• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1999.11a
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• pp.396-400
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• 1999

인간의 감성은 다차원적 감정으로 이루어져 있다. 본 연구는 감성의 2차원 구조를 근거로 쾌-불쾌, 각성-이완 2차원적 감성을 생리신호로 분류하고자 하였다. 20명 남녀 대학생을 참가시켜 자극을 2차원 감성자극(쾌(펜디향수), 불쾌(에탄올), 각성(싸이렌), 이완(가요))으로 정의하고, 2*2 자극제시로 감성을 유발하였다. 26명의 남녀대학생을 실험에 참가시켜 4가지 감성을 유발하여, 측정한 생리신호로는 중추신경계의 활동을 나타내는 EEG(f3, p3, f4, p4)를 측정하였으며, 자율신경계의 활동을 나타내는 ECG(lead II), GSR, SKT를 측정하였다. 각각의 측정한 신호들에 대한 t-test를 실시하여 유의성 있는 변수를 추출하였으며 추출된 변수는 EEG의 f3(beta), p3(delta, beta), f4(delta), p4(alpha), HRV의 HF, HF/LF, GSR의 rising time이었으며 2차원 감성을 분류하였다.

• 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.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.246-249
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• 2019

심전도는 심장운동으로 미세하게 변하는 심장의 전위차를 신체외부의 피부에서 측정한 것으로 최근 의료, 금융, 보안, 오락 등 서비스에서 기존의 생체신호시스템의 대안으로 많은 연구가 되고 있다. 기존 서비스로서 개인인식, 개인인증, 부정맥인식, 행동인식, 심방세동 검출 등은 근본적으로 심전도를 분류하는 기술이고 또한 최근 딥러닝이 여러 분야에서 두드러진 성능들이 보고되었기 때문에 딥러닝을 이용한 심전도 분석도 많은 연구가 되고 있다. 따라서 본 논문은 딥러닝기반 심전도 분류의 국내외 동향분석을 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.19-22
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• 2008

최근 서구화된 식생활 패턴과 흡연, 비만 등의 원인으로 인해 심근경색, 협심증과 같은 심근허혈(myocardial ischemia) 질환이 급증하고 있다. 이 논문에서는 심전도 신호로부터 허혈성 심장 질환 진단을 위해 출현 패턴 마이닝을 이용하여 심근경색 및 협심증의 진단 신호인 ischemia beat를 분류 하였다. 또한 기존의 출현 패턴 마이닝에 빠른 패턴 탐사와 저장 공간의 효율성을 고려하여 Apriori-T 빈발 패턴 탐사 알고리즘을 출현 패턴 생성이 가능하도록 확장하였다. PhysioNet의 ST-T 데이터베이스로부터 138개의 대조군(정상)과 ischemia beat 데이터에 제안된 분류 알고리즘을 실험한 결과 최소 75% 및 최대 95%의 예측 정확도를 보였다.

• YAKHAK HOEJI
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• v.53 no.2
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• pp.51-59
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• 2009

Quantitative analysis of (+)-catechin (C), (-)-epigallocatechin (EGC), (-)-epicatechin (EC), (-)-epigallocatechin gallate (EGCG), (-)-epicatechin gallate (ECG) and caffeine in commercial green tea was carried out by HPLC employing gradient elution of 0.1% acetic acid and acetonitrile on ODS column. The optimized HPLC method provided satisfactory linearity, accuracy and precision. The relationship between the concentration of the components and cultivated region of the commercial green tea was not significant, while the concentration of EGCG, ECG and caffeine decreased significantly in the later harvested green tea samples (p<0.01). Multivariate analysis of the components was performed in order to characterize and evaluate the cultivated region and harvest period-related variation. Hierarchical clustering and discriminant analysis were applied to classify the geographical and seasonal origins of the green tea samples. The classification accuracy of the cultivated region and harvest period by discriminant analysis was 95% and 91%, respectively, indicating that this method could be reliable and convenient for the quality control of herbal products with different origin.

• Journal of Preventive Medicine and Public Health
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• v.39 no.6
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• pp.485-492
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• 2006

Objectives : To measure the distribution of electrocardiographic ST segment depression, and evaluate its relationships with cardiovascular risk factors based on the cross-sectional studies within a rural Korean community Methods : This study analyzed 1,343 persons, over 40 years old, who participated in a baseline survey during 2002-2005; the exclusion criteria included: a past history of myocardial infarction and angina pectoris, and specific conduction abnormalities. A Standard 12 leads ECG was recorded using an FCP-2101 (Fukuda Denshi Co.). The ST segment depression was retrospectively measured by a physician, according to the Minnesota code classification. Results : ST segment depression was found in 3.6 and 6.4% of male and female participants, respectively. After adjusting for age, gender, smoking, physical activity and obesity differences, high blood pressure showed significant relations with ST depression in females (male ORs=2.67, 95% CI=0.85-8.50; female ORs=2.62, 95% CI=1.29-5.32) Conclusions : As an ischemic ECG sign, ST depression was related to hypertension in female participants. This relationship remained significant, even after cases with left ventricular hypertrophy were removed.

• Science of Emotion and Sensibility
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• v.5 no.2
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• pp.1-9
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• 2002

It is already known that olfactory susceptibility differ with races and sex. Moreover, with aging both detection and identification about olfactory information were impaired. For researches about evaluation of the odor with aging, although the subject used, from infants to elderly, was various, the kinds of odor used were restricted to simple alcohol and acetic acid. Also, the evaluation methods were mainly used olfactory test. From over respects , this research was done as follows. Subjects were 19 to 72 years (n=50) whose sense-of-smell functions are normal. They were taken as stability and closed eye state. The odor stimuli were used 100% natural odor of six kinds of Basil, Lavender, Lemon, Jasmine, Ylangylang oil and Skatole , during 60 seconds using olfactometer. ECG, GSR and subjective evaluation were measured, and examined their relevance. Twenty and 40 ages group evaluated Lemon and 60 ages group did Lavender affirmatively. Correlation was seen among RRI, HR, GSR and subjective evaluation for 40 ages group, and it turns out that it is the group which a mature olfactory function most. These results are fully applied not only to development of the classified cosmetics for the age group but to development of the artificial smell and taste.

• Clinical and Experimental Pediatrics
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• v.45 no.9
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• pp.1097-1105
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• 2002

Purpose : This study was conducted to estabilish the prevalence, clinical features and relationship between ECG findings and echocardiographic findings of Wolff-Parkinsion-White(WPW) syndrome in asymptomatic preschool children. Methods : An electrocardiographic screening study was performed on 77,824 preschool children in Jeonbuk province from April, 1999 to August, 2001. Patients with WPW syndrome underwent echocardiographic study. Results : Twenty three patients with WPW syndrome were discovered by electrocardiographic screening of preschool children. The prevalence rate was 2.9 per 10,000 preschool children and there was no significant sexual difference. Two patients had a history of symptoms related to tachyarrythmia. According to the ECG classification of Rosenbaum et al., five patients were type A and 18 were type B. Utilizing the criteria of Gallagher et al, right anterior, 12 patients; right anteiror paraseptal, four patients; left anteiror, three patients. Nineteen of 23 patients underwent echocardiographic study. Four of five patients with type A WPW syndrome had abnormal early systolic anterior motion of left ventricular posterior wall. Twelve of 14 patients with type B had abnormal interventricular septal motion characterized by early sytolic posterior motion immediately after inscription of the delta wave. Conclusion : The prevalence rate of preschool children in Jeonbuk province was 2.9/10,000. By the classification according to the electrocardiographic findings, the accessory pathway location was dominant right side than left side. In the echocardiographic study, type A WPW syndrome showed abnormal left ventricular posterior wall motion and type B WPW showed abnormal interventricular septal motion.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.4
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• pp.825-832
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• 2014

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. Even if some methods have the advantage in low complexity, but they generally suffer form low sensitivity. Also, it is difficult to detect PVC accurately because of the various QRS pattern by person's individual difference. Therefore it is necessary to design an efficient algorithm that classifies PVC based on QRS pattern in realtime and decreases computational cost by extracting minimal feature. In this paper, we propose PVC classification based on QRS pattern using QS interval and R wave amplitude. For this purpose, we detected R wave, RR interval, QRS pattern from noise-free ECG signal through the preprocessing method. Also, we classified PVC in realtime through QS interval and R wave amplitude. The performance of R wave detection, PVC classification is evaluated by using 9 record of MIT-BIH arrhythmia database that included over 30 PVC. The achieved scores indicate the average of 99.02% in R wave detection and the rate of 93.72% in PVC classification.

• Journal of Korea Multimedia Society
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• v.12 no.3
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• pp.451-459
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• 2009

This paper presents an approach to detect premature ventricular contraction(PVC) using discrete wavelet transform and fuzzy neural network. As the input of the algorithm, we use 14 coefficients of d3, d4, and d5, which are transformed by a discrete wavelet transform(DWT). This paper uses a neural network with weighted fuzzy membership functions(NEWFM) to diagnose PVC. The NEWFM discussed in this paper classifies a normal beat and a PVC beat. The size of the window of DWT is $-31/360{\sim}+32/360$ second(64 samples) whose center is the R wave. Using the seven records of the MIT-BIH arrhythmia database used in Shyu's paper, the classification performance of the proposed algorithm is 99.91%, which outperforms the 97.04% of Shyu's analysis. Using the forty records of the M1T-BIH arrhythmia database used in Inan's paper, the classification performance of the proposed algorithm is 98.01%, which outperforms 96.85% of Inan's one. The SE and SP of the proposed algorithm are 84.67% and 99.39%, which outperforms the 82.57% and 98.33%, respectively, of Inan's study.