• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.367-368
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• 2008

한의학의 주요 방법 중 하나인 맥진은 한의사가 환자의 손목 부위를 손가락으로 진맥하여 환자의 맥동을 감지하는 행위이다. 하지만 이러한 맥진은 주관적이고 형이학적 이어서 맥진의 발전을 위해서는 맥진의 객관화와 정량화가 요구된다. 본 연구는 기존의 와이어 본딩(wire bonding)을 이용한 맥진 센서의 단점인 내성을 극복하기 위하여 FDB(Face Down Bonding) 방식을 이용하였으며, $3{\times}3$ 멀티 어레이 센서간의 crosstalk를 극복하고자 센서들을 격리시킬 수 있는 댐(dam)을 형성하였다. 또한, 댐을 감싸고 상단 및 하단에 들기를 형성하는 패드를 이용하여 피부에 접촉하도록 제작하였다. 센서의 특성을 평가하기 위하여 각 센서 출력 단자의 저항 값을 측정하였으며 센서 스펙에서 제공하는 값과 동일함을 확인하였고, 실제 요골동맥 부위에서 맥파를 측정하여 전형적인 요골동맥 맥과 파형이 측정됨을 확인하였다.

• Journal of Satellite, Information and Communications
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• v.9 no.1
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• pp.85-89
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• 2014

Electrocardiogram (ECG) is a diagnostic test which records the electrical activity of the heart, shows abnormal rhythms and detects heart muscle damages. With this ECG signal, medical centers diagnose patients' heart disease symptoms. A normal resting heart rate for adults rages from 60 to 100 beats a minute. An irregular heartbeat is called "arrhythmia", and arrhythmia is also called "cardiac dysrhythmia". In an arrhythmia, the heartbeat maybe too slow(slower than 60beats), too rapid(faster than 100beats), too irregular, etc. Among these symptoms of arrhythmia, if the heart beat is slower than the normal range, the symptom is called "bradycardia", and if it is faster than the range, it is called "tachycardia" In this letters, we proposed the detection algorithm of cardiac arrhythmia in ECG signal using R-R interval through the detection of R-peak.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1968_1969
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• 2009

한의학에서 맥진을 하는 위치인 좌, 우 요골동맥상의 촌(寸), 관(關), 척(尺) 위치는 손목에 있는 요골 경상돌기(styloid preocess) 부근의 볼록한 지점인 고골(高骨)을 기준으로 맥이 느껴지는 위치를 검지, 중지, 약지를 이용해 찾는다. 각각의 위치는 한의학적인 관점에서 각기 다른 장부의 기능과 연결되며 그 차이를 인지하여 맥을 진단하는데 그 결과에 따라 병증을 진단하는 요소로 활용되게 된다. 그러나 생리학적으로 좌, 우 요골동맥의 차이는 크지 않다고 알려져 있으며 차이에 대한 연구도 많지 않다. 본 연구에서는 기존연구에서 밝혀진 좌, 우 요골동맥의 혈류속도의 차이를 근거로 한의사 맥진시 센서 역할을 하는 손가락에서 감지된 좌, 우 맥진위치의 차이가 실제 맥진기에서도 나타나는지를 측정을 통해 확인 해 보고자 한다. 건강한 20대 남자 135명을 대상으로 맥파를 측정하여 맥파 파라메터 중 차이를 보이는 파라메터를 통계분석하였다. 그 결과, 11개의 파라메터가 좌, 우 맥진위치에서 차이를 보이는 것을 확인하였다. 차이를 보이는 변수는 특정 변수로 한정되지 않고 맥압과 관련된 (h1~5) 변수와 피크가 나타나는 시간의 변수, 맥파 파형의 면적 등 다양한 변수에서 차이를 확인할 수 있었다.

• 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.

• Journal of Biomedical Engineering Research
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• v.10 no.3
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• pp.343-350
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• 1989

A new algorithm classifying ECG Arrhythmia signals using Back-propagation network is proposed. The base-line of ECG signal is detected by high pass filter and probability density function then input data are normalized for learning and classifying. In addition, ECG data are scanned to classify Arrhythmia signal which is hard to find R-wave. A two-layer perceptron with one hidden layer along with error back-propagation learning rule is utilized as an artificial neural network. The proposed algorithm shows outstanding performance under circumstances of amplitude variation, baseline wander and noise contamination.

• Proceedings of the Korean Magnestics Society Conference
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• 2011.06a
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• pp.180-182
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• 2011

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.2
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• pp.437-444
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• 2016

Most methods for detecting arrhythmia require pp interval, diversity of P wave morphology, but it is difficult to detect the p wave signal because of various noise types. Therefore it is necessary to use noise-free R wave. In this paper, we propose algorithm for premature contraction arrhythmia classification through ECG pattern analysis and template threshold. For this purpose, we detected R wave through the preprocessing method using morphological filter, subtractive operation method. Also, we developed algorithm to classify premature contraction wave pattern using weighted average, premature ventricular contraction(PVC) and atrial premature contraction(APC) through template threshold for R wave amplitude. The performance of R wave detection, PVC classification is evaluated by using 6 record of MIT-BIH arrhythmia database that included over 30 PVC and APC. The achieved scores indicate the average of 99.77% in R wave detection and the rate of 94.91%, 95.76% in PVC and APC classification.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.4
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• pp.2217-2224
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• 2014

This paper deals with system development which measures 12 channel ECG using medical analog front end(AFE) and discriminates arrythmia through signal analysis. Recently, occurrences of cardiac arrest have been increased. So the need of system that diagnoses an arrythmia which results in cardiac arrest is increasing. There are some drawbacks of conventional 12 channel ECG system that it occupies bulk and consists of complicated circuit. To improve those, we made up the system composed of medical AFE, algorithm for discriminating arrythmia and DSP for signal processing. This system can be monitored 12 channel ECG waveforms and the discriminant analysis result of arrhythmia through 7" LCD and received the input through touch pannel. In this study, we conducted normal operation test about output signal of ECG simulator(normal/abnormal ECG signal) to verify the implemented system and performance evaluation of the optimization process for applying arrhythmia algorithm to an embedded environment.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.6
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• pp.701-709
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• 2019

Recently, heart rate signal, which is one of biological signals, have been used in various fields related to healthcare. Conventionally, most of the proposed heart rate signal detection methods are contact type methods, but there is a problem of discomfort that the subject have to contact with the device. In order to solve the problem, detection study by non-contact method has been progressed recently. The detected heart rate signal can be used for finger vein liveness detection and various application using heart rate. In this paper, we propose a method to obtain heart rate signal by using finger vein imaging system. The proposed method detected the signal from the changes of the brightness value in the time domain of the infrared finger vein images and converted it into the frequency domain using the image processing algorithm. After the conversion, we removed the noise not related to the heart rate signal through band-pass filtering. In order to evaluate the accuracy of the signal, we analyzed the correlation with the signal obtained simultaneously with the finger vein acquisition device and contact type PPG sensor approved by KFDA. As a result, it was possible to confirm that the heart rate signal detected in non-contact method through the finger vein image coincides with the waveform of actual heart rate signal.

• 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.