• 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.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.6
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• pp.57-63
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• 2012

Effective use of stethoscope is very important for primary clinical diagnosis for the increasing cardiovascular and respiratory disease. This study developed the contact vibration sensor using piezopolymer film which minimizes the ambient noise, and signal processing algorithm was applied for providing better auscultation sounds compare to the existing electronic stethoscopes. Especially, low frequency heart sounds were acquired without distortion, and the quality of lung sounds were improved. Also, auscultating sounds could be transmitted using bluetooth, which made possible to be used for the u-healthcare environment. Results of this study, auscultation of heart and lung sounds, could be applied to the convergence industry of medical and information communication technology through remote diagnosis.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.4 s.316
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• pp.74-78
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• 2007

Novel concept of sensor mat and its signal processing method is proposed for patient monitoring in medical application. Proposed sensor mat structure has sensing inner layer which has cross-linked arrangement using plastic optical fiber(POF). Large core diameter of plastic optical fiber behaved as band pass filter by averaging the noise component caused by unwanted environmental factors. Signal processor followed by sensor output added noise immune performance by filtering out unwanted component. Fail-proof patient breath monitoring scheme was realized by using intelligent decision algorithm. Unlike the conventional approach by using mechanical sensor, which have high sensitivity both to signal and to environmental noise, our approach provided reliable breath motion detection.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.3
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• pp.299-306
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• 2016

In this paper, a vital sign sensor based on impedance variation of resonator is proposed to detect the respiration and heartbeat signals within near-field range as a function of the separation distance between resonator and subject. The sensor consists of an oscillator with a built-in planar type patch resonator, a diplexer for only pass the second harmonic frequency, amplifier, SAW filter, and RF detector. The cardiac activity of a subject such as respiration and heartbeat causes the variation of the oscillation frequency corresponding impedance variation of the resonator within near-field range. The combination of the second harmonic oscillation frequency deviation and the superior skirt frequency of the SAW filter enables the proposed sensor to extend twice detection range. The experimental results reveal that the proposed sensor placed 40 mm away from a subject can reliably detect respiration and heartbeat signals.

• Journal of the Korea Society of Computer and Information
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• v.26 no.11
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• pp.21-31
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• 2021

As the COVID-19 pandemic rapidly changes healthcare around the globe, the need for smart healthcare that allows for remote diagnosis is increasing. The current classification of respiratory diseases cost high and requires a face-to-face visit with a skilled medical professional, thus the pandemic significantly hinders monitoring and early diagnosis. Therefore, the ability to accurately classify and diagnose respiratory sound using deep learning-based AI models is essential to modern medicine as a remote alternative to the current stethoscope. In this study, we propose a deep learning-based respiratory sound classification model using data collected from medical experts. The sound data were preprocessed with BandPassFilter, and the relevant respiratory audio features were extracted with Log-Mel Spectrogram and Mel Frequency Cepstral Coefficient (MFCC). Subsequently, a Parallel CNN network model was trained on these two inputs using stacking ensemble techniques combined with various machine learning classifiers to efficiently classify and detect abnormal respiratory sounds with high accuracy. The model proposed in this paper classified abnormal respiratory sounds with an accuracy of 96.9%, which is approximately 6.1% higher than the classification accuracy of baseline model.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.4
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• pp.418-425
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• 2014

This paper presents a Ku-Band Doppler Radar System to measure respiration and heart rate. It was measured by using simultaneous radar and ECG(Electrocardiogram). Arctangent demodulation without dc offset compensation can be applied to transmitted I/Q(In-phase & Quadrature-phase) signal in order to improve the RMSE(Root Mean Square Error) about 50 %. The power leaked to receiving antenna from the transmitting antenna is always generated because of continuously opening the transceiver of CW(Continuous Wave) Doppler radar. As the output power increase, leakage power has an effect on the SNR(Signal-to-Noise Ratio) of the system. Therefore, in this paper, leakage cancellation technique that adds the signal having the opposite phase of the leakage power to the leakage power was implemented in order to minimize the decline of receiver sensitivity. By applying the leakage cancellation techniques described above, it is possible to measure the heart rate and respiration of the human at a distance of up to 35 m. the heart rate of the measured data at a distance of 35 m accords with the heart rate extracted from the ECG data.

• Journal of Advanced Navigation Technology
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• v.13 no.4
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• pp.482-489
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• 2009

This paper proposes a CW(Continuous-Wave) bio-radar applying a new adaptive noise canceller based on ALE(Adaptive Line Enhancer) which can remove the Gaussian noise and system noise. Recently the research works on this CW bio-radar which can be used to detect heartbeat and respiration are advanced by the university and research facility. Although the researches describe CW bio-radar not only is vulnerable for the Gaussian noise but also has a disadvantage of decreasing the heart-rate accuracy due to the noise, the researches do not demonstrate the effective method for removing the noise component in a baseband signal. In this paper, a CW bio-radar applying the new adaptive noise canceller based on ALE which can remove the noise component is proposed. This paper compares and analyzes the performance for increasing the heart-rate accuracy according to removing the Gaussian noise and system noise in the baseband signal through the quadrature receiver which can alleviate the demodulation sensitivity to target position.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.9
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• pp.2105-2112
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• 2010

The noise component of electrocardiogram is not distributed in a certain frequency band. It is expressed in various types of signals by rater's physical and environmental conditions. Particularly, since the baseline wander is occurred by the mixture of the original signal and 0 ~ 2 [Hz] range of the frequency components according to muscle constraction of part attaching to an electrode and respiration rythm, it makes the ECG signal analysis difficult. Several methods have been proposed to eliminate the wandering effectually. However, they have some problems. In some methods, the high processing time is required due to the computational complexity, while in other cases ECG signal morphology can be distorted. This paper suggests a simple and effective algorithm that eliminates baseline wander with low computational complexity and without distorting signal morphology. First, the algorithm detects and segments a baseline wandering interval using slope analysis and curve point detection, second, approximates the wandering in the interval as a sinusoid, and then subtracts the sinusoid from signal. Finally, ecg signals without baseline wander are obtained. In order to evaluate the performance of the algorithm, several ECG signals with baseline wandering in MIT/BIH ECG database 101, 111, 113, 234 record were chosen and applied to the algorithm. It is found that the algorithm removes baseline wanders effectively without significant morphological distortion.

• The Journal of the Acoustical Society of Korea
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• v.30 no.1
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• pp.9-16
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• 2011

When a hydrofoil ship plies at high speed, there exist possibilities of collision with ocean mammals dwelling near the surface. An active sonar located within the immersed hydrofoil structure that provides the lift for the vessel, can be used for early warning of their presence. The proper functioning of the active sonar system depends on its ability to reject noise and pick up the target signal. In this article, we measured the noise on a hydrofoil of an operating ship with two flush-mounted hydrophones. The measurements were conducted for the purpose of (1) identifying the effect of operating state of machinery likes engine, cooler and generator (2) observing the change of noise depending on the measuring position (3) observing the change of noise with increasing ship speed. To verify our experiment, experiments were performed three times and the measured results are compared with other investigations and they show similarity to each other. The results are analyzed with frequency domain in order to apply to operating active sonar detecting system and focus on high frequency band within sonar's operating frequency region. Through these experiments and analysis, it is expected that we can identify the generated noise around hydrofoil where active sonar is installed and these results lead us to design active sonar that could distinguish target signal from noise more effectively.

• Journal of Biomedical Engineering Research
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• v.19 no.3
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• pp.251-260
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• 1998

The Holter monitoring system is a widely used noninvasive diagnostic tool for ambulatory patient who may be at risk from latent life-threatening cardiac abnormalities. In this paper, we design a high performance intelligent holter monitoring system which is characterized by the small-sized and the low-power consumption. The system hardware consists of one-chip microcontroller(68HC11E9), ECG preprocessing circuit, and flash memory card. ECG preprocessing circuit is made of ECG preamplifier with gain of 250, 500 and 1000, the bandpass filter with bandwidth of 0.05-100Hz, the auto-balancing circuit and the saturation-calibrating circuit to eliminate baseline wandering, ECG signal sampled at 240 samples/sec is converted to the digital signal. We use a linear recursive filter and preprocessing algorithm to detect the ECG parameters which are QRS complex, and Q-R-T points, ST-level, HR, QT interval. The long-term acquired ECG signals and diagnostic parameters are compressed by the MFan(Modified Fan) and the delta modulation method. To easily interface with the PC based analyzer program which is operated in DOS and Windows, the compressed data, that are compatible to FFS(flash file system) format, are stored at the flash memory card with SBF(symmetric block format).