• Science of Emotion and Sensibility
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• v.6 no.4
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• pp.9-14
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• 2003

Sleep stages have been useful indicator to check a person's comfortableness in a sleep, But the traditional method of scoring sleep stages with polysomnography based on the integrated analysis of the electroencephalogram(EEG), electrooculogram(EOG), electrocardiogram(ECG), and electromyogram(EMG) is too restrictive to take a comfortable sleep for the participants, While the sympathetic nervous system is predominant during a wakefulness, the parasympathetic nervous system is more active during a sleep, Cardiovascular function is controlled by this autonomic nervous system, So, we have interpreted the heart rate variability(HRV) among sleep stages to find a simple method of classifying sleep stages, Six healthy male college students participated, and 12 night sleeps were recorded in this research, Sleep stages based on the "Standard scoring system for sleep stage" were automatically classified with polysomnograph by measuring EEG, EOG, ECG, and EMG(chin and leg) for the six participants during sleeping, To extract only the ECG signals from the polysomnograph and to interpret the HRV, a Sleep Data Acquisition/Analysis System was devised in this research, The power spectrum of HRV was divided into three ranges; low frequency(LF), medium frequency(MF), and high frequency(HF), It showed that, the LF/HF ratio of the Stage W(Wakefulness) was 325% higher than that of the Stage 2(p＜.05), 628% higher than that of the Stage 3(p＜.001), and 800% higher than that of the Stage 4(p＜.001), Moreover, this ratio of the Stage 4 was 427% lower than that of the Stage REM (rapid eye movement) (p＜.05) and 418% lower than that of the Stage l(p＜.05), respectively, It was observed that the LF/HF ratio decreased monotonously as the sleep stage changes from the Stage W, Stage REM, Stage 1, Stage 2, Stage 3, to Stage 4, While the difference of the MF/(LF+HF) ratio among sleep Stages was not significant, it was higher in the Stage REM and Stage 3 than that of in the other sleep stages in view of descriptive statistic analysis for the sample group.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1490-1499
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• 2022

Arrhythmia is a condition in which the heart has an irregular rhythm or abnormal heart rate, early diagnosis and management is very important because it can cause stroke, cardiac arrest, or even death. In this paper, we propose arrhythmia classification using hybrid combination model of CNN-BLSTM. For this purpose, the QRS features are detected from noise removed signal through pre-processing and a single bit segment was extracted. In this case, the GAN oversampling technique is applied to solve the data imbalance problem. It consisted of CNN layers to extract the patterns of the arrhythmia precisely, used them as the input of the BLSTM. The weights were learned through deep learning and the learning model was evaluated by the validation data. To evaluate the performance of the proposed method, classification accuracy, precision, recall, and F1-score were compared by using the MIT-BIH arrhythmia database. The achieved scores indicate 99.30%, 98.70%, 97.50%, 98.06% in terms of the accuracy, precision, recall, F1 score, respectively.

• Korean Journal of Biological Psychiatry
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• v.8 no.1
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• pp.20-36
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• 2001

The debate about whether depressive disorders should be divided into categories or arrayed along a continuum has gone for decade, without resolution. In our review, there is more evidence consistent with the spectrum concept than there is with the idea that depressive disorders constitute discrete clusters marked by relatively discontinuous boundaries. First, "depression spectrum", "is there a common genetic factors in bipolar and unipolar affective disorder", "threshold model of depression" and "bipolar spectrum disorder" are reviewed. And, a new subtype of depression is so called SeCA depression that is a stressor-precipitated, cortisol-induced, serotonin-related, anxiety/aggression-driven depression. SeCA depression is discussed. But, there is with the idea that depressive disorders constitute discrete subtypes marked by relatively discontinuous boundaries. This subtypes of depressive disorder were reviewed from a variety of theoretical frames of reference. The following issues are discussed ; Dexamethasone suppression test(DST), TRH stimulation test, MHPG, Temperament Character Inventory(TCI), and heart rate variability(HRV).

• Journal of the Korea Society of Computer and Information
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• v.15 no.2
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• pp.65-74
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• 2010

We propose a system that automatically recognizes the tense or relaxed condition of scrolling-shooting game subject that plays. Existing study compares the changed values of source of stimulation to the player by suggesting the source, and thus involves limitation in automatic classification. This study applies SOM of unsupervised learning for automatic classification and recognition of player's condition change. Application of SOM for automatic recognition of tense and relaxed condition is composed of two steps. First, ECG measurement and analysis, is to extract characteristic vector through HRV analysis by measuring ECG after having the player play the game. Secondly, SOM learning and recognition, is to classify and recognize the tense and relaxed conditions of player through SOM learning of the input vectors of heart beat signals that the characteristic extracted. Experiment results are divided into three groups. The first is HRV frequency change and the second the SOM learning results of heart beat signal. The third is the analysis of match rate to identify SOM learning performance. As a result of matching the LF/HF ratio of HRV frequency analysis to the distance of winner neuron of SOM based on 1.5, a match rate of 72% performance in average was shown.

• The KIPS Transactions:PartB
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• v.15B no.6
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• pp.507-516
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• 2008

Cardiac disease is the leading cause of death in the world. Quantification of cardiac function is performed by manually calculating blood volume and ejection fraction in routine clinical practice, but it requires high computational costs. In this study, an automatic left ventricle (LV) segmentation algorithm using short-axis cine cardiac MRI is presented. We compensate coil sensitivity of magnitude images depending on coil location, classify edge information after extracting edges, and segment LV by applying region-growing segmentation. We design a weighting function for intensity signal and calculate a blood volume of LV considering partial voxel effects. Using cardiac cine SSFP of 38 subjects with Cornell University IRB approval, we compared our algorithm to manual contour tracing and MASS software. Without partial volume effects, we achieved segmentation accuracy of $3.3mL{\pm}5.8$ (standard deviation) and $3.2mL{\pm}4.3$ in diastolic and systolic phases, respectively. With partial volume effects, the accuracy was $19.1mL{\pm}8.8$ and $10.3mL{\pm}6.1$ in diastolic and systolic phases, respectively. Also in ejection fraction, the accuracy was $-1.3%{\pm}2.6$ and $-2.1%{\pm}2.4$ without and with partial volume effects, respectively. Results support that the proposed algorithm is exact and useful for clinical practice.

• Proceedings of the ESK Conference
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• 1995.10a
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• pp.37-37
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• 1995

CNS의 인간공학적 실험 평가 항목중 중요 요소의 하나인 운전원의 인지적 작업부하(정보입력, 의사결정, 및 정서적 부하)를 평가하기 위해 인지적부하를 부과할 수 있는 사건 시나리오 구성방법, 피실험자에 대한 훈련 방법, 실험과 디브리핑을 통한 운전원 행위 및 사건 경위 기록 체계를 개발하였다. 운전원 행위자료 데이타베이스에는 특정 요소행위 시점, 관측행위 분류, 사용된 표시장치, 의사결정내용, 사용된 조종장치, 조종행위분류, 운전원간 의사소통 내용, 정서상태, 표시장치 및 조종장치의 사용편의성 여부 및 불편이유, 주요사건 발생시점에 관한 정보가 기록되었다. 운전중 CNS 운전원에 제시되는 자극의 변화에 수반되는 운전원의 생리적 변화를 측정하여 이로부터 운전원이 받는 정신부하를 측정하는 체계를 개발하였다. 이를 위해 ECG, EEG, 호흡패턴,피부온도, 수평EOG, 수직EOG, 심박률, 및 호흡률의 생리변수에 대한 측정이 이루 어졌으며 각각의 신호를 초당 100개씩 샘플링하여 A/D 변환하고 정신부하 추정 알고리즘을 거쳐 정신부하 여부를 판정하는 점수를 구하였다. 다차원의 정신부하 판정 점수는 OR gate에 의해 통합되어 정신부하 발생시점과 함께 정신부하데이터베이스에 기록되었다.

• Proceeding of EDISON Challenge
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• 2017.03a
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• pp.712-714
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• 2017

미병의 예방과 관리의 중요성이 거론되고 있으나, 미병에 대한 분류나 진단을 위한 확고한 근거가 미약한 상황으로서 미병 진단 인자 분류를 위한 생리시스템 모델 개발이 필요한 시점이다. 본 연구의 목적은 개발한 생리학적 모델이 미병 단계를 구별하는데 효과 및 유용성이 있는지를 임상 검증하기 위하여 생리학적 모델 인공지능 시뮬레이션을 개발하고자 함이다. 인공지능 계산은 3층으로 구성된 네트워크를 이용하였으며 각 층은 30개의 neuron들로 구성하였다. 인공지능망의 입력 값은 나이, 수축기 혈압, 이완기 혈압, 심박수 값 (입력 값 4개)이고 출력 값은 혈관 저항값인 Ra이다. 머신러닝 차수를 높이면서 인공지능을 사용하지 않은 생리적 모델로부터 도출된 결과와 인공지능을 통하여 계산된 결과를 비교하였다. 개발된 인공지능계산을 이용한 생리시스템 모델은 대량의 표본집단에서 임상 검증에 기여할 것이다.

• Journal of Chest Surgery
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• v.29 no.12
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• pp.1337-1341
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• 1996

From September 1989 to March 1996, 13 patients with prosthetic valve thrombosis underwent reoperdtion on 16 occasions. The mean interval between implantation and reoperation was 27.8 months. The anticoagulation status was inadequate in 44% of th Instances. The majority(75%) were in NYHA functional class IV, 6 of them being in shock. Reoperation was performed for valve replacement(15 of 16 occasions) or thrombectomy(1 of 16 occasions) within 3 to 192 hours(mean 33.5 hours). Operative mortality at reoperation was 25%(4 patients). Re-thrombosis occurred In 3 patients. Long-term outcome was satisfactory in all survivors with a mean follow-up of 30.B months. The present results indicate that an early diagnosis and prompt surgical intervention is needed to decrease operative mortality.

• The Korean Journal of Nuclear Medicine Technology
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• v.12 no.3
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• pp.222-228
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• 2008

Purpose: The objectives of this study were to compare the left ventricle ejection fraction (LVEF) from gated cardiac blood pool scan (GCBP) for analysis auto-drawing region of interest mode (AROI) and manual-drawing region of interest mode (MROI), respectively. To evaluation the relationships between values produced by both ROI modes. Materials and Methods: Gated cardiac blood pool scan using in vivo method Tc-99m Red Blood Cell were performed for 33 patients (mean age: $53.2{\pm}13.2\;y$) with objective of chemotherapy using single head gamma camera (ADAC Laboratories, Milpitas, CA). Left ventricular ejection fraction was automatically and manually measured, respectively. Results: There was significant difference statistically between AROI and MROI ($LVEF^{AROI}$: $71.4{\pm}12.4%$ vs. $LVEF^{MROI}$: $65.8{\pm}5.9%$, p=0.003). Intra-observer agreements in AROI was higher than MROI ($\gamma^{AROI}=0.964$, Cronbach's $\alpha^{AROI}=0.986$ vs. $\gamma^{MROI}=0.793$, Cronbach's $\alpha^{MROI}=0.911$), either. Additionally, there was no significant difference statistically at best septal view (${\Delta}LVEF^{BSV}=0.7{\pm}2.3%$, p=0.233), however statistically significant difference was found at badly separated septal view (${\Delta}LVEF=10.9{\pm}11.4%$, p=0.001). Moreover, Intra-observer agreements in best septal view was higher than badly separated septal view ($\gamma^{BSV}=0.939$, Cronbach's $\alpha^{BSV}=0.978$; $\gamma=0.948$, Cronbach's $\alpha=0.981$ at AROI, $\gamma^{BSV}=0.836$, Cronbach's $\alpha^{BSV}=0.936$; $\gamma=0.748$, Cronbach's $\alpha=0.888$ at MROI). Conclusion: When best septal view was acquired, LVEF by AROI and MROI indicated not different. Comparing Intra-observer agreements with AROI and MROI, the AROI tended to show higher. Therefore, it is considered that the AROI than MROI is valuable in reproducibility and objective when ROI analysis by acquire left ventricular of best septal view.

• Journal of Chest Surgery
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• v.30 no.12
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• pp.1205-1213
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• 1997

This study reviewed useful aspects of the intraoperative transesophageal echocardiography among the patients in whom heart surgery were undertaken between January 1996 and July 1996 at St.Pauls hospital, Medical College of Catholic University, Seoul, Korea. During that period, 61 patients were operated on because of valvular heart disease(25 patients), coronary artery disease(22 patients), congenital heart disease(13 patients), and combined coronary artery disease and valvular heart disease(1 patient). Two patients(1 redo-VSD and 1 valvular heart diease) needed repeated aortic cross clamping and complementary procedures because of incomplete initial procedures. There was no incidence of air embolism. We could observe significant relationship of cardiac output monitoring methods either by thermodilution technique and transesophageal echocardiography by linear regression analysis(p<0.001). We tested myocardial response(percentage of systolic wall thickness, PSWT) with low dose dobutamine challenge to predict post-CABG myocardial perfusion. And the test showed statistically significant resp.onse(sensitivity 76%, specificity 94.7%, positive predictive value 95%, negative predictive value 75%). These results suggest that cardiac surgeon could draw more benefits by intraoperative transesophageal echocardiography.