• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.4
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• pp.727-732
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• 2012

This paper presents an approach to classify normal and arrhythmia from the MIT-BIH Arrhythmia Database using Discrete Cosine Transform(DCT), Discrete Wavelet Transform(DWT) and neural network. In the first step, Discrete Cosine Transform is used to obtain the representative 15 coefficients for input features of neural network. In the second step, Discrete Wavelet Transform are used to extract maximum value, minimum value, mean value, variance, and standard deviation of detail coefficients. Neural network classifies normal and arrhythmia beats using 55 numbers of input features, and then the accuracy rate is 98.8%.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2001.05a
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• pp.194-199
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• 2001

쾌적한 스포츠웨어는 기능성에 있어서 자연환경의 변화조건과 인체의 운동 및 활동에 맞추어 열절달 및 수분전달 등을 적절히 조절할 수 있어야 한다. 이에 본 연구에서는 일반환경조건 및 강우환경조건하에서의 형상기억 투습방수직물 소재의 스포츠웨어 착용에 따른 인체생리반응 및 쾌적감을 규명하기 위하여 스포츠웨어를 제작하여, 인공기후실에서 환경조건변화에 따른 온열생리학적 특성 및 주관적 감각을 측정, 그 특성을 비교, 고찰하였다. 평균피부온은 강우환경조건에서 온도가 낮게, 변동폭이 많게 나타났다. 변화경향을 운동부하를 기점으로 온도의 상승이 나타났고, 운동 2단계에 가장 높은 온도를 나타냈으며, 이후 감소하였다. 직장온은 일반환경조건에 비해 강우환경조건에서 온도의 미세한 상승을 보였다. 의복내 기후는 두 조건 모두에서 가슴부위보다 등부위의 온·습도의 변동폭이 크게 나타났고, 강우환경조건에서의 의복내 온도를 제외하고는 모두 등부위의 온·습도가 높게 나타났다. 최고 혈압은 운동의 강도에 따라 비례하여 상승하고, 최저 혈압에는 큰 영향없이 나타났으며, 변화경향은 의복내 온도의 경향과 역으로 나타났다. 평균혈압은 일반환경조건에서 6.9mmHg 높게 나타났다. 심박수는 일반환경조건에서 4.4beats/min 높게 나타났다. 강우환경조건의 주관적 감각의 평가에서, 신체에 직접 가해지는 빗물 등으로 인해 불쾌감이 증가하였고, 운동 후에는 일반환경조건과 달리 냉감이 증가하였으며, 습윤감은 최고치에 달하였다.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.13 no.8
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• pp.626-636
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• 2003

The beat distribution property of the King Seong-deok Divine Bell is investigated by experiment and analysis. The beat map method is proposed to explain the beat distribution property on the circumference of the bell. For the analytical investigation, an analytical model of the vibration beat is derived on a slightly asymmetric shell of revolution by using the modal expansion method. In the analytical method, the beat map can be drawn only if the modal parameters of the bell are obtained. The analytical beat model is applied to draw the beat map of the King Seong-deok Divine Bell. The validity of the analytical method is verified by comparing the analytical beat maps with the experimental results. This paper proposes a visualization method of the beat and theoretically identifies the reason why the clear and unclear beats repeat periodically along the circumference of the bell and how the striking position influences the beat distribution property.

• Journal of Physiology & Pathology in Korean Medicine
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• v.22 no.4
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• pp.725-732
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• 2008

From old times, we think it is very important to become pregnancy with child and to give birth healthy, as the human gives not just body but also spirit. When we judge pregnancy, we usually check lady's menstrual cycle. But it is too difficult to diagnosis as pregnancy only check that. Therefore feeling pulse has been made use of knowing pregnancy or not, monthly pregnancy states and childbirth. "Haung-di-nei-jing" mentions pregnancy-pulse, for example, "Yin beats and Yang distinguishes", "Shou-shao-yin-mai moves severely", "Lady has some symptoms, but no Xie-mai". Since then, there are many opinions of schools about that. For the period of pregnancy, pulse shows special features, according as the symptoms differ from month to month. When pregnant woman is just about to bear, her pulse changes unusually. In oriental medicine, it is called as Li-jing-mai. Pregnancy-pulse is worth refering to pursue a clinical examination.

• Korean Journal of Veterinary Research
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• v.43 no.3
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• pp.501-505
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• 2003

The chemical immobilization in giraffes (Giraffa camelopardalis reticulata) remains a challenge because of their size, behavior, and anatomic and physiologic characteristics that commonly create life threatening problems during immobilization. The drug combination medetomidine (MED) and ketamine (KET) was administered by remote injection. The dosages of MED and KET were correlated to the giraffe's shoulder height (SH), become recumbent with a dosage of $114{\mu}g$ of MED and 2.1 mg of KET, $320{\mu}g$ of atipamezole per cm of SH, respectively. After injection of the drugs, initial signs of sedation including ataxia were noticed at 3 minutes followed by lateral recombency at 12 minutes. The mean heart rate, respiratory rate and rectal temperature recorded during the procedures were 55 beats per minute, 48 breaths per minute and $36.6^{\circ}C$, respectively. Atipamezole was administered, after 33 minutes result in death. Assuming that 24 hours fasting times were short and light esteemed of atipamzole adverse effects like vomiting, passive regurgitation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.6
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• pp.1128-1133
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• 2011

In a wind farm, a large number of small wind turbine generators (WTGs) operate whilst a small number of a large generator do in a conventional power plant. To maintain high quality and reliability of electrical energy, a wind farm should have equal performance to a thermal power plant in the transient state as well as in the steady state. The wind farm shows similar performance to the conventional power plant in the steady state due to the advanced control technologies. However, it shows quite different characteristics during fault conditions in a grid, which gives significant effects on the operation of a wind farm and the power system stability. This paper presents an analysis of response of a wind farm during grid fault conditions. During fault conditions, each WTG might produce different frequency components in the voltage. The different frequency components result in the non-fundamental frequencies in the voltage and the current of a wind farm, which is called by "beats". This phenomenon requires considerable changes of control technologies of a WTG to improve the characteristics in the transient state such as a fault ride-through requirement of a wind farm. Moreover, it may cause difficulties in protection relays of a wind farm. This paper analyzes the response of a wind farm for various fault conditions using a PSCAD/EMTDC simulator.

• Journal of Biomedical Engineering Research
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• v.30 no.4
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• pp.294-305
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• 2009

The bio signals essentially have different characteristics in each person. And the main purpose of automatic diagnosis algorithm based on bio signals focuses on discriminating differences of abnormal state from personal differences. In this paper, we propose automatic ECG diagnosis algorithm which discriminates normal heart beats from premature ventricular contraction using optimization of wavelet parameterization to solve that problem. The proposed algorithm optimizes wavelet parameter to let energy of signal be concentrated on specific scale band. We can reduce the personal differences and consequently highlight the differences coming from arrhythmia via this process. The proposed algorithm using ELM as a classifier show high discrimination performance between normal beat and PVC. From the experimental results on MIT-BIH arrhythmia database the performances of the proposed algorithm are 98.1% in accuracy, 93.0% in sensitivity, 96.4% in positive predictivity, and 0.8% in false positive rate. This results are similar or higher then results of existing researches in spite of small human intervention.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.4
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• pp.293-299
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• 2004

This paper is about the extraction of basis function for ECG signal processing. In the first step, it is assumed that ECG signal consists of linearly mixed independent source signals. 12 channel ECG signals, which were sampled at 600sps, were used and the basis function, which can separate and detect source signals - QRS complex, P and T waves, - was found by applying the fast fixed point algorithm, which is one of learning algorithms in independent component analysis(ICA). The possibilities of significant point detection and classification of normal and abnormal ECG, using the basis function, were suggested. Finally, the proposed method showed that it could overcome the difficulty in separating specific frequency in ECG signal processing by wavelet transform. And, it was found that independent component analysis(ICA) could be applied to ECG signal processing for detection of significant points and classification of abnormal beats.

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.5
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• pp.702-712
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• 2016

A wrist watch type wearable cardiovascular monitoring device is proposed for continuous and convenient monitoring of the patient's cardiovascular system. For comprehensive monitoring of the patient's cardiovascular system, the concurrent electrocardiogram (ECG) and arterial pulse wave (APW) sensor front-end are fabricated in $0.18{\mu}m$ CMOS technology. The ECG sensor frontend achieves 84.6-dB CMRR and $2.3-{\mu}Vrms$-input referred noise with $30-{\mu}W$ power consumption. The APW sensor front-end achieves $3.2-V/{\Omega}$ sensitivity with accurate bio-impedance measurement lesser than 1% error, consuming only $984-{\mu}W$. The ECG and APW sensor front-end is combined with power management unit, micro controller unit (MCU), display and Bluetooth transceiver so that concurrently measured ECG and APW can be transmitted into smartphone, showing patient's cardiovascular state in real time. In order to verify operation of the cardiovascular monitoring system, cardiovascular indicator is extracted from the healthy volunteer. As a result, 5.74 m/second-pulse wave velocity (PWV), 79.1 beats/minute-heart rate (HR) and positive slope of b-d peak-accelerated arterial pulse wave (AAPW) are achieved, showing the volunteer's healthy cardiovascular state.

• 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.