• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.1403-1404
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• 2015

현대인의 질병 중 심혈관계 질환의 증가로 인한 건강관리의 중요성이 더해감에 따라 소형 심전계의 필요성이 대두되어지며 운동과 같은 동잡음에 취약한 환경에서도 안정적인 신호를 얻기 위한 연구가 진행되어지고 있다. 본 논문에서는 측정 리드의 거리 최소화에 따른 연구로서 여러 개의 소형 심전도 모듈을 부착하였을 때의 각각의 신호가 임상심전도와 얼마나 유사하게 측정되어질 수 있는지에 대해 연구하였으며 심전도(ECG) 신호의 측정 원리를 위하여 심장 전기쌍극자 모델에 기반하여 전극간 거리를 최소화한 패치형 전극 측정 시스템을 개발하고, 2개 이상의 다중 패치전극 측정 시스템으로부터 측정된 심장전기활동 신호를 합성하여 임상적 심전도와 유사성이 높은 전극신호 유도법을 개발하였다. 또한 이 유도법의 검증을 위하여 임상 심전도 측정장치의 결과와 상관성을 분석하였으며 최대 r 값은 0.859로 얻어졌다.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.5
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• pp.653-659
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• 2011

In general, electrocardiogram(ECG) signals are sampled with a frequency over 200Hz and stored for a long time. It is required to compress data efficiently for storing and transmitting them. In this paper, a method for compression of ECG data is proposed, using by Non Uniform B-spline approximation, which has been widely used to approximation theory of applied mathematics and geometric modeling. ECG signals are compressed and reconstructed using B-spline basis function which curve has local controllability and control a shape and curve in part. The proposed method selected additional knot with each step for minimizing reconstruction error and reduced time complexity. It is established that the proposed method using B-spline approximation has good compression ratio and reconstruct besides preserving all feature point of ECG signals, through the experimental results from MIT-BIH Arrhythmia database.

• 건강소식
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• v.35 no.3
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• pp.16-17
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• 2011

심전도 검사란 심장에서 생기는 전기신호로 심장 이상을 검사하는 것이다. 심장의 박동에 의해 발생한 심장의 활동 상태를 그래프 상으로 기록하는 것으로 심전도 검사를 통해 알 수 있는 질환은 부정맥, 협심증, 심근경색, 고헐압, 심근증 등이 있다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.249-252
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• 2008

A wearable ubiquitous health care monitoring system using integrated ECG and accelerometersensors based on WSN is designed and developed. Wireless sensor network technology is applied for non intrusive healthcare in some wide area coverage with small battery support for RF transmission. We developed wearable devices which are wearable USN node, sensor board and base-station. Low power operating ECG and accelerometer sensor board was integrated to wearable USN node for user's health monitoring. The wearable ubiquitous healthcare monitoring system allows physiological data to be transmitted in wireless sensor network from on body wearable sensor devices to a base-station connected to server PC using IEEE 802.15.4. Physiological data displays and stores on server PC continuously.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.3
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• pp.553-558
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• 1999

The ECG signal is very important information for diagnosis of patient and a cardiac disorder That signal is hard to filter the noise because that is mixed with a lot of noise, and the error of the filtering will distort the ECG signal. The existing method for the filtering of the ECG signal has structure that has many steps for filtering, so that structure is complex and the processing speed is slow. For the improvement of that problem, we propose the method of filtering that has simple structure using the RBF neural networks and have good results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.9
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• pp.728-735
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• 2013

In this paper, we present a method of transmitting ECG signals in real-time mobile environment to be possible to implement the ubiquitous healthcare system. Because of the excessive amount of data transmission of ECG signals, it is necessary to propose a limitation to the real-time transmission. We propose a real-time electrocardiographic monitoring system based on the proposal of unusual waveform detection algorithm which detects the R-wave distortions from the arrhythmia ECG signals having unusual waveform of about 10% on average. It is very effective in terms of time and cost for medical staffs to monitor and analyze ECG signals for a long period of time. Monitoring unusual waveform by gradually adjusting the threshold values of potential and kurtosis makes the amount of data transmitted decrease and significance level of waveform to be enhanced. The unusual waveform detection algorithm is implemented with ubiquitous environment inter-working device client. It is applicable to ubiquitous healthcare system capable of real-time monitoring the ECG signal. While ensuring the mobility, it allows for real-time continuous monitoring of ECG signals.

• Smart Media Journal
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• v.8 no.3
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• pp.62-69
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• 2019

Electrocardiogram (ECG) signals cannot be counterfeited and can easily acquire signals from both wrists. In this paper, we propose a method of generating a coupling image using direction information of ECG signals as well as its usage in a personal recognition method. The proposed coupling image is generated by using forward ECG signal and rotated inverse ECG signal based on R-peak, and the generated coupling image shows a unique pattern and brightness. In addition, R-peak data is increased through the ECG signal calculation of the same beat, and it is thus possible to improve the recognition performance of the individual. The generated coupling image extracts characteristics of pattern and brightness by using the proposed convolutional neural network and reduces data size by using multiple pooling layers to improve network speed. The experiment uses public ECG data of 47 people and conducts comparative experiments using five networks with top 5 performance data among the public and the proposed networks. Experimental results show that the recognition performance of the proposed network is the highest with 99.28%, confirming potential of the personal recognition.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.4
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• pp.21-29
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• 2010

In this study, we aimed to develope the physio-module for echocardiography. This physio-module includes multi-functions such as ECG, respiration, PCG, heart sound, and this is used to diagnose a cardiac disease in using ultrasound images synchronized with biosignals of physio-module. In this paper, the developed physio-module was verified by applying various test patterns considering each biosignal's characteristics and we could get the performance of QRS trigger delay time within international standard, EC-13 criteria. And ECG's change in physio-module and blood flow in M-mode was synchronized.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.624-630
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• 2010

As electrocardiogram(ECG) signals are generally sampled with a frequency of over 200Hz, a method to compress diagnostic information without losing data is required to store and transmit them efficiently. In this paper, an ECG signal compression method, which uses feature points based on curvature, is proposed. The feature points of P, Q, R, S, T waves, which are critical components of the ECG signal, have large curvature values compared to other vertexes. Thus, these vertexes are extracted with the proposed method, which uses local extremum of curvatures. Furthermore, in order to minimize reconstruction errors of the ECG signal, extra vertexes are added according to the iterative vertex selection method. Through the experimental results on the ECG signals from MIT-BIH Arrhythmia database, it is concluded that the vertexes selected by the proposed method preserve all feature points of the ECG signals. In addition, they are more efficient than the AZTEC(Amplitude Zone Time Epoch Coding) method.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.2
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• pp.62-69
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• 2022

An electrocardiogram (ECG) is one of the most important biosignals, and in particular, continuous ECG monitoring is very important in patients with arrhythmia. There are many different types of arrhythmia (sinus node, sinus tachycardia, atrial premature beat (APB), and ventricular fibrillation) depending on the cause, and continuous ECG monitoring during daily life is very important for early diagnosis of arrhythmias and setting treatment directions. The ECG signal of arrhythmia patients is very unstable, and it is difficult to detect the R-peak point, which is a key feature for automatic arrhythmias detection. In this study, we develped a continuous measuring Holter ECG monitoring device and software for analysis and confirmed the utility of R-peak of the ECG signal with MIT-BIH arrhythmia database. In future studies, it needs the validation of algorithms and clinical data for morphological classification and prediction of arrhythmias due to various etiologies.