• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.1
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• pp.16-22
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• 2010

Electrocardiogram(ECG) analysis and arrhythmia recognition are critical for diagnosis and treatment of ill patients. Cardiac arrhythmia is a condition in which heart beat may be irregular and presents a serious threat to the patient recovering from ventricular tachycardia (VT) and ventricular fibrillation (VF). Other arrhythmias like atrial premature contraction (APC), Premature ventricular contraction (PVC) and superventricular tachycardia (SVT) are important in diagnosing the heart diseases. This paper presented new method to classify various arrhythmias contrary to other techniques which are limited to only two or three arrhythmias. ECG is decomposed into Intrinsic Mode Functions (IMFs) by Empirical Mode Decomposition (EMD). Burg algorithm was performed on IMFs to obtain AR coefficients which can reduce the dimension of feature vector and utilized as Multi-class SVM inputs which is basically extended from binary SVM. We chose optimal parameters for SVM classifier, applied to arrhythmias classification and achieved the accuracies of detecting NSR, APC, PVC, SVT, VT and VP were 96.8% to 99.5%. The results showed that EMD was useful for the preprocessing and feature extraction and multi-class SVM for classification of cardiac arrhythmias, with high usefulness.

• 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.

• Journal of Veterinary Clinics
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• v.6 no.2
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• pp.281-290
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• 1989

To gain insight into the relationship between the occurrence of occlusive arrhythmia(OA) and the incidence of reperfusion arrhythmia(RA), this study used 25 open-chest dogs anesthetized with halothan, these were ligated between anterior ventricular branch and marginal branch of left circumflex artery for 30 minutes and occlusive arrhythmia were observed during the ligation. After releasing of the ligation, TA were observed during 5 minutes. The results were summerized as follow； 1. Such arrhythmias as ventricular fibrillation(VF), short run type VPC Premature contraction(VPC), Venticular tachycardia(VT), ventricularc and trigeminy VPC(TVPC) were observed during occlusion and reperfusion. 2. The cases occurred VT, SRVPC and TVPC during occlusion necessarily were Incidence of RA. 3. RA never occurred without appearence of occlusive arrhythmias. 4. The occurrence rate of OA showed 55.5% in the incidence group of RA and 24.6％ in the non incidence group of RA. 5. The occurrence rate of VPC during occlusion showed 9.9＋5.85(episode/min) in the incidence group of RA and 4.46＋5.88(episode/min) in the non-incidence group of RA. These results may be estimated that the occurrence of VT, SRVPC and TVPC, and the high occurrence rate of VPC during occlusion can be predicted the incidence.

• The Korean Journal of Emergency Medical Services
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• v.9 no.1
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• pp.25-32
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• 2005

Purpose: There has been an increase in the number of prehospital cardiac arrests due to increases in both cardiovascular diseases and the average age of the population, We performed this study to identify the proper resuscitation technique and AED to be used to increase the survival rate in prehospital cardiac arrest. Methods: We studied 57 victims with prehospilal cardiac arrest by EMT's Reports form January to December, 2004. Results: Fifty-seven of 92 victims were trasported with ECG in prehospital cardiac arrest. Ventricular fibrillation(VF)/ ventricular tachycardia was 56.2%, asystole was 33,3%, and pulseless electrical activity(PEA.) was 10.5% in initial rhythm analysis, There weren't attempt CPR in 14.0%. Twenty of the 32(62.5%) were shocked by AED for the adequacy method. There were no statistical differences the transportation time. Conclusion: With the increase in cardiovascular disease and old age, the number out-of-hospital cardiac arrests has risen accordingly. However, there were lack of CPR by bystander, defibrillation, advanced cardiac life support(ACLS) in prehospital stage. To improve the adequancy of basic life support and to increase the performance of ACLS, especially AED, we must create challenges to develop new protocols in prehospital care.

• Journal of Biomedical Engineering Research
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• v.28 no.4
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• pp.556-568
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• 2007

Unsatisfied results of return of spontaneous circulation (ROSC) estimates were caused by the fact that the predictability of the predictors was insufficient. This unmet estimate of the predictors may be affected by transitional events due to behaviors which occur during cardiopulmonary resuscitation (CPR). We thus hypothesized that the discrepancy of ROSC estimates found in statistical characteristics due to transitional CPR events, may affect the performance of the predictors, and that the performance of the classifier dichotomizing between ROSC and No-ROSC might be different during CPR. In a canine model (n=18) of prolonged ventricular fibrillation (VF), standard CPR was provided with administration of two doses of epinephrine 0 min or 3 min later of the onset of CPR. For the analysis of the likelihood of a successful defibrillation during CPR, Support Vector Classification was adopted to evaluate statistical peculiarity combining time and frequency based predictors: median frequency, frequency band-limited power spectrum, mean segment amplitude, and zero crossing rates. The worst predictable period showed below about 1 min after the onset of CPR, and the best predictable period could be observed from about 1.5 min later of the administering epinephrine through 2.0-2.2 min. As hypothesized, the discrepancy of statistical characteristics of the predictors was reflected in the differences of the classification performance during CPR. These results represent a major improvement in defibrillation prediction can be achieved by a specific timing of the analysis, as a change in CPR transition.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.5
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• pp.45-54
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• 2007

Time/frequency analysis has been extensively used in biomedical signal processing. By extracting some essential features from the electro-physiological signals, these methods are able to determine the clinical pathology mechanisms of some diseases. However, this method assumes that the signal should be stationary, which limits its application in non-stationary system. In this paper, we develop a new signal processing method using Hilbert-Huang Transform to perform analysis of the nonlinear and non-stationary ventricular fibrillation(VF). Hilbert-Huang Transform combines two major analytical theories: Empirical Mode Decomposition(EMD) and the Hilbert Transform. Hilbert-Huang Transform can be used to decompose natural data into independent Intrinsic Mode Functions using the theories of EMD. Furthermore, Hilbert-Huang Transform employs Hilbert Transform to determine instantaneous frequency and amplitude, and therefore can be used to accurately describe the local behavior of signals. This paper studied for Return Of Spontaneous Circulation(ROSC) and non-ROSC prediction performance by Support Vector Machine and three parameters(EMD-IF, EMD-FFT) extracted from ventricular fibrillation ECG waveform using Hilbert-Huang transform. On the average results of sensitivity and specificity were 87.35% and 76.88% respectively. Hilbert-Huang Transform shows that it enables us to predict the ROSC of VF more precisely.

• International Journal of Control, Automation, and Systems
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• v.3 no.4
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• pp.571-579
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• 2005

In this paper, we proposed an algorithm for arrhythmia classification, which is associated with the reduction of feature dimensions by linear discriminant analysis (LDA) and a support vector machine (SVM) based classifier. Seventeen original input features were extracted from preprocessed signals by wavelet transform, and attempts were then made to reduce these to 4 features, the linear combination of original features, by LDA. The performance of the SVM classifier with reduced features by LDA showed higher than with that by principal component analysis (PCA) and even with original features. For a cross-validation procedure, this SVM classifier was compared with Multilayer Perceptrons (MLP) and Fuzzy Inference System (FIS) classifiers. When all classifiers used the same reduced features, the overall performance of the SVM classifier was comprehensively superior to all others. Especially, the accuracy of discrimination of normal sinus rhythm (NSR), arterial premature contraction (APC), supraventricular tachycardia (SVT), premature ventricular contraction (PVC), ventricular tachycardia (VT) and ventricular fibrillation (VF) were $99.307\%,\;99.274\%,\;99.854\%,\;98.344\%,\;99.441\%\;and\;99.883\%$, respectively. And, even with smaller learning data, the SVM classifier offered better performance than the MLP classifier.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.4
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• pp.274-283
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• 2005

Coronary Perfusion Pressure(CPP) is known for the most important parameter related to the Return of Spontaneous Circulation (ROSC), however, clinically measuring CPP is difficult either invasive or non-invaisive method. En this paper, we analyze the correlation between the extracted parameter from VF ECG wave and the CPP with the statistical method, and predict CPP value using the extracted parameters within significance level. the extracted parameters are median frequency(MF), peak frequency(PF), average segment amplitude(ASA), MSA(maximum segment amplitude), Two parameters, MF, and ASA are selected in order to predict CPP value with general regression neural network, and then we evaluated the agreement statistics between the simulated CPP and the measured CPP. In conclusion, the mean and variance of the difference between the simulated CPP and the measured CPP are 8.9716±1.3526 mmHg, and standard deviation 6.4815 mmHg with one hundred-times training and test results. the simulated CPP and the measured CPP are agreed with the overall accuracy $90.68\%$ and kappa coefficient $81.14\%$ as a discriminant parameter of ROSC.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.730-736
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• 2011

In this paper, we designed the models for pattern classification which can reflect the latest trend in time series. It has been shown that fusion models based on statistical and AI methods are superior to traditional ones for the pattern classification model supporting decision making. Especially, the hit rates of pattern classification models combined with fuzzy theory are relatively increased. The statistical SVM models combined with fuzzy membership function, or the models combining neural network and FCM has shown good performance. BPN, PNN, FNN, FCM, SVM, FSVM, Decision Tree, Time Series Analysis, and Regression Analysis were used for pattern classification models in the experiments of this paper. The economical indices DB with time series properties of the financial market(Korea, KOSPI200 DB) and the electrocardiogram DB of arrhythmia patients in hospital emergencies(USA, MIT-BIH DB) were used for data base.

• The Korean Journal of Emergency Medical Services
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• v.8 no.1
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• pp.149-160
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• 2004

Background : To save out-of-hospital cardiac arrest cases is a major concern for Korea. Cardiac arrest is a very common problem, with > 18,000 cases dying each year in Korea. Overall, survival to hospital discharge remains poor. Resuscitation has become an important multidisciplinary branch of medicine, demanding a spectrum of skills and attracting a plethora of specialities and organizations. Since the "Utstein Style" was advocated in 1991, many reports about out-of-hospital cardiac arrest have been published based on this guideline. These differences prevent valid inter-hospital and international comparisons. However, we do not know the true effectiveness of resuscitation. There are no guideline for reviewing, reporting, conducting research on resuscitation in Korea. This study evaluated the out-of-hospital factor associated with survival discharge of out-of-hospital cardiac arrest, was especially to provide basic data for the unified reporting guideline of resuscitation in Korea. Methods : From January 1990 to July 2004, we collected data about out-of-hospital cardiac arrest at Wonju Christian Hospital(WCH-CAD), Ewha Women University Mokdong Hospital(Ewha-CAD), I used same record form based on the "Utstein Style". The "Utstein Style" is internationally recommended guidelines for reporting outcome data from resuscitation events. Results : Resuscitation was performed in 1443 out-of-hospital cardiac arrest patients at 2 hospitals. Five hundred eighty(40.25%) patients recovered the spontaneous circulation at least once and One hundred sixty eight(11.66%) patients discharged alive. Initial EKG showed Ventricular Tachycardia/Ventricular Fibrillation in One hundred thirty five(9.33%) patients, asystole in one thousand nine(69.73%) patients and other rhythms in one hundred thirty nine(20.94%) patients. Among one hundred two cardiogenic cardiac arrest patients, two(2.0%) patients was discharged alive. Conclusion : Overall survival rate of out-of-hospital cardiac arrest patients was 11.66% which was poorer than that of the western country. The proportion of the cardiogenic cause was 33.38% which was only half of the western country. VT/VF is relatively not common ac a initial EKG rhythm. These differences might be to due difference in the prevalence pattern of out-of-hospital cardiac arrest as well as prematurity of the EMSS. It is needed that the best survival can be achieved if all following links have been optimized : rapid access, early CPR, early defibrillation, early ACLS.