study, we proposed a non-contact home monitoring system for infant's respiration using Doppler radar in order to prevent SIDS. The respiration data were acquired from a commercialized baby simulator(Simbaby$^{TM}$) using a Doppler radar. To evaluate a performance of the proposed system, the simulator was placed in a supine and prone position and the chest belt was used simultaneously as a reference signal. As a result, correlation coefficients between respiration rates of Doppler radar and the chest belt in each position were 0.95(p < 0.001) and 0.98(p < 0.001), respectively. The averages of difference were $-0.29{\pm}5.21(mean{\pm}1.96{\cdot}$ standard deviation) in supine and $-0.12{\pm}3.05$ in prone from Bland-Altman analysis. The results indicated an excellent performance in detecting apnea with a sensitivity of 100% and a positive predictive value of 100% in each posture respectively. These results demonstrated that a proposed Doppler radar system is suitable for non-contact respiratory monitoring in order to prevent SIDS of infant.

• Journal of IKEEE
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• v.11 no.1 s.20
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• pp.24-29
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• 2007

In this paper, we developed a Mac-Yule measurement system which consider psychological stable state of patience. The developed system consist with a hardware device that can derive a EEG, respiration and pulse wave, and a software which acquire a biological signal and signal processing The EEGs are derived with bipolar method from frontal head. The respiration signals obtain from nasal front with a transducer which consist with thermistor bridge. The pulse waves are detected from earlobe with photoplethysmograph method. A power spectrum of EEG are used as the decision parameters of psychological stable state of patience. The decision of Mac-Yule are defined as origin text method that of numbers of pulse to 1 respiration period. As the results of experiment with developed system, we could have a spectrum band discretion of EEG signal, stable respiration signal detection and automatic gain controlled pulse signal with realtime. And then, we could detect Mac-Yules from processed signals.

• Journal of Korea Multimedia Society
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• v.21 no.3
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• pp.382-390
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• 2018

A major accident occurring on the bed is falls that occur during at times when the care of nurses or protectors is inadequate, which is fatal to patients or the elderly. In particular, Enuresis or sleepiness caused by sleep apnea increases the risk of falls. Therefore, it is very important to detect falls and sleep apnea of patients without infringing privacy in the bed to patient's safety and accident prevention. In this paper, we reviewed the technologies developed for bed monitoring and implemented a non-intrusive monitoring system. The Occupancy Sensor allows the temperature of the bed and surrounding area to be extracted to enable track of the patient's motion. The Doppler Radar detects the patient's movements at normal times and the respiration state when patients have no movement during sleeping. It is specially designed for real-time monitoring of falling and respiration during sleeping through contactless multi-sensing while solving patient's privacy problems.

• Journal of Biomedical Engineering Research
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• v.33 no.1
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• pp.39-46
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• 2012

Electrical impedance tomography(EIT) can produce functional images with conductivity distributions associated with physiological events such as cardiac and respiratory cycles. EIT has been proposed as a clinical imaging tool for the detection of stroke and breast cancer, pulmonary function monitoring, cardiac imaging and other clinical applications. However EIT still suffers from technical challenges such as the electrode interface, hardware limitations, lack of animal or human trials, and interpretation of conductivity variations in reconstructed images. We improved the KHU Mark2 EIT system by introducing an EIT electrode interface consisting of nano-web fabric electrodes and by adding a synchronized biosignal measurement system for gated conductivity imaging. ECG and respiration signals are collected to analyze the relationship between the changes in conductivity images and cardiac activity or respiration. The biosignal measurement system provides a trigger to the EIT system to commence imaging and the EIT system produces an output trigger. This EIT acquisition time trigger signal will also allow us to operate the EIT system synchronously with other clinical devices. This type of biosignal gated conductivity imaging enables capture of fast cardiac events and may also improve images and the signal-to-noise ratio (SNR) by using signal averaging methods at the same point in cardiac or respiration cycles. As an example we monitored the beat by beat cardiac-related change of conductivity in the EIT images obtained at a common state over multiple respiration cycles. We showed that the gated conductivity imaging method reveals cardiac perfusion changes in the heart region of the EIT images on a canine animal model. These changes appear to have the expected timing relationship to the ECG and ventilator settings that were used to control respiration. As EIT is radiation free and displays high timing resolution its ability to reveal perfusion changes may be of use in intensive care units for continuous monitoring of cardiopulmonary function.