• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.126-134
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• 2017

There have been numerous studies on extracting the R-peak from electrocardiogram (ECG) signals. However, most of the detection methods are complicated to implement in a real-time portable electrocardiograph device and have the disadvantage of requiring a large amount of calculations. R-peak detection requires pre-processing and post-processing related to baseline drift and the removal of noise from the commercial power supply for ECG data. An adaptive filter technique is widely used for R-peak detection, but the R-peak value cannot be detected when the input is lower than a threshold value. Moreover, there is a problem in detecting the P-peak and T-peak values due to the derivation of an erroneous threshold value as a result of noise. We propose a robust R-peak detection algorithm with low complexity and simple computation to solve these problems. The proposed scheme removes the baseline drift in ECG signals using an adaptive filter to solve the problems involved in threshold extraction. We also propose a technique to extract the appropriate threshold value automatically using the minimum and maximum values of the filtered ECG signal. To detect the R-peak from the ECG signal, we propose a threshold neighborhood search technique. Through experiments, we confirmed the improvement of the R-peak detection accuracy of the proposed method and achieved a detection speed that is suitable for a mobile system by reducing the amount of calculation. The experimental results show that the heart rate detection accuracy and sensitivity were very high (about 100%).

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.787-788
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• 2006

본 논문에서는 적응적 재구성 필터를 이용한 심전도 신호의 잡음제거 알고리즘을 개발하고 이를 임베디드 보드 상에서 구현하였다. 구현된 시스템의 검증을 위해, 제안된 알고리즘은 PC 상에서 소프트웨어만으로 구현했을 때와 적응적 재구성 필터를 소프트웨어와 FPGA 로 구현했을 때의 실행시간 및 잡음제거 성능을 비교하였다. 실험결과 FPGA 상에서 구현된 시스템은 PC 상에서 구현된 프로그램과 비교하여 동일 잡음제거 성능을 가질 때 약 5배정도의 실행시간 향상을 보였다.

• Science of Emotion and Sensibility
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• v.13 no.3
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• pp.467-474
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• 2010

Recently, Study of functional clothing for Vital sensing is focused on reducing artifact by human motions, in order to enhance the electrocardiogram(ECG) sensing accuracy. In this study, considering the factors for each element found from the analysis, a 3-lead electrode inside textile embroidered with silver yarn was developed, and draft designs off our types of vital-signal sensing garments, which are 'chest-belt typed' garment, 'cross-typed' garment 'x-typed' garment and 'curved x-typed' garment, were prepared. The draft designs were implemented on a sleeveless male shirt made of an elastic material so that the garment and the electrodes can remain closely attached along the contour of the human body, and the acquired data was sent to the main computer over a wireless network. In order to evaluate the effects caused by body movements and the ECG-sensing capability for each type in static and dynamic states, displacements were measured from one and two dimensional perspectives. ECG measurement evaluation was also performed for Signal-to-noise ratio(SNR) analysis. Applying the experimental results, the draft garment designs were modified and complemented to produce two types of modular approaches 'continuous-attached' and 'insertion-detached' for the ECG-sensing smart clothing.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.30 no.6
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• pp.366-371
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• 2017

In this paper, we introduce an electrocardiogram (ECG) system designed to solve problems caused by wetgels and motion artifacts in measuring active movement. The system is called a dry-contact ECG and was designed by considering impedance matching between skin and electrode as well as the frictional electricity between electrode and clothes. In order to create the system, we measured impedance on the skin-electrode interface, and the result was applied to the electronic circuit scheme. Moreover, we added an electrode on the back of the measurement electrode to make a flow path to ground the electrical noise. The final ECG circuit and novel electrode were used to detect real human cardiac signals from a subject who was tested while standing still and walking. The signals obtained from the two activities were nicely shaped, without any motion artifact noise. We took electrode size into account in this study because the impedance depended on the area of the electrode. An electrode of 50 mm diameter showed the best curve for the ECG signal without any electrical noise.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.12
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• pp.2671-2676
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• 2009

Empirical mode decomposition (EMD) is new time-frequency analysis method to decompose the signal adaptively and efficiently. The key idea of EMD is to decompose the signal into a set of functions defined by the signal itself, named Intrinsic Mode Functions (IMFs), which preserve the inherent properties of the original signal. Since the decomposition is based on the local time scale of the signal, it is not only applicable to nonlinear and non-stationary processes but also useful in biomedical signals like electrocardiogram (ECG). Traditional low-pass filter uses fourier transform to analysis signal in frequency domain, but EMD is filtered to maintain signal properties in time domain. This paper performed signal decomposition and filtering for noisy ECGs using EMD method. The proposed method is presented and compared with traditional low-pass filter by two performance indices. Our results show effectiveness for enhancement of the noisy ECG waveforms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.1
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• pp.192-200
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• 2015

Several algorithms have been developed to classify arrhythmia which rely on specific ECG(Electrocardiogram) database. Nevertheless personalized difference of ECG signal exist, performance degradation occurs because of carrying out diagnosis by general classification rule. Most methods require accurate detection of P-QRS-T point, higher computational cost and larger processing time. But it is difficult to detect the P and T wave signal because of person's individual difference. Therefore it is necessary to classify the pattern by analyzing personalized ECG signal and extracting minimal feature. Thus, QRS pattern Analysis of personalized ECG Signal by Q, R, S peak variability is presented in this paper. For this purpose, we detected R wave through the preprocessing method and extract eight feature by amplitude and phase variability. Also, we classified nine pattern in realtime through peak and morphology variability. PVC, PAC, Normal, LBBB, RBBB, Paced beat arrhythmia is evaluated by using 43 record of MIT-BIH arrhythmia database. The achieved scores indicate the average of 93.72% in QRS pattern detection classification.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.12
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• pp.82-87
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• 2016

The photoplethysmogram (PPG) signal is one of the mainly considered bio signals along with the electrocardiogram (ECG) signal. PPG signals can be used to estimate the speed of flow of blood in vein, saturation of peripheral oxygen and etc. The heartbeat rate is a common feature in order to evaluate those checkup lists. To estimate the correct heartbeat rate, dynamic noises must be removed in the PPG signal. Conventionally, the acceleration signal is used to remove dynamic noises. This method, however, increases the computational complexity. In this paper, we proposes a solution that uses only PPG signals to calculate the heartbeat rate, and which can be used as a basement in real-time healthcare solution.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.05a
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• pp.512-515
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• 2001

The heifer electrocardiograph is a widely progressing research which is used in judgement to existence for a heart disease and analyzes electric potential changes of heart movement during continuous living of everyday after attaching to body portable holler recorder for twenty-four hours. In order to obtain electrocardiogram clearly, it must eliminate that 60Hz power line interference, baseline wandering, noise of muscle constriction. In holter electrocardiogram, the most big problem which is recorded signal of ECG(electrocardiogram) is a baseline wandering elimination, which is occurred by rhythm of respiration and muscle constriction of part from attaching to an electrode. Such baseline is roughly irregular wandering and shaking up and down therefore the part of baseline wandering elimination is very important because it is difficult of ECG diagnosis. In this study, it is stabilized baseline wandering in analog part as implementation f real-time signal processing digital filter so it is applicable to analyze patient's heart disease by way of design of baseline wandering elimination system.

• Clinical and Experimental Pediatrics
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• v.46 no.5
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• pp.490-494
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• 2003

Purpose : We'd like to determine the incidence of congenital heart disease and arrhythmia in elementary school children in Busan, and to provide adequate prevention and treatment. Methods : A total of 23,802(male 12,909, female 10,893) 1st grade elementary school children living in Busan were studied. All children were 7-8 years old. We obtained their medical history by questionnaire and checked elecrocardiography(ECG). Subsequent screening tests including a 2nd ECG, chest X-ray, phonocardiogram and CBC for the students who had abnormal findings at the first screening test. The third screening test was done for students who had cardiac murmurs or abnormal ECG findings in the second screening test by echocardiogram, treadmill test and 24-hour Holter monitoring. Results : Among 23,802 children participants, 605(2.54%) had abnormal ECG findings at the first screening test. Q wave abnormality(0.58%) was observed most frequently, and complete right bundle branch block(RBBB)(0.26%), sinus tachycardia(0.24%), right axis deviation(0.22%) and ventricular premature contraction(VPC)(0.21%) followed in order. Four hundred and twenty four children participated in the second ECG screening test. Two hundred and two children(47.6%) had an abnormality such as sinus tachycardia(18.8%), VPC(17.8%), or complete RBBB(17.3%). After completing the third examination including echocardiogram, we couldn't find the students with ventricular tachycardia (VT) or SVT at the third arrhythmia screening test. Conclusion : A high incidence of arrhythmia was found in the 1st grade elementary school children in Busan despite their healthy appearances, although fatal heart diseases were not noted. Early diagnosis, adequate preventative measures and treatment will prevent and decrease the frequency of emergent situations like syncope and sudden death.

• Journal of IKEEE
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• v.13 no.1
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• pp.77-86
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• 2009

A wavelet Electrocardiogram(ECG) detector and its analog-to-digital converter(ADC) for low-power implantable cardiac pacemakers are presented in this paper. The proposed wavelet-based ECG detector consists of a wavelet decomposer with wavelet filter banks, a QRS complex detector of hypothesis testing with wavelet-demodulated ECG signals, and a noise detector with zero-crossing points. To achieve high-detection performance with low-power consumption, the multi-scaled product algorithm and soft-threshold algorithm are efficiently exploited. To further reduce the power dissipation, a low-power ADC, which is based on a Successive Approximation Register(SAR) architecture with an on/off-time controlled comparator and passive sample and hold, is also presented. Our algorithmic and architectural level approaches are implemented and fabricated in standard $0.35{\mu}m$ CMOS technology. The testchip shows a good detection accuracy of 99.32% and very low-power consumption of $19.02{\mu}W$ with 3-V supply voltage.