• 센서학회지
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• 제21권1호
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• pp.39-45
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• 2012

Recently the convergence of healthcare technology is used for daily life healthcare monitoring. Cardiac arrhythmia is presented by the state of the heart irregularity. Abnormal heart's electrical signal pathway or heart's tissue disorder could be the cause of cardiac arrhythmia. Fatal arrhythmia could put patient's life at risk. Therefore arrhythmia detection is very important. Previous studies on the detection of arrhythmia in various ECG analysis and classification methods had been carried out. In this paper, an ECG signal processing techniques to detect abnormal ECG based on DTW minimum accumulation distance through the template matching for normalized data and variable threshold method for ECG R-peak detection. Signal processing techniques able to determine the occurrence of normal ECG and abnormal ECG. Abnormal ECG detection algorithm using DTW minimum accumulation distance method is performed using MITBIH database for performance evaluation. Experiment result shows the average percentage accuracy of using the propose method for Rpeak detection is 99.63 % and abnormal detection is 99.60 %.

• 반도체디스플레이기술학회지
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• 제11권3호
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• pp.57-61
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• 2012

In order to analyze the ECG, it is important to pinpoint the repeat interval of the ECG. In this paper, we present an efficient algorithm for finding the QRS complex on the ECG. We escaped from the conventional methods to go through multiple steps of preprocessing to make ECG easier to find the QRS complex. We selected the candidate peak that has the possibility of the QRS complex in original ECG, and used technique to find the QRS complex among the candidate peak. In this way, we could get similar efficiency to Pan & Tompkins Algorithm that is most representative QRS complex detection algorithm, just used fewer operations than Pan & Tompkins Algorithm.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2007년도 춘계종합학술대회
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• pp.347-350
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• 2007

본 연구는 무선 센서네트워크를 활용하여 환자 또는 고령자를 위한 ECG, 활동량 모니터링 시스템을 설계 및 구현하였다. 심전도 변화는 사람의 활동, 뛰거나 걷기 등의 움직임에 따라 조금씩 변화한다. 그래서 종종 자세, 행동에 따른 ECG변화의 기록은 중요시되며 이를 위해 매일 활동하는 환자의 활동 모니터링 시스템이 필요하다. ECG와 활동량 데이터는 자동 알림기능을 지원하는 시스템에 저장되고 긴급 상황 발생 시 보다 빠르게 초기 활동을 할 수 있게 한다. 몸에서 계측된 ECG 데이터와 활동량 데이터는 무선 센서네트워크를 통해 베이스테이션과 연결된 서버에 전송되며 서버에서 비정상적 상황을 판별시 발생 의사의 PDA 또는 서버에 데이터를 전송한다.

• 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.

• 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.

• 한국정보통신학회논문지
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• 제13권6호
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• pp.1215-1221
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• 2009

본 연구에서는 무선 센서네트워크 환경에서 요구하는 데이터 전달의 신뢰성 향상을 위해 기능성 노드를 제안한다. 생체신호 모니터링을 위해 기존의 지속적인 생체신호 전송시 발생하는 데이터 손실을 줄이기 위해 비정상적인 QRS-complex 검출이 가능한 센서노드를 이용하고, Ad-hoc 네트워크 환경에서 비정상적인 QRS-comoplex 발생시에만 데이터를 전송함으로써 무선 센서네트워크 내에 발생되는 데이터량을 줄일 수 있었다. 본 연구에서 Ad-hoc 환경에서의 기능성 노드를 사용함으로써 그 결과 의료 목적을 위한 무선 센서네트워크에서 전체 패킷발생을 줄여 센서노드의 전력소모를 크게 줄이고 시스템의 신뢰도를 크게 높이는 것으로 확인되었다.

• 대한의용생체공학회:의공학회지
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• 제31권4호
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• pp.316-320
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• 2010

HRV(Heart rate variability) analysis parameter is widely used as an index to evaluate the autonomic nervous system and cardiac function. For reliable HRV analysis, we need to acquire the accurate ECG signals. Most of commercially available portable ECG devices have low sampling rate because of low power consumption and small size issues, which make it difficult to measure RR-interval accurately. This study is to improve the accuracy of RR-interval by developing R-wave interpolation technique, based on the morphological characteristics of the QRS complex. When the developed method was applied to ECG obtained at 200 Hz and the results were compared with 1000 Hz reference device, the error range decreased by 1.33 times in sitting and by 2.38 times in cycling exercise. Therefore, the proposed interpolation technique is thought to be useful to improve the accuracy of R-R interval in the portable ECG device with low sampling rate.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1991년도 춘계학술대회
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• pp.51-55
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• 1991

This paper describes an algorithm of pattern analysis of ECG signals by significant points extraction method. The significant points can be extracted by modified zerocrossing method, which method determines the real significant point among the significant point candidates by zerocrossing method and slope rate of left side and right side. This modified zerocrossing method improves the accuracy of detection of real significant point position. This paper also describes the pattern matching algorithm by a hierarchical AND/OR graph of ECG signals. The decomposition of ECG signals by a hierarchical AND/OR graph can make the pattern matching process easy and fast. Furthermore the pattern matching to the significant points reduces the processing time of ECG analysis.

• 한국전자통신학회논문지
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• 제15권1호
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• pp.191-198
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• 2020

본 연구는 ECG 신호를 이용하여 AR/VR 장치 사용 중에 발생할 수 있는 스트레스와 심장 상태에 따른 위험 예측을 위한 실시간 분석 시스템을 개발하였다. 제안 방법에는 ECG 신호의 R-R 간격을 이용한 HRV, BPM 측정법과 선행연구를 이용하여, 2차원 공간의 대치방법을 통해 실시간 진단방법을 제안하였다. 5분단 위로 ECG 데이터를 분석하고 자율신경계 진단 결과로 도출했다.

• 대한의용생체공학회:의공학회지
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• 제28권4호
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• pp.441-448
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• 2007

Heart rate variability (HRV) in electrocardiogram (ECG) is an important index for understanding the health status of heart and the autonomic nervous system. Most HRV analysis approaches are based on the proper heart rate (HR) data. Estimation of heart rate is thus a key process in the HRV study. In this paper, we report an innovative method to estimate the heart rate. This method is mainly based on the concept of periodicity transform (PT) and instantaneous period (IP) estimate. The method presented is accordingly called the "PT-IP method." It does not require ECG R-wave detection and thus possesses robust noise-immune capability. While the noise contamination, ECG time-varying morphology, and subjects' physiological variations make the R-wave detection a difficult task, this method can help us effectively estimate HR for medical research and clinical diagnosis. The results of estimating HR from empirical ECG data verify the efficacy and reliability of the proposed method.