• 대한전기학회논문지:시스템및제어부문D
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• 제55권11호
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• pp.495-501
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• 2006

Diagnostics of unborn baby is mainly aimed at prediction and detection of occurrence of intrauterine hypoxia. Consequences resulting from fetal hypoxia appear in its heart activity. In this study, we have developed a new non-invasive system for fetal hypoxia diagnosis which provides systolic time interval(STI) parameters on the basis of analysis of electrical and mechanical heart activity together. For this we have worked on 1) the proper lead system for the acquisition of abdominal ECG, 2) the independent component analysis based signal processing and fetal ECG separation, 3) the development of a hardware which consists of an abdominal ECG amplifying module and an ultrasound module and 4) the detection of characteristic points of FECG and Doppler signal and the extraction of diagnostic parameters. The developed system was evaluated by the clinical experiments in which 33 subjects were participated. The acquired STI by the system were distributed within the ranges from the well-established invasive results of other researchers. From this, we can conclude that the developed non-invasive fetal hypoxia diagnosis system is useful.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2009년도 춘계학술대회
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• pp.337-340
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• 2009

Wireless tele-home-care application gives new possibilities for ECG (electrocardiogram) monitoring system with wearable biomedical sensors. Thus, continuously development of high convenient ECG monitoring system for high-risk cardiac patients is essential. This paper describes to monitor a person's ECG using wearable approach. A wearable belt-type ECG electrode with integrated electronics has been developed and has proven long-term robustness and monitoring of all electrical components. The measured ECG signal is transmitted via an ultra low power consumption wireless sensor node. ECG signals carry a lot clinical information for a cardiologist especially the R-peak detection in ECG. R-peak detection generally uses the threshold value which is fixed thus it bring errors due to motion artifacts and signal size changes. Variable threshold method is used to detect the R-peak which is more accurate and efficient. In order to evaluate the performance analysis, R-peak detection using MIT-BIH databases and Long Term Real-Time ECG is performed in this research. This concept able to allow patient to follow up critical patients from their home and early detecting rarely occurrences of cardiac arrhythmia.

• 대한의용생체공학회:의공학회지
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• 제14권4호
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• pp.379-386
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• 1993

This paper describes design of a Chaos analyser and its applications to analysis of nonlinear characteristirs of ECG. The proposed system can easily distinguish chaotic system among the various dynamical systems by chaotic quantitative and qualitative analysis and also chaotic characteristics which represents states of nonlinear dynamical system. And we have also proposed new possibilities to recognize abnormal state of ECG signal using the chaotic characteristics.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1993년도 추계학술대회
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• pp.137-140
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• 1993

This paper describes a Chaos analyzer and its applications to characteristic analysis of ECG signals and the other signals. We can detect chaotic system among the various system by quantitative and qualitative analysis using the proposed system. And we also propose a new Possibility to recognize abnormal state of ECG signal using the chaotic characteristcs of signal.

• 한국전자통신학회논문지
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• 제11권11호
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• pp.1141-1148
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• 2016

본 논문은 웨어러블 시스템을 이용하여, ECG 전기 패턴을 QRS을 이용하여 급성 심장마비 예측 감지 시스템으로, 웨어러블 심장 이상 징후 감지 스마트 워치와, 이를 포함 하고 디지털 ECG (X, Y) 패턴 좌표 DB를 이용하여 비정상 패턴을 즉시 감지하고, 급성 심장마비 예방 시스템 및 그 방법을 보여준다. 특히, 디지털 ECG(X, Y) 패턴 정보를 이용한 이상 징후 유형과 대비하는 단계를 통해서 급성 심장마비 발생 시, 골든타임을 놓치지 않고 응급 처치할 수 있음을 보여 준다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2001년도 하계종합학술대회 논문집(5)
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• pp.89-92
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• 2001

For the diagnosis of arrhythmia in the heart system, the QRS complex of ECG signals is used in many cases. The rejection of the noise in ECG signals is important to acquisition of exact QRS complex. This paper presents some experimental results about instantaneous bandwidth estimation and noise rejection of ECG signals with the purpose of rejection of the 60 Hz power noise and the motion artifacts such as EMG signals and contact noise. ECG signals corrupted by noise are cleaned by using the variable bandwidth filter. For the filtering of ECG signals with noise, the instantaneous bandwidth of the signals is estimated by analysis of time-frequency representation of ECG signal.

• 대한의용생체공학회:의공학회지
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• 제18권1호
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• pp.45-50
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• 1997

In this paper, we designed a Molter analysis system using the visual programming method It differs from the existing analysis system in that the various signal processing algorithms represented by icons were designed by GUI concept which provide unskilled user with easy and convenient analysis environment. In order to analyze ECG signal. we only select the icon representing an algorithm to be applied by mouse and arrange the selected icons upon the order to be jlrocessed on screen. As a result it provides a convenient usage and flexibility of analysis. Also, we can find the optimal algorithm for the ambulatory ECG analysis by comparing the several results obtained from the various analysis configuration.

• 제어로봇시스템학회논문지
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• 제8권8호
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• pp.691-697
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• 2002

Myocardial ischemia is a disorder of cardiac function caused by insuficient blood flow to the muscle tissue of the heart. We can diagnose myocardial ischemia by observing the change of ST-segment, but this change is temporary. Our primary purpose is to detect the temporary change of the 57-segment automatically In the signal processing, the wavelet transform decomposes the ECG(electrocardiogram) 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. Amplitude comparison method is adopted to detect QRS complex. Reducing the effect of noise to the minimum, we grouped ECG by 5 data and compared the amplitude of maximum value. To recognize the ECG .signal pattern, we adopted the polynomial approximation partially and statistical method. The polynomial approximation makes possible to compare some ECG signal with different frequency and sampling period. The ECG signal is divided into small parts based on QRS complex, and then, each part is approximated to the polynomials. After removing the distorted ECG by calculating the difference between the orignal ECG and the approximated ECG for polynomial, we compared the approximated ECG pattern with the database, and we detected and classified abnormality of ECG.

• 한국통신학회논문지
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• 제35권9B호
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• pp.1322-1329
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• 2010

As body sensor network (BSN) research becomes mature, the need for managing power consumption of sensor nodes has become evident since most of the applications are designed for continuous monitoring. Real time Electrocardiograph (ECG) analysis on sensor nodes is proposed as an optimal choice for saving power consumption by reducing data transmission overhead. Smart sensor nodes with the ability to categorize lately detected ECG cycles communicate with base station only when ECG cycles are classified as abnormal. In this paper, ECG classification algorithms are described, which categorize detected ECG cycles as normal or abnormal, or even more specific cardiac diseases. Our Euclidean distance (ED) based classification method is validated to be most power efficient and very accurate in determining normal or abnormal ECG cycles. A close comparison of power efficiency and classification accuracy between our ED classification algorithm and generalized linear model (GLM) based classification algorithm is provided. Through experiments we show that, CPU cycle power consumption of ED based classification algorithm can be reduced by 31.21% and overall power consumption can be reduced by 13.63% at most when compared with GLM based method. The accuracy of detecting NSR, APC, PVC, SVT, VT, and VF using GLM based method range from 55% to 99% meanwhile, we show that the accuracy of detecting normal and abnormal ECG cycles using our ED based method is higher than 86%.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1986년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 17-18 Oct. 1986
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• pp.633-636
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• 1986

We have developed an automated ECG interpretation technique by micro-computer for rapid analysis of ECG data in the clinical hospital. This system is consisted of 16 bit microcomputer including bandpass-filter, comparator, A/D converter in order to obtain the QRS width, R-R interval.