• Journal of Digital Convergence
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• v.14 no.9
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• pp.331-339
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• 2016

Chronic diseases are increasing nowadays as daily habits changed due to economic growth. Among chronic diseases, heart cerebrovascular disease is one of the major causes of death in South Korea that accounts for approximately 20% of mortality. Tests to measure anomaly of the heart is ECG tests, which measures and analyzes the electrical heart activity. Any mistakes in lead attachment location critically affects ECG testings, and statistical facts showed that only 2.8% of the nurses properly located leads to patients. As a solution, this paper proposes a system based on a projection-based augmented reality technology to generate X-ray images to the patient's chest to point out exact attachment locations of ECG leads. Evaluation comparison results showed a 2.6 cm difference between the conventional system and the proposed system. ECG test results also showed significant signal differences between the systems in leads V1, V2, and V3. The ECG measured accurately by the proposed system would help greatly in patient management and clinical decisions of clinicians.

• Proceedings of the Korea Contents Association Conference
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• 2014.11a
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• pp.31-32
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• 2014

본 논문은 두 사람의 중첩된 심전도 신호를 평균 심전도 파형을 이용하여 분리하는 방법을 제안한다. 사전에 등록한 두 사람의 평균 심전도 파형을 이용하여 중첩된 심전도 신호에서 각 개인의 R-peak 위치를 구별해내고 이를 바탕으로 각 두 사람의 심전도 신호를 분리한다. 분리된 심전도 신호를 바탕으로 두 사람의 신호를 분석함으로써 각자의 건강상태 확인이나 상호간의 호감도 측정 등의 오락적인 분야에 활용할 수 있다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.11a
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• pp.246-248
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• 2012

심전도는 측정 기기에서 발생하는 전기적 잡음이나 근육에서 발생하는 근전도에 의한 잡음, 전극을 부착한 사람의 움직임에 의한 동잡음 등에 민감한 특성을 보인다. 또한 심장의 이상으로 인하여 왜곡이 심하게 발생하므로 심전도에서 의미 있는 구간을 검출하기 위해서는 이들을 보완하는 알고리즘이 필수적이라 할 수 있다. 논문에서는 심전도 분석의 보조를 위하여 입력된 심전도가 가지는 잡음과 왜곡을 제거하고 구간의 위치를 출력하는 시스템을 제안한다. 이를 위해 관련 알고리즘 중, 가장 널리 알려진 'Pan & tompkins algorithm'을 시스템에 이식하였고 알고리즘의 각 단계를 알아보기 쉽게 출력하는 인터페이스를 구성하였다. 시스템의 기능을 확인하기 위해 MIT/BIH 데이터베이스를 이용하였으며, 잡음과 왜곡이 심하여 육안으로 구간을 확인하기 힘든 심전도에서도 높은 구간검출 정확도를 확인할 수 있었다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.4C
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• pp.313-320
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• 2012

An ECG(Electrocardiogram) compression can increase the processing speed of system as well as reduce amount of signal transmission and data storage of long-term records. Whereas conventional performance evaluations of loss or lossless compression algorithms measure PRD(Percent RMS Difference) and CR(Compression Ratio) in the viewpoint of engineers, this paper focused on the performance evaluations of compression algorithms in the viewpoint of diagnostician who diagnosis ECG. Generally, for not effecting the diagnosis in the ECG compression, the position, length, amplitude and waveform of the restored signal of PQRST wave should not be damaged. AZTEC, a typical ECG compression algorithm, is validated its effectiveness in conventional performance evaluation. In this paper, we propose novel performance evaluation of AZTEC in the viewpoint of diagnostician.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.483-486
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• 2000

심전도에서 QRS complex와 R-wave의 검출은 부정맥 진단, 심전도의 특성점 검출 기준, heart rate variability(HRV) 측정에 있어서 중요하나, 시시각각 변화하는 생리적 변화와 여러 가지 노이즈로 인해 검출이 쉽지 않다 제안된 알고리듬에서는 wavelet filter banks를 이용하여 대칭적 enhanced 신호와 noise 와 같은 very high frequency 성분이 제거된 ECG에 근사화 된 approximated 신호를 얻는다. Enhanced 신호로부터 QRS complex의 위치를 검출하고, 검출된 위치의 주변에서 대칭적 wavelet의 특성이 반영된 dominant한 peak의 위치정보, 즉 R wave의 후보점을 얻는다. 이 위치 정보를 이용하여 enhanced 신호에서 각 peak에서의 크기, approxi-mated 신호에서 각 peak 주변에서의 기울기 변화, 기울기 부호 등을 고려하여 R-wave의 위치를 원래의 ECG 신호에서 얻는다. MIT/BIH database에 적용한 결과 99.6%의 QRS complex검출률과 92.9%의 R-wave 검출률을 보였다.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2001.05a
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• pp.6-9
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• 2001

집중도를 평가하기 위하여 피험자에게 집중을 유발시키는 3가지 task(단기기억작업, Corsi block tapping task, visuomotor task)를 부가하고 주관평가 및 생리신호(뇌파, 심전도, 맥파, 피부온도, 호흡, 피부전도도)를 측정하였다. 뇌파를 mapping하여 평가에 적합한 전극이 위치를 선정하고, task 수행중 집중도 변화와 짐전도의 심박변화와의 관계를 분석하였다. 분석결과 안정과 task 수행시 뇌파 mapping상 전체 power의 변호가 frontal 부분에서 크게 나타났으며, 집중시 R-R 간격의 순간간격변화가 줄어들었다.

• Journal of Satellite, Information and Communications
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• v.9 no.2
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• pp.80-84
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• 2014

As an integrated technology with IT and biomedical sciences, U-health offers various healthcare services without time and space limit. In order to make a proper diagnosis, doctors need two key technologies: biosignal measurement and high reliability communication technologies. In this paper, we introduce an implementation process of a bio signal system with using an electrocardiography(ECG) sensor, video, global positioning system(GPS), communication module and micro controller unit(MCU).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.2
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• pp.414-421
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• 2015

This paper presents a new method to decompose a duplicated ECG signal, which is measured from two people, to two individual ECG signals. In paper, it is shown that the duplicated ECG signal can be decomposed, provided that their SAECG signals are known. As the SAECG signal is the average of a ECG signal, it is a feature to identify individual ECG signals from the duplicated signal. Since the ECG signal is nearly periodic, so-called heart-rate, the period of each ECG signal can be found by using the autocorrelation of the duplicated signal, That is, the autocorrelation has high peaks at the multiple instants of heart-rate of each person. With the heart-rate of each person obtained by some processing, all R-peaks are identified by the SAECG signals. To be concrete, the SAECG signal of each person is repeatedly placed at the R-peak instants with his heart-rate, and the weight of each SAECG signal is computed by LMSE optimization. Finally, as adding the error signal in the LMSE optimization processing to the weighted SAECG signal, each individual ECG signal is obtained. In experimental results, we demonstrate that the duplicated ECG signal is successfully decomposed into two ECG signals.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.3
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• pp.378-382
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• 2006

This paper presents an approach to detect premature ventricular contractions(PVC) using the neural network with weighted fuzzy membership functions(NEWFM). NEWFM classifies normal and PVC beats by the trained weighted fuzzy membership functions using wavelet transformed coefficients extracted from the MIT-BIH PVC database. The two most important coefficients are selected by the non-overlap area distribution measurement method to minimize the classification rules that show PVC classification rate of 99.90%. By Presenting locations of the extracted two coefficients based on the R wave location, it is shown that PVC can be detected using only information of the two portions.

• Journal of the Korean Magnetics Society
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• v.23 no.4
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• pp.135-143
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• 2013

The clip-type pulsimeter equipped with a Hall sensor has a permanent magnet attached in the "Chwan" position to the center of a radial artery. The clip-type pulsimeter is composed of a hardware system measuring voltage signals. These electrical bio-signals display pulse rate, non-invasive blood pressure, respiratory rate, pulse wave velocity (PWV), and spatial pulse wave velocity (SPWV) simultaneously measured by using the radial artery pulsimeter, the electrocardiograph (ECG), and the photoplethysmograph (PPG). The findings of this research may be useful for developing a oriental-western biomedical signal storage device, that is, the new and fusion patient monitor, for a U-health-care system.