• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.669-672
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• 2017

최근 한국인의 주요 사망원인 중 하나로 부정맥이 부각되고 있다. 심방조기수축(PAC:Premature Atrial Contraction)은 심방이 동방결절의 명령이 있기 전에 수축해 버리는 것이다. 심방조기수축은 일시적으로 유발하였다 사라지곤 할 수 있기 때문에 심한 증상이 없다면 생명에 위협을 가하진 않지만 반대의 경우에는 위험할 수 있다. 따라서 비정상적인 심장 박동이 발생하면 이를 검출하여 조기에 부정맥을 진단할 수 있는 방법이 필요하다. 이를 위해 대상의 ECG 신호로부터 QRS패턴에 해당하는 특징들을 추출하였고 특징들을 이용하여 심방조기수축 파형을 분류한다. 오류 역전파 기반으로 특징들을 훈련하며 가중치와 바이어스값을 구한뒤 이를 이용하여 정상파형과 심방조기수축 파형을 분류한다.

• 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.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.1399-1402
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• 2011

본 논문에서는 조기 심실 수축과 조기 심방 수축을 검출함에 있어 정밀한 QRS 구간의 폭, 정확한 P파와 T파의 크기 및 위치를 크게 요구하지 않고, 데이터의 가공과 복잡한 알고리즘의 사용에 의해 발생하는 ECG 데이터의 변형과 손실을 최소화할 수 있으며, 또한 개인차 때문에 발생할 수 있는 오류를 최소화하기 위한 알고리즘을 제안한다. 이를 위해 ECG 신호를 각각의 단위 파형으로 분리한 후, 정상 R-R 간격을 가지는 파형을 기준으로 기준파형을 만들어, 각 파형과 기준파형사이의 패턴 대조 및 유사도 분석을 통해 조기 심실수축과 조기심방수축을 검출할 수 있도록 하였다.

• The KIPS Transactions:PartD
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• v.19D no.1
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• pp.105-112
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• 2012

Most methods for detecting PVC and APC require the measurement of accurate QRS complex, P wave and T wave. In this study, we propose new algorithm for detecting PVC and APC without using complex parameter and algorithms. Proposed algorithm have wide applicability to abnormal waveform by personal distinction and difference as well as all sorts of normal waveform on ECG. To achieve this, we separate ECG signal into each unit patterns and made a standard unit pattern by just using unit patterns which have normal R-R internal. After that, we detect PVC and APC by using similarity analysis for pattern matching between standard unit pattern and each unit patterns.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1924-1925
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• 2007

본 논문에서는 부정맥 판별을 위한 전처리 과정으로 PCA, LDA, ICA를 바탕으로 하여 정확도를 비교하여 보았다. 각각의 전처리는 고유의 특성을 가지고 있으며 본 논문의 목적은 부정맥 판별상 어떤 전처리가 더욱 정확성의 면에서 효과적인지를 알아보는 것이다. 본 논문의 데이터는 MIT-BIH에 기반하고 있으며, Beat의 분류는 정상(Normal), 좌각차단(Left Bundle Branch Block, LBBB), 우각차단(Right Bundle Branch Block, RBBB), 조기심실수축(Premature Ventricular Contraction, PVC), 조기심방수축(Atrial Premature Beat, APB), paced Beat, 심실보충수축(Ventricular Escape Beat)로 나누었다. 실험적 결과는 PCA-BPNN의 경우 95.53%, ICA-BPNN의 경우 93.95%, LDA-BPNN의 경우 96.42%로 LDA가 가장 ECG 부정맥 판별 응용에 있어 가장 효율적인 방법으로 나타났다.

• Journal of Chest Surgery
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• v.32 no.3
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• pp.255-261
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• 1999

Background: Atrial fibrillation is one of the most prevalent of all arrhythmias and in up to 79% of the patients with mitral valve disease. This study examined whether the atrial fibrillation that occur in patients with mitral valve operation could be eliminated by a concommitant maze operation without cryoablation. Material and Method: From May 1997 to April 1998, 14 patients with atrial fibrillation associated with mitral valve disease underwent Maze III operation without cryoablation. Preoperatively there were 6 men and 8 women with an average age of 46.2${\pm}$10.7 years. Eleven patients had mitral stenosis, and three had mitral insufficiency. The associated heart diseases were aortic valve disease in 4, tricuspid valve regurgitation in 1 and ASD in 2. Using transthoracic echocardiography, the mean left atrial diameters was 54.7${\pm}$5.3 mm and thrombi were found in the left atrium of 2 patients. Postoperatively the ratio between the peak speed of the early filling wave and that of the atrial contraction wave (A/E ratio) was determined from transmitral flow measurement. Operations were mitral valve replacement in 13 including 4 aortic valve replacements, 1 DeVega annuloplasty and 2 ASD closures. Maze III operation was performed in 1 patient. Result: Five patients (38%) had recurred atrial fibrillation, which was reversed with flecainide or amiodarone at the average time of postoperative 38.8${\pm}$23.5 days. Postoperative complications were postoperative transient junctional rhythm in 6, transient atrial fibrillation in 5, reoperation for bleeding in 3, postpericardiotomy syndrome(1), unilateral vocal cord palsy(1), postoperative psychosis(1), and myocardial infarction(1). Postoperatively A/E ratio was 0.43${\pm}$0.22 and A wave found in 9(64%) patients. 3 to 14 months postoperatively (average follow- up, 8.1 months), all of patients had normal sinus rhythm and 9(64%) patients had left atrial contraction and 11(79%) patients were not on a regimen of antiarrhythmic medication. Conclusion: We conclude that Maze III operation without cryoablation is an effective surgical treatment in atrial fibrillation associated with the mitral valve disease.

• Journal of Yeungnam Medical Science
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• v.4 no.2
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• pp.23-27
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• 1987

Mass electrocardiographic (ECG) examination was performed on 13,801 children (male 7,526 and female 6,275) of elementary and middle school in Taegu from May 1. 1986. to April 30. 1987. We read their ECG according to the "Pediatric Electrocardiography." The results were as following; The Incidence of ECG abnormality was 1.05%(male 1.3% and female 0.75%). Fifty eight children (0.42%) had atrial and ventricular hypertrophy; two right atrial hypertrophy, five left atrial hypertrophy, thirty five fight ventricular hypertrophy and sixteen left ventricular hypertrophy respectively. Ectopic beats occurred in 25 children (0.18%) ; They were atrial in 12 children, ventricular in 8 children and junctional in 5 children. There were 62 children (0.45%) of conduction disturbance ; They were first degree atrioventricular (A-V) block in 21 children, type I second degree A-V block in 1 child, A-V dissociation in 1 child, right bundle branch block in 36 children, left bundle branch block in 1 child and WPW syndrome in 2 children. Nonspecific ST, T changes and sinus tachycardia were found in 3 and one children respectively.

• 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.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.2
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• pp.62-69
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• 2022

An electrocardiogram (ECG) is one of the most important biosignals, and in particular, continuous ECG monitoring is very important in patients with arrhythmia. There are many different types of arrhythmia (sinus node, sinus tachycardia, atrial premature beat (APB), and ventricular fibrillation) depending on the cause, and continuous ECG monitoring during daily life is very important for early diagnosis of arrhythmias and setting treatment directions. The ECG signal of arrhythmia patients is very unstable, and it is difficult to detect the R-peak point, which is a key feature for automatic arrhythmias detection. In this study, we develped a continuous measuring Holter ECG monitoring device and software for analysis and confirmed the utility of R-peak of the ECG signal with MIT-BIH arrhythmia database. In future studies, it needs the validation of algorithms and clinical data for morphological classification and prediction of arrhythmias due to various etiologies.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.8
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• pp.1947-1954
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• 2013

Previous works for detecting arrhythmia have mostly used nonlinear method such as artificial neural network, fuzzy theory, support vector machine to increase classification accuracy. Most methods require accurate detection of P-QRS-T point, higher computational cost and larger processing time. But it is difficult to detect the P and T wave signal because of person's individual difference. Therefore it is necessary to design efficient algorithm that classifies different arrhythmia in realtime and decreases computational cost by extrating minimal feature. In this paper, we propose arrhythmia detection based on binary coding using QRS feature varibility. For this purpose, we detected R wave, RR interval, QRS width from noise-free ECG signal through the preprocessing method. Also, we classified arrhythmia in realtime by converting threshold variability of feature to binary code. PVC, PAC, Normal, BBB, Paced beat classification is evaluated by using 39 record of MIT-BIH arrhythmia database. The achieved scores indicate the average of 97.18%, 94.14%, 99.83%, 92.77%, 97.48% in PVC, PAC, Normal, BBB, Paced beat classification.