• 대한의용생체공학회:의공학회지
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• 제43권6호
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• pp.399-408
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• 2022

Because arrhythmia occurs irregularly, it should be examined for at least 24 hours for accurate diagnosis. For this reason, this paper developed firmware software for arrhythmia detection and prevented consumption of temporal and human resources and enabled continuous management and early diagnosis. Prior to the experiment, the interval between the R peaks of the QRS Complex was calculated using the Pan-Tompkins algorithm. The developed firmware software designed and implemented an algorithm to detect arrhythmia such as tachycardia, bradycardia, ventricular tachycardia, persistent tachycardia, and non-persistent tachycardia, and a data transmission format to monitor the collected data based on BLE. As a result of the experiment, arrhythmia was found in real time according to the change in BPM as designed in this paper. And the data quality for BLE communication was verified by comparing the sensor's serial communication value with the Android application reception value. In the future, wearable devices for real-time arrhythmia detection will be lightweight and developed firmware software will be applied.

• 대한치과의사협회지
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• 제40권9호통권400호
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• pp.703-708
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• 2002

Cardiac arrhythmia is irregular heart rate. It's one of the reason of unpredictable sudden death. Accurate diagnosis and management of cardiac arrhythmia are the most important factors for the life of patient. To obtain a good prognosis, Dentist should be know and manage the multi-types of cardiac arrhythmia during dental treatment with the cooperation of medical doctor majored in cardiac circulation medicine. We casually found the cardiac arrhythmia in mandible prognathism patient during preparation for orthognathic surgery. Orthognathic surgery for cardiac arrhythmia patient was done successfully under general anesthesia with the temporary cardiac pace-maker.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1990년도 춘계학술대회
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• pp.13-16
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• 1990

This paper describes a software algorithm for automatic diagnosis of arrhythmia using the criteria of Minnesota code manual. This algorithm represents more accurate and more objective information to medical doctor by standardizing the criteria of diagnosis of arrhythmia. Because this algorithm doesn't need complicated mathematic processing, it carries out the real-time automatic diagnosis that is very important in clinic. The Decision-Table technology suggests the proper results for the given conditions. So it expresses the complicated medical problems simply and clearly, those are not solved by the mathematical methods. The Decision-Tables have very simple structure and so it is very easy to correct or expand the system by adding or correcting some rules.

• 대한의용생체공학회:의공학회지
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• 제11권1호
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• pp.171-178
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• 1990

This paper describes a software algorithm for automatic diagnosis of arrhythmia using the criteria of Minnesota code manual. This algorithm provides more accurate and more objective information to medical doctor by standardizing the criteria of diagnosis of arrhythmia. Because this algorithm doesn't need complicated mathematic processing, it carries out the real-time automatic diagnosis that is very important in clinic. The Decision-Table technology suggests the proper results for the given conditions. So it can express clearly the complicated medical problems those are not solved by the mathematical methods. The Decision-Tables have very simple structure. Therefore, it is very easy to correct or expand the system by adding or correcting some rules.

• 전기전자학회논문지
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• 제25권1호
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• pp.212-217
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• 2021

Premature contraction arrhythmia is the most common disease among arrhythmia and it may cause serious situations such as ventricular fibrillation and ventricular tachycardia. Most of arrhythmia clasification methods have been developed with the primary objective of the high detection performance without taking into account the computational complexity. Also, personalized difference of ECG signal exist, performance degradation occurs because of carrying out diagnosis by general classification rule. Therefore it is necessary to design efficient method that classifies arrhythmia by analyzing the persons's physical condition and decreases computational cost by accurately detecting minimal feature point based on only QRS features. We propose method for personalized specific classification of premature contraction arrhythmia based on QRS features in smart healthcare environments. For this purpose, we detected R wave through the preprocessing method and SOM and selected abnormal signal sets.. Also, we developed algorithm to classify premature contraction arrhythmia using QRS pattern, RR interval, threshold for amplitude of R wave. The performance of R wave detection, Premature ventricular contraction classification is evaluated by using of MIT-BIH arrhythmia database that included over 30 PVC(Premature Ventricular Contraction) and PAC(Premature Atrial Contraction). The achieved scores indicate the average of 98.24% in R wave detection and the rate of 97.31% in Premature ventricular contraction classification.

• Clinical and Experimental Pediatrics
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• 제60권11호
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• pp.344-352
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• 2017

Arrhythmias in the neonatal period are not uncommon, and may occur in neonates with a normal heart or in those with structural heart disease. Neonatal arrhythmias are classified as either benign or nonbenign. Benign arrhythmias include sinus arrhythmia, premature atrial contraction, premature ventricular contraction, and junctional rhythm; these arrhythmias have no clinical significance and do not need therapy. Supraventricular tachycardia, ventricular tachycardia, atrioventricular conduction abnormalities, and genetic arrhythmia such as congenital long-QT syndrome are classified as nonbenign arrhythmias. Although most neonatal arrhythmias are asymptomatic and rarely life-threatening, the prognosis depends on the early recognition and proper management of the condition in some serious cases. Precise diagnosis with risk stratification of patients with nonbenign neonatal arrhythmia is needed to reduce morbidity and mortality. In this article, I review the current understanding of the common clinical presentation, etiology, natural history, and management of neonatal arrhythmias in the absence of an underlying congenital heart disease.

• Clinical and Experimental Pediatrics
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• 제53권6호
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• pp.680-687
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• 2010

Patients with congenital heart diseases (CHD) are confronted with early- and late-onset complications, such as conduction disorders, arrhythmias, myocardial dysfunction, altered coronary flow, and ischemia, throughout their lifetime despite successful hemodynamic and/or anatomical correction. Rhythm disturbance is a well-known and increasingly frequent cause of morbidity and mortality in patients with CHD. Predisposing factors to rhythm disturbances include underlying cardiac defects, hemodynamic changes as part of the natural history, surgical repair and related scarring, and residual hemodynamic abnormalities. Acquired factors such as aging, hypertension, diabetes, obesity, and others may also contribute to arrhythmogenesis in CHD. The first step in evaluating arrhythmias in CHD is to understand the complex anatomy and to find predisposing factors and hemodynamic abnormalities. A practical stepwise approach can lead to diagnosis and prompt appropriate interventions. Electrophysiological assessment and management should be done with integrated care of the underlying heart defects and hemodynamic abnormalities. Catheter ablation and arrhythmia surgery have been increasingly applied, showing increasing success rates with technological advancement despite complicated arrhythmia circuits in complex anatomy and the difficulty of access. Correction of residual hemodynamic abnormalities may be critical in the treatment of arrhythmia in patients with CHD.

• 한국컴퓨터정보학회논문지
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• 제18권8호
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• pp.131-139
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• 2013

본 논문에서는 먼저 심전도 진단을 위한 처리 과정별 관련 연구내용을 살펴본 후 심전도 신호의 리듬 특징을 이용하여 부정맥을 검출 및 분류하는 방법을 제안한다. 특징 추출에서는 리듬 구간에 대하여 동일성 및 규칙성 등의 리듬 및 심박 분포에 관련되는 특징을 추출하게 되며, 리듬 분류에서는 리듬 구간의 특징에 대하여 미리 구축된 규칙 베이스를 이용하여 리듬 유형을 분류하게 된다. MIT-BIH 부정맥 데이터베이스의 모든 리듬 유형에 대한 실험을 통하여 정상 리듬 규칙만으로도 100% 부정맥 검출 성능을 보였으며, 부정맥 리듬 규칙으로는 유형 분류 적용 가능성을 확인하였다.

• 대한전자공학회논문지
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• 제26권8호
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• pp.1217-1226
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• 1989

This paper describes a design of hardware system for real time automatic diagnosis of ECG arrhythmia based on pipeline processor consisting of three microcomputer. ECG data is acquisited by 12 bit A/D converter with hardware QRS triggered detector. Four diagnostic parameters-heart rate, morpholigy, axis, and ST segment-are used for the classification and the diagnosis of arrhythmia. The functions of the main CPU were distributed and processed with three microcomputers. Therefore the effective data process and the real time process using microcomputer can be obtained. The interconnection structure consisting of two common memory unit is designed to decrease the delay time caused by data transfer between processors and be which the delay time can be taken 1% of one clock period.

• 대한의용생체공학회:의공학회지
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• 제30권4호
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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.