• Journal of Internet Computing and Services
• /
• v.10 no.2
• /
• pp.179-186
• /
• 2009

This paper presents an approach to classify normal and Ventricular Tachycardia/Ventricular Fibrillation(VT/VF) from the Creighton University Ventricular Tachyarrhythmia DataBase(CUDB) using the neural network with weighted fuzzy membership functions(NEWFM). In the first step, wavelet transform is used for producing input values which are used in the next step. In the second step, two numbers of input features are extracted by phase space reconstruction method and peak extraction method using coefficients produced by wavelet transform in the previous step. NEWFM classifies normal and VT/VF beats using two numbers of input features, and then the accuracy rate is 90.13%.

• The Journal of the Korea Contents Association
• /
• v.9 no.7
• /
• pp.19-26
• /
• 2009

This paper presents an approach to classify normal and ventricular tachycardia/fibrillation(VT/VF) from the Creighton University Ventricular Tachyarrhythmia Database(CUDB) using the neural network with weighted fuzzy membership functions(NEWFM) and wavelet transforms. In the first step, wavelet transforms are used to obtain the detail coefficients at levels 3 and 4. In the second step, all of detail coefficients d3 and d4 are classified into four intervals, respectively, and then the standard deviations of the specific intervals are used as eight numbers of input features of NEWFM. NEWFM classifies normal and VT/VF beats using eight numbers of input features, and then the accuracy rate is 90.1%.

• Proceedings of the KIEE Conference
• /
• 2007.10a
• /
• pp.473-474
• /
• 2007

본 연구는 체내 이식형 Pacemaker를 연구하면서 심장 질환을 Therapy 해 주는 방법에 대해 저전력 및 성능향상에 중점을 두고 연구 및 실험을 하였다. 우선적으로 심장의 심박동을 연산량이 적은 Peak_detection에서 체크하여 전력소모를 줄이고 나오는 각 심실 및 심방의 Interval을 Disease_episode 에서 받는다. 여기서 5가지 심실 및 심방에 관한 질환들 (VF : Ventricular Fibrillation, VT : Ventricular Tachycardia, FVT : Fast Ventricular Tachycardia, FAT_AF : Fast Atrial Tachycardia/Atrial Fibrillation, AT_AF : Atrial Tachycardia AT_AF : Atrial Fibrillation)을 판별한 후 각 병증에 맞는 Therapy 값을 출력하게 하였다. 그 외에 남아있는 병증에 대해서도 Therapy가 저전력 및 성능향상 되도록 설계하였다. 기존에 적용되어 있는 Detection 기법에서는 각각의 병증에 대해서 각 Detection이 있어 VF와 VT 사이에 있는 FVT와 같은 병증을 치료할 때 FVT 같은 경우에는 VF와 VT사이에 있는 질병이기 때문에 FVT_VF 및 FVT_VT와 같이 각각의 Detection을 두어 전력 소모가 있었다. 심장에서는 여러 질병이 한번에 나을 수 없다는 것에 착안하여 (심박동 Interval에 의해 질병이 판단되므로) 다른 병증이지만 같은 진단 기준을 쓰는 Detection을 통합함으로써 하나의 모듈로 구성하여 Gate수를 줄이고 저전력을 구현하였다. 또한 병증을 판별하는 진단 기준 모듈 중 Onset_Criterion 재설계하여 좀더 성능 향상에 중점을 두었다.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.42 no.5 s.305
• /
• pp.27-34
• /
• 2005

Ventricular fibrillation(VF) is generally caused by chaotic behavior of electrical propagation in heart and may result in sudden cardiac death. In this study, we proposed a ventricular fibrillation detection algorithm based on support vector machine classifier, which could offer benefits to reduce the teaming costs as well as good classification performance. Before the extraction of input features, raw ECG signal was applied to preprocessing procedures, as like wavelet transform based bandpass filtering, R peak detection and segment assignment for feature extraction. We selected input features which of some are related to the rhythm information and of others are related to wavelet coefficients that could describe the morphology of ventricular fibrillation well. Parameters for SVM classifier, C and ${\alpha}$, were chosen as 10 and 1 respectively by trial and error experiments. Each average performance for normal sinus rhythm ventricular tachycardia and VF, was 98.39%, 96.92% and 99.88%. And, when the VF detection performance of SVM classifier was compared to that of multi-layer perceptron and fuzzy inference methods, it showed similar or higher values. Consequently, we could find that the proposed input features and SVM classifier would one of the most useful algorithm for VF detection.

• The Korean Journal of Physiology and Pharmacology
• /
• v.3 no.1
• /
• pp.47-52
• /
• 1999

Blood flow restoration to ischemic zone of the heart is essential to salvage of ischemic tissue. However, there is a large body of evidence documenting that the reperfusion can induce reperfusion injury like reperfusion-induced malignant arrhythmias. In the present study, employing a cat model of regional cardiac ischemia, we examined if reperfusion rendered in a gradual fashion could lower the incidence of reperfusion-induced ventricular fibrillation (VF), which usually precipitated within a few to several tens of seconds after abrupt reperfusion. The experiments were conducted with male mongrel cats (n=46, 2.5-5 kg). The animals in the control and 30 MIN groups were subjected to an episode of 20- and 30-min left anterior descending coronary artery occlusion, respectively, followed by abrupt reperfusion. The animals in 5 G and 10 G groups received gradual reperfusion over a 5- and 10-min period, respectively, following a 20-min occlusion. The proportion of animals that exhibited VF during the reperfusion phase was 11/15 in the control, 7/10 in the 30 MIN, 5/10 in the 5 G and 2/11 in the 10 G groups. The incidence of VF in the 10 G group was significantly lower than that in the control or 30 MIN group subjected to abrupt reperfusion. These results suggest that the gradual reperfusion is a useful procedure against reperfusion-induced VF.

• Korean Journal of Clinical Pharmacy
• /
• v.6 no.2
• /
• pp.32-40
• /
• 1996

The electrophysiological effects of benzopyran potassium channel openers (PCOs: lemakalim, KR-30450 and KR-30818) on the ischemia/reperfusion-induced arrythmias were investigated. In anesthetized rats, subjected to 45 min occlusion of the left anterior descending coronary artery (LAD) followed by 90 min reperfusion, ventricular arrythmias were identified according to the Lambeth Conventions by lead II ECG. Rats were intravenously given vehicle ($1\%$ DMSO), lemakalim, KR-30450, and KR-30818 alone or in combination with a selective $K_{ATP}$ blocker glibenclamide, 30 min prior to coronary occlusion. Compared to vehicle, lemakalim ($30{\mu}g/kg$ i.v.), the active enantiomer of cromakalim, had a tendancy to increase the duration of ventricular tachycardia (Vl) and ventricular fibrillation (VF), the number of premature ventricular complexes (PVC) and the incidence of VF, especially in the early post-occlusion peroid ($0\~15$ min), while increasing ST-segment elevation. Both KR-30450 ($30{\mu}g/kg$, i.v.) and KR-30818 (30, $100{\mu}g/kg$, i.v.) showed similar proarrhythmic effects to lemakalim (PVC, duration of VT, and incidence of VF) with a tendancy to decrease the duration of VF and ST-segment elevation. Unlike other PCOs, however, glibenclamide (0.3, 1.0 mg/kg) had opposite effects on the induction of arrhythmias (PVC, the duration of VF); it had a tendancy to increase the duration of VT with a slight elevation of ST-segment. It seems likely that glibenclamide (0.3 mg/kg, i.v.), reduced the effects of lemakalim or KR-30450 ($30{\mu}g/kg$, i.v.) on arrhythmias (PVC, VT, VF and ST-segment). These results indicate that, in the coronary occluded rat model of ischemia, lemikuiln and KR-30450 exert a proarrhythmic activity, the effect being considered related to the opening of KATP channel.

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

• Proceedings of the IEEK Conference
• /
• 2006.06a
• /
• pp.873-874
• /
• 2006

In this paper, we have developed a ventricular fibrillation detection system based on DSP processor. The developed system was able to detect VF in real time correctly and quickly. We compared the performance of the floating point simulation with that of fixed point simulation. The computational cost of fixed point simulation was remarkably reduced than that of floating point simulation.

• The Korean Journal of Physiology and Pharmacology
• /
• v.4 no.4
• /
• pp.319-324
• /
• 2000

The causal relationship between heat shock protein (HSP) and second window of cardioprotective effect is still undetermined. In the present study, we assessed whether HSP-producing substances, amphetamine and ketamine, afforded protection against reperfusion-induced ventricular fibrillation (VF) and these protective effect remained after the inhibition of HSP72 production by quercetin, a mitochondrial ATPase inhibitor. Adult mongreal male cats $(n=60,\;2.5{\sim}4\;kg)$ were used in this study. Experimental animals were divided into five groups; control group (n=15), amphetamine ('A', n=11) group, ketamine ('K', n=9) group, amphetamine-ketamine ('AK', n=16) group and amphetamine-ketamine-quercetin ('AKQ', n=9) group. Twenty-four hours after the drug treatment, an episode of 20-min coronary artery occlusion was followed by 10-min reperfusion. The incidence of reperfusion-induced VF in the AK and AKQ groups was significantly lower than that in control group (p＜0.01). After the ischemia/reperfusion procedure, western blot analysis of HSP72 expression in the myocardial tissues resected from each group was performed. HSP72 production in the AK group was marked, whereas HSP72 was not detected in the AKQ and control groups. These results suggest that the suppressive effect against reperfusion-induced VF induced by amphetamine and ketamine is not mediated by myocardial HSP72 production but by other mechanisms.

• Industrial Engineering and Management Systems
• /
• v.12 no.4
• /
• pp.380-388
• /
• 2013

Large variation in electrocardiogram (ECG) waveforms continues to present challenges in defining R-wave locations in ECG signals. This research presents a procedure to extract the R-wave locations by forward-backward (FB) algorithm and classify the arrhythmic beat conditions by using RR intervals. The FB algorithm shows forward and backward searching rules from QRS onset and eliminates lower-amplitude signals near the baseline using a statistical process control concept. The proposed algorithm was trained the optimal parameters by using MIT-BIH arrhythmia database (MITDB), and it was verified by actual Holter ECG signals from a local hospital. The signals are classified into normal (N) and three arrhythmia beat types including premature ventricular contraction (PVC), ventricular flutter/fibrillation (VF), and second-degree heart block (BII) beat. This work produces 98.54% accuracy in the detection of R-wave location; 98.68% for N beats; 91.17% for PVC beats; and 87.2% for VF beats in the collected Holter ECG signals, and the results are better than what are reported in literature.