• Journal of Korea Multimedia Society
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• v.13 no.7
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• pp.973-982
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• 2010

In this paper, we proposed the single-channel adaptive noise canceller for the enhancement of heart sound (HS) in the auscultation signal. In case of either normal or emergency, a HS diagnosis is difficult due to the various signal source in the chest. Therefore, the HS enhancement is necessary. The conventional active noise canceller(ANC) has two channel, main signal and reference signal. For signal channel, the reference signal in ANC was generated by the proposed HS analyser and BS-Gate based on the characteristic of HS. This reference signal is suitable to the ANC condition. Experimental data were acquisited from MP36, SS30L in BIOPAC Inc., By the experiment, we confirmed that the proposed single-channel ANC was efficient for HS enhancement. And by the comparison with active linear enhancement, it was validate that the proposed ANC is not affected by the variation of a heartbeat.

• Journal of Satellite, Information and Communications
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• v.12 no.1
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• pp.28-33
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• 2017

In this paper, new signal model for bio-signal detection, i.e heart beat and respiration, using CW radar. Most research on this similar topic are based on the conventional signal model which is not correct in envisaging reflected signal from the human body. The system developed based on this conventional model can not predict exact performance of the system. So in this paper modified signal model for bio-radar is proposed and then simulation for detecting heartbeat and respiration signal in AWGN, multipath environment. The detection performance difference between two signal models are discussed.the modified

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.42-47
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• 2001

Analyzing the ECG signal, we can find heart disease, for example, arrhythmia and myocardial infarction, etc. Particularly, detecting arrhythmia is more important, because serious arrhythmia can take away the life from patients within ten minutes. In this paper, we would like to introduce the signal processing for ECG analysis and the device made for wireless communication of ECG data. In the signal processing, the wavelet transform decomposes the ECG signal into high and low frequency components using wavelet function. Recomposing the high frequency bands including QRS complex, we can detect QRS complex and eliminate the noise from the original ECG signal. To recognize the ECG signal pattern, we adopted the polynomial approximation partially and statistical method. The ECG signal is divided into small parts based on QRS complex, and then, each part is approximated to the polynomials. Comparing the approximated ECG pattern with the database, we can detect and classify the heart disease. The ECG detection device consists of amplifier, filters, A/D converter and RF module. After amplification and filtering, the ECG signal is fed through the A/D converter to be digitalized. The digital ECG data is transmitted to the personal computer through the RF transceiver module and serial port.

• Journal of Biomedical Engineering Research
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• v.3 no.1
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• pp.23-30
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• 1982

The regimen of physical activity of the patient with coronary artery disease requires that he should not overshoot the prescribed heart rate based on his age, health and fuctional status of the heart during his exercise. The step input of work load, however, involves a great danger of overshooting. The purpose of this study was to desigil a system that makes it passible for a subject to check the overshooting. This system shows on tile H.R-meter, the amplified and filtered heart-rate signal of the subject received by the photosensor on his earlobe, puts it in the lead coinpensational circuit where it is conpared with the reference input signal(=the presfribed heart rate). The output of the lead compensational circuit works the aull meter. By means of this null meter, the subject knows whether he is overshooting the prescribed heart rate or not. He can continue the natl meter needle at the'Zero'position through the control of the speed of pedaling of the bicycle ergometer, An experimental test, made on eight men and four women in healthy condition, showed that 91. 7% of them vlaintained the stable heart rate and that the overshooting of the desired heart rate did not exceed $\pm$2BPM. According to the result of this experiment, since the heart rate feedback controller makes it possible for the subject to take the prescribed exercise based not on the work load but on the heart rate which incidentally is inexpensive, it can be made use of as the instrument for the regimen of pflysical activity by the patient with coronary artery disease.

• The Journal of the Acoustical Society of Korea
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• v.25 no.3
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• pp.144-150
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• 2006

Clinicians usually use stethoscopic auscultation for the diagnosis of heart diseases. However, the heart sound signal has varying characteristics due to the noise and/or the conditions of the patients. Also, it is not easy for junior clinicians to find the acoustical differences between different kinds or heart sound signals. which may result in errors in the diagnosis. Thus it will be quite useful for the clinicians to make use of an automatic classification system using signal processing techniques. In this paper, we propose to use hidden Markov models in stead of artificial neural networks which have been conventionally used for the automatic classification of heart sounds. In the experiments classifying heart sound signals. we could see that the proposed methods were quite successful in the classification accuracy.

• Journal of electromagnetic engineering and science
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• v.5 no.3
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• pp.132-139
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• 2005

Wireless bio-signal sensing system, which is based on the principle of Doppler radar, can measure a respiration and heart rates with a periodic movement of skin and muscle near the heart. Though the sensing monostatic system using a circulator has been studied, this bistatic system can be improved by using a circular polarized antenna which has a high isolation between transmitter and receiver. In this paper, we measured the bio-signal without the direct contact with the person. The design of each system and experimental results are discussed.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.55.4-55
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• 2001

Analyzing the ECG signal, we can find heart disease. Myocardial ischemia is a disorder of cardiac function caused by insufficient blood flow to the muscle tissue of the heart. Myocardial ischemia is inscribed on ST-segment of the ECG during and after patient takes exercise or is under stress, but after long time past, the ECG pattern is return to steady state. Therefore, it is necessary to monitor and analyze the ECG signal continuously for patient or aged people. Our primary purpose is the detection of temporary change of the ST-segment of ECG automatically. In the signal processing, the wavelet transform decomposes the ECG signal into high and low frequency components using wavelet function. Recomposing the high frequency bands including QRS complex, we can detect QRS complex more easily ...

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.3
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• pp.138-141
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• 2006

Blood flow is one of vital signals related to human physiological information. Photoplethysmograph (PPG) has been used to measure indirectly heart rate, blood oxygen saturation ($SpO_2$), and so on. Because PPG signal is weak and sensitive to motion artifacts, it is very important to continuously obtain stable PPG signal during free movement. In this study, we applied the scaled Fourier linear combiner (SFLC) using both the adaptive filter and FLC to remove effectively the motion artifacts as well as background noise in the real time without additional signal correlated with motion from a accelerometer. The proposed method would be useful to reduce the movement and background noise which are not synchronized with heart rate.

• 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.