• Journal of Sensor Science and Technology
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• v.22 no.5
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• pp.338-345
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• 2013

Premature ventricular contractions are the most common of all arrhythmias and may cause more serious situation like ventricular fibrillation and ventricular tachycardia in some patients. Therefore, the detection of this arrhythmia becomes crucial in the early diagnosis and the prevention of possible life threatening cardiac diseases. Most methods for detecting arrhythmia require pp interval, or the diversity of P wave morphology, but they are difficult to detect the p wave signal because of various noise types. Thus, it is necessary to use noise-free R wave. So, the new approach for the detection of PVC is presented based on the rhythm analysis and the beat matching in this paper. For this purpose, we removed baseline wandering of low frequency band and made summed signals that are composed of two high frequency bands including the frequency component of QRS complex using the wavelet filter. And then we designed R wave detection algorithm using the adaptive threshold and window through RR interval. Also, we developed algorithm to classify PVC using RR interval. The performance of R wave and PVC detection is evaluated by using MIT-BIH arrhythmia database. The achieved scores indicate average detection rate of 99.76%, sensitivity of 99.30% and specificity of 98.66%; accuracy respectively for R wave and PVC detection.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.15 no.4
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• pp.485-494
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• 2008

Purpose: In this study, relationships between symptom experience and quality of life in a cross-sectional sample of patients with Atrial Fibrillation (AF) were investigated. Methods: This descriptive study involved a convenience sample of AF patients from S university hospital, C city. One hundred and two AF patients completed psychometric validated measures of AF related symptoms and quality of life. Descriptive statistics and Pearson correlation coefficients with SPSS WIN 14.0 were used for data analysis. Results: Of 16 atrial arrhythmia-related symptoms, the patients reported 'tiredness' as the most frequent and 'shortness of breath' as the most severe. The level of overall quality of life for patients with AF was 53.92. There were significant differences in symptom frequency according to religion, New York Heart Association (NYHA) classification and left ventricular ejection fraction ; symptom severity according to monthly income and stroke ; quality of life according to age, job, alcohol intake, NYHA class and stroke. Quality of life for these patients was positively correlated with symptom frequency and symptom severity. Conclusions: This study demonstrated that patients with more frequent and severe symptoms perceive poorer quality of life than patients with less frequent and less severe symptoms. Symptom experience should be assessed early to improve quality of life for patients.

• Journal of Chest Surgery
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• v.57 no.1
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• pp.1-24
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• 2024

• Advances in Traditional Medicine
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• v.4 no.3
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• pp.157-161
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• 2004

We showed the effects of the traditional herbal medicine, Jukyeoondam-tang (JO-T, Zhu-ru-Wen-Dan-Tang in Chinese), on ventricular arrhythmia induced by aconitine. Electrophysiological experiments with conventional microelectrode techniques revealed that JO-T potently suppressed the aconitine-induced arrhythmias in ventricular strips of the rat. In the aconitine-induced arrhythmia model of the rat, pretreatment with JO-T $(100\;{\mu}g/ml)$ completely occluded the appearance of ventricular tachyarrhythmia (VT) or ventricular fibrillation (VF) induced by aconitine. Furthermore, the aconitine-induced ventricular arrhythmia was occluded by $Na^+$ channel blocker quinidine but was not occluded by $K^+$ channel blocker glibenclamide $(3\;{\mu}mol/L)\;and\;Ca^{2+}$ channel blocker nifedipine $(10\;{\mu}mol/L)$. We also confirmed the effect of JO-T in the ischemia-reperfusion (I/R)-induced arrhythmia model of the rat. JO-T did not affect the I/R-induced arrhythmias in rats. JO-T may alleviate the risk of ventricular arrhythmias following aconitine. These results suggest that JO-T is a potent antiarrhythmic drug having a$Na^+$ channel-blocking action.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.3
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• pp.204-210
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• 2011

This paper proposes a fuzzy support vector machine ($FSVM_n$) pattern classifier to classify the arrhythmia patterns of an electrocardiograph (ECG). The $FSVM_n$ is a pattern classifier which combines n-dimensional fuzzy membership functions with a slack variable of SVM. To evaluate the performance of the proposed classifier, the MIT/BIH ECG database, which is a standard database for evaluating arrhythmia detection, was used. The pattern classification experiment showed that, when classifying ECG into four patterns - NSR, VT, VF, and NSR, VT, and VF classification rate resulted in 99.42%, 99.00%, and 99.79%, respectively. As a result, the $FSVM_n$ shows better pattern classification performance than the existing SVM and FSVM algorithms.

• Journal of Chest Surgery
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• v.16 no.3
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• pp.337-341
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• 1983

The experience with operative treatment for total correction of Tetralogy of Fallot at the department of Thoracic and Cardiovascular Surgery, Korea University Hospital from January, 1977, through April, 1983 was reviewed. Of the 29 patients reviewed, male to female occurrence ratio was 22:7 Type of V.S.D. was type II in 26 cases[90%] and total conus defect in 3 cases[10%]. Average size of V.S.D. was 19 mm. Type of Right ventricular outflow tract stenosis was highest frequency with pulmonary valvular and infundibular stenosis combined type in 21 cases[72%], and there were 8 deaths In this group. Type of R.V.O.T. reconstruction contains 2 cases of infundibulectomy only, 1 case of infundibulectomy with valvular commissurotomy, 2 cases of pericardial patch, 23 Cases of pericardial patch with Teflon or Dacron felt reinforced and 1 case of pulmonary valved conduit reconstruction. Operative mortality was higher in outflow patch through pulmonary valve ring. Overall mortality was 31%. Major causes of death and postoperative complications were low output syndrome, complete A-V block acute renal failure, ventricular fibrillation, bleeding brain abscess, and sudden cardiac arrest.

• 순환기질환의공학회:학술대회논문집
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• 2002.11a
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• pp.46-47
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• 2002

• 한국전산유체공학회:학술대회논문집
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• 2008.03b
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• pp.496-497
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• 2008

In this study, we present the computational analysis of cardiac arrhythmias that is the major cause of human sudden cardiac death. First, electric excitation and condution in one dimensional cardiac tissue model is solved and the results on condution block are represented. In two dimensional model, vortex daynamics in cardiac tissue is analyzed to delineate the breakup phenomenon inducing ventricular fibrillation. We also simulated a three dimenional heart model to see the vortex breakup and explained the mechanism in physiological aspect.

• Journal of Chest Surgery
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• v.24 no.12
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• pp.1201-1208
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• 1991

Two successful pulmonary thromboendartectomies were performed. In the first case, it was performed under cardiopulmonary bypass with moderate hypothermia and ventricular fibrillation In the second case, it was done under deep hypothermia and intermittent circulatory arrest. The patients are recovered uneventfully without complication and discharged from the hospital on warfarin. Their symptoms were improved and the follow-up pulmonary perfusion scans revealed no evidence of residual pulmonary embolus in both cases.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.9
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• pp.2021-2030
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• 2012

Premature ventricular contraction(PVC) is the most common disease among arrhythmia and it may cause serious situations such as ventricular fibrillation and ventricular tachycardia. Particularly, in the healthcare system that must continuously monitor patient's situation, it is necessary to process ECG (Electrocardiography) signal in realtime. In other words, the design of algorithm that exactly detects R wave using minimal computation and classifies PVC by analyzing the persons's physical condition and/or environment is needed. Thus, the patient adaptive pattern matching algorithm for the classification of PVC is presented in this paper. For this purpose, we detected R wave through the preprocessing method, adaptive threshold and window. Also, we applied pattern matching method to classify each patient's normal cardiac behavior through the Hash function. The performance of R wave detection and abnormal beat classification is evaluated by using MIT-BIH arrhythmia database. The achieved scores indicate the average of 99.33% in R wave detection and the rate of 0.32% in abnormal beat classification error.