• 대한전기학회논문지:시스템및제어부문D
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• 제54권3호
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• pp.198-205
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• 2005

In this paper, we proposed a new algorithm for the separation of fetal ECG from single channel abdominal ECG. The algorithm consists of a stage of demixing vector calculation for initial signal and a stage of fetal beat detection for the rest of signal. The demixing vector was obtained by applying independent component analysis technique to projected signals into time-frequency domain. For the test of this algorithm, simulation signals, De Lathauwer's data and some measured data, which was acquired from 8 healthy volunteers whose pregnant periods ranged from 22 weeks to 35 weeks and whose ages from 27 to 37, were used. For each data, the accuracy of fetal beat detection was $100\%$ and with the location of fetal beats, fetal heart rate variability and morphology could be offered. In conclusion, this proposed algorithm showed the possibility of fetal beat separation with a single channel abdominal ECG and it might be adopted to a fetal health monitoring system, by which a single channel abdominal ECG is acquired.

• 한국정보통신학회논문지
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• 제4권1호
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• pp.27-33
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• 2000

현재 사회는 고령화와 생활의 질적 향상으로 인해 재택 의료 기술이 필요하게 되었다. 재택 의료가 가능하게 되려면 재택 의료기의 가격이 저렴해야 하며, LAM이나 공중망에 의료기가 직접 접속을 하여 어디서든지 의사가 있는 병원으로 접속이 가능해야 한다. 본 논문에서는 심전도 전처리 과정중 기저선 제거만을 하고 디스플레이 영역을 생략하며, 전력선 잡음 제거를 위해 연산량이 적은 디지털 필터를 적용함으로써 CPU의 부담을 줄일 뿐 아니라 크기를 줄이고 가격을 낮출 수 있고, 남는 CPU의 능력을 LAN(Local Area Network)을 이용한 심전도 데이터 전송에 사용하여 직접 TCP/IP망에 접속할 수 있는 심전도 단말기를 구현하였다.

• 한국정보통신학회논문지
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• 제3권3호
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• pp.553-558
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• 1999

환자의 상태 및 심장 질환 등의 진단에 있어 매우 중요한 정보신호는 심전도 신호이며, 많은 잡음이 혼입되어 있기 때문에 잡음 신호의 필터링이 매우 어렵고 잘못된 신호처리는 심전도 신호의 왜곡을 가져올 수 있다. 심전도 신호의 잡음을 필터링하기 위해 기존의 방법은 다 단계 형태로 필터를 구성하여 처리하기 때문에 신호처리 구조가 복잡하고 연산 량이 많아 처리속도가 느려진다. 이러한 문제를 개선하기 위해 인공지능의 한 기법인 RBF 신경회로망을 이용하여 간단한 구조로 심전도 신호의 필터링 방법을 제안하고, 실험한 결과 우수한 성능을 얻었다.

• 대한의용생체공학회:의공학회지
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• 제12권4호
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• pp.267-276
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• 1991

This paper describes syntactic pattern recognition algorithm for pattern recognition and diagnostic parameter extraction of ECG signal. ECG signal which is represented linguistic string is evaluated by pattern grammar and its interpreter-LALR(1) parser for pattern recognition. The proposed pattern grammar performs syntactic analysis and semantic evaluation simultaneously. The performance of proposed algorithm has been evaluated using CSE database.

• 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.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1997년도 추계학술대회
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• pp.435-438
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• 1997

One of the main techniques or diagnosing heart disease is by examining the electrocardiogram(ECG). Many studies on detecting the QRS complex, P, and T waves have been performed because meaningful information is contained in these parameters. However, the earlier detecting techniques can not effectively extract those parameters from the ECG that is severely contaminated by noise source such 60Hz powerline interference, motion artifact and baseline drift. in this paper, we performed the extracting parameters from and recovering the ECG signal using wavelet transform that has recently been applying to various fields.

• 전자공학회논문지B
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• 제30B권6호
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• pp.67-75
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• 1993

ECG pattern was classified using a back-propagation neural network. An improved feature extractor of ECG is proposed for better classification capability. It is consisted of preprocessing ECG signal by an FIR filter faster than conventional one by a factor of 5. QRS complex recognition by moving-window integration, and peak extraction by quadratic approximation. Since the FIR filter had a periodic frequency spectrum, only one-fifth of usual processing time was required. Also, segmentation of ECG signal followed by quadratic approximation of each segment enabled accurate detection of both P and T waves. When improtant features were extracted and fed into back-propagation neural network for pattern classification, the required number of nodes in hidden and input layers was reduced compared to using raw data as an input, also reducing the necessary time for study. Accurate pattern classification was possible by an appropriate feature selection.

• 대한의용생체공학회:의공학회지
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• 제14권2호
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• pp.137-145
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• 1993

Time domain analysis as well as frequency domain analysis of signal conditioning filters is very useful for practical applications. Time domain analysis of digital filters for noise cancelling in ECG signals is presented. Several band pass and band reject filters are designed for the analysis. Computer simulations are performed to compare the distortions of the Butterworth type filters and linear phase optimal FIR filters which are widely used for ECG signal processing. Band reject filters are applied to power line interference cancelling in ECG signals.

• 융합신호처리학회논문지
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• 제22권2호
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• pp.45-50
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• 2021

최근 IT기술이 발달함에 따라 다양한 생체신호 측정 기기에 대한 연구 및 관심이 높아지고 있으나, 가장 대표적인 생체 신호 중 하나인 심전도, 특히 부정맥 신호 검출과 관련한 연구는 미비한 현실이다. 부정맥은 그 발병원인이 다양하며 발병이후 예후가 좋지 않으므로 조기진단을 통한 예방치료가 최선이다. 하지만 부정맥을 진단하기 위한 도구인 24시간 홀터 심전계는 사용지속시간의 제약, 일상생활로 인한 동잡음 분석의 어려움, 위험상황에서 사용자의 실시간 알람 기능에 단점을 보인다. 본 연구에서는 장시간 연속 측정이 가능한 심전도 및 맥박 모니터링 기기와 실시간 모니터링 앱, 분석용 소프트웨어를 개발하였으며, 측정한 값의 경향성을 확인하였다. 향후 연구에서는 심전도 신호 측정 분석의 정량적 결과 도출에 관한 연구가 필요하며, 이를 바탕으로 하는 부정맥 신호 검출 알고리즘 개발과 관련한 추가 연구를 진행해야 한다.

• 센서학회지
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• 제21권4호
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• pp.241-248
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• 2012

Recently healthcare industry such as pharmaceutical, medical device and healthcare service technology is growing significantly. Mobile healthcare has attracted big attention due to IT convergence technology. Paradigm of healthcare has been changed from the 1st generation(communicable disease prevention) and the 2nd generation(treatment of disease due to extended life expectancy) to the 3rd generation(extended life expectancy due to prevention and control). In our study, we suggest the 3rd generation mobile healthcare system using Bluetooth based wearable ECG monitoring system and smart phone technology. The mobile healthcare system consists of wearable shirts with Bluetooth communication module, ECG sensor, battery, and mobile phone. The ECG data is obtained by a miniaturized sensor and the data is transferred to a mobile phone using Bluetooth communication. Then, user can monitor his/her own ECG signal on an application using Android in mobile phone. The Bluetooth communication device is used due to highly reliable data transmission property and the Bluetooth chip is embedded in every mobile phone. The wearable shirts with chest belt of Bluetooth ECG module is designed with a focus on convenience in the daily life of a wearer. The ECG signal evaluation software in Android based mobile phone is developed for the health check and the ECG signal variation is tested according to the activities of the wearer such as walking, climbing stairs, stand up and sit down, and so on.