• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.6
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• pp.18-26
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• 2009

In this paper, we proposed multipurpose signal detection methods for ECG (electrocardiogram) based u-healthcare systems. For ECG based u-healthcare system, QRS signal extraction for cardiovascular disease diagnosis is essential. Also, for security and convenience reasons, it is desirable if u-healthcare system support biometric identification directly from user's bio-signal such as ECG for this case. For this, from Lead II signal, we developed QRS signal detection method and also, we developed signal extraction method for biometric identification using Lead II signal which is relatively robust from signal alteration by aging and diseases. For QRS signal detection capability from Lead II signal, ECG signals from MIT-BIH database are used and it showed 99.36% of accuracy and 99.68% of sensitivity. Also, to show the performance of signal extraction capability for biometric diagnosis purpose, Lead III signals are measured after drinking, smoking, or exercise to consider various monitoring conditions and it showed 99.92% of accuracy and 99.97% of sensitivity.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.6
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• pp.43-50
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• 2011

Currently, conventional security methods including IC card or password type method are quickly switched into biometric security systems in various applications and the electrocardiogram (ECG) has been considered as one of novel biometrics way. However, conventional ECG based biometrics used lead II signal which conventionally used for formulaic signal to heart disease diagnosis and it is not suitable for biometrics since it is rather difficult to find consistent features for heart disease patents. To overcome this problem, we developed new biometrics system using ECG lead III signals. For wave extraction, signal peak points are extracted through AAV algorithm. For feature selection, extracted waves are categorized into one of four wave types and total twenty two features including number of vertices, wave shapes, amplitude information and interval information are extracted based on their wave types. Experimental results for thirty-six people showed 100% specificity, 95.59% sensitivity and 99.17% of overall identification accuracy.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.861-862
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• 2006

본 논문에서는 차동증폭기와 대역통과 필터를 이용한 심전도측정 시스템의 구현하고 동작을 확인하였다. 구현된 하드웨어의 성능평가를 위해 동일한 입력 신호에 대한 시뮬레이션 결과와 실제 출력을 비교 하였다. 또한, 실제 동작을 확인하기 위하여 심전도 신호 중 리드 II(lead II)파형을 추출하였다. 설계된 회로는 소형화 및 경량화가 가능하기 때문에, 유비쿼터스 환경에 서 이동 중 심전도신호의 측정에 적용가능하며 능동형 게임의 감성추출에도 적용 가능할 것으로 본다.