• Korea Information Processing Society Review
• /
• v.21 no.5
• /
• pp.73-81
• /
• 2014

• Proceedings of the Korean Society for Emotion and Sensibility Conference
• /
• 2009.05a
• /
• pp.209-210
• /
• 2009

수면단계는 수면감성을 평가하는데 있어서 중요한 생리지표로서 사용되어왔다. 그러나 수면다원검사를 이용한 전통적 수면단계 분류방법은 뇌전도, 안전도, 심전도, 근전도 등을 종합적으로 측정하므로 수면단계를 비교적 정확히 분류할 수 있지만 피험자에게 심한 구속감을 주는 문제가 있다. 본 연구에서는, 각성상태에서 교감신경계가 지배적인 반면에 수면 중에는 부교감신경계가 더 활동적인 점에 착안하여 수면단계를 간단히 분류할 수 있는 방법을 찾고자 수면단계에 따른 심박동변이도(heart rate variability: HRV)를 분석하였다. 단일채널 심전도를 이용하여 수면단계별로 HRV 의 교감신경계/부교감신경계 활성도의 비율을 분석한 결과, W(wakefulness) 단계가 NREN(non REM) 2 단계, 3 단계, 4 단계에 비하여 높게 나타났으며, NREM 4 단계는 REM(rapid eye movement) 단계와 NREM 1단계에 비하여 낮게 나타났다. 또한 교감신경계/부교감신경계 활성도 비율의 수면단계에 따라 변화하는 양상은 W, REM, NREM 1, 2, 3, 4 단계의 순으로 단조 감소하였다.

• Journal of the Korean Society of Radiology
• /
• v.10 no.4
• /
• pp.285-290
• /
• 2016

The purpose of our study was to retrospectively evaluate the cause of a decreased calcium score of follow-up studies on coronary artery calcium scores (CACs) computed tomography (CT). The subjects were healthy 100 people(85 males $60.6{\pm}6.9$ years, 15 females $67.2{\pm}7.3$ years). The subjects decreased CACs were divided into 4 subgroups depending on Agatston classification, minimal (1-10), mild (11-100), moderate (101-400), severe (400<). As a result of decreased CACs were scan location disagreement 51%, motion artifact 26%, equipment changes 14%, operator mistakes 5%, input miss 2%, image loss 1%, arrhythmia 1%. In the mild group, the most common decreased CACs were 49 people. In the minimal group, the most significant variation reduction has occurred to 6 people. Scan location disagreement was considered a partial volume effects due to the scan starting position. It showed less than 100 CACs a high variation (19.7%) in more than 100 CACs, a lower variation (2.2%), these could be seen that the variation range is different that can be tolerated according to the calcification score. Motion artifact factor was found in 26%, which is so closely related to the preceding tests that affect the higher heart rate like this pulmonary function test, exercise stress test.

• The KIPS Transactions:PartD
• /
• v.16D no.1
• /
• pp.11-26
• /
• 2009

In order to diagnose cardiovascular disease, we proposed EP-based(emerging pattern- based) classification technique using multi-parametric diagnosis indexes. We analyzed linear/nonlinear features of HRV for three recumbent postures and extracted four diagnosis indexes from ST-segments to apply the multi-parametric diagnosis indexes. In this paper, classification model using essential emerging patterns for diagnosing disease was applied. This classification technique discovers disease patterns of patient group and these emerging patterns are frequent in patients with cardiovascular disease but are not frequent in the normal group. To evaluate proposed classification algorithm, 120 patients with AP (angina pectrois), 13 patients with ACS(acute coronary syndrome) and 128 normal people data were used. As a result of classification, when multi-parametric indexes were used, the percent accuracy in classifying three groups was turned out to be about 88.3%.

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

• Annual Conference of KIPS
• /
• 2023.05a
• /
• pp.627-629
• /
• 2023

생체 신호를 분석하여 사용자의 건강과 정신 상태를 예측하고, 관련 질병에 관해 예방하는 연구가 늘어나고 있다. 생체 신호 중 심박은 사람의 육체, 정신적인 상태를 반영하는 대표적인 신호이지만 기존의 접촉 패드를 통한 ECG나 광학 센서를 통한 PPG로 심박을 예측할 때는 구속적인 환경이 필요하여 일상적인 상황 속에 적용하기 어려웠다. 이러한 단점을 해결하고자 본 논문은 UBFC-RPPG 데이터셋의 동영상 프레임을 RGB 채널마다 다른 가중치를 적용하는 전처리를 하여 학습 데이터의 크기를 줄이면서 정확도를 높이고, 3D-CNN을 활용한 딥러닝으로 순간적인 영상에서도 PPG 신호를 예측할 수 있도록 1초 전처리 영상을 학습한 후, 신호를 예측하는 것을 목표로 한다. 이렇게 비접촉식으로 취득된 신호는 더 다양한 환경에서의 감정분류, 우울증 진단, 질병 감지 등 다양한 분야에 활용될 수 있다.

• Science of Emotion and Sensibility
• /
• v.8 no.1
• /
• pp.47-54
• /
• 2005

This study is aimed to inspect how the different sensitivities in Behavioral activation system(BAS) and behavioral inhibition system(BIS) modulate on the properties of physiological responses stimulated by positive or negative affective sound. We measured the electroencephalogram(EEG) and electrocardiogram (ECG) of 32 students, consisted of four groups depending on the BAS and BIS sensitivities, during listening to meditation music or noise. The EEG was recorded at Fpl and Fp2 sites and Power spectral density(PSD) of HRV was derived from the ECG, and the power of HRV was calculated for 3 major frequency ranges(low frequency[LF], medium frequency and high frequency[HF]). After listening to music or noise, subjects reported the affect induced by the sound. For EEG, the power in the alpha band at Fp2, especially in the alpha-2 band(9.0-11.0 Hz) increased during the subjects listening to music, while the power at Fpl increased during noise. During listening to meditation music, there is a tendency that the left-sided activation in prefrontal cortex(PFC) is positively correlated with the difference of BAS(Z)-BIS(Z). During listening to noise, there is a tendency that the right-sided activation in PFC is dominant in case any of the sensitivity of BAS or BIS is high. For HRV, we found that the index of MF/(LF+HF), during listening to music, was higher significantly in the individuals with a low BIS but high BAS than in the individuals with a low sensitivity both BIS and BAS individuals. With high BIS, regardless of the BAS sensitivity, the difference of this index values was not significant. From these results we suggest that the physiological responses of different individuals in BAS and BIS react differently under the same emotionally provocative challenge.

• KIISE Transactions on Computing Practices
• /
• v.21 no.7
• /
• pp.464-469
• /
• 2015

Long-term electrocardiogram data can be acquired by linking a Holter monitor to a mobile phone. However, most systems are designed to detect arrhythmia through heartbeat classification, and not just for supporting clinical decisions. In this paper, we propose an Abstracting algorithm, and introduce an analogous pateint search system using this algorithm. An analogous patient searcher summarizes each patient's typical pattern using the results of heartbeat, which can greatly simplify clinical activity. It helps to find patients with similar arrhythmia patterns, which can help in contributing to diagnostic clues. We have simulated these processes on data from the MIT-BIH arrhythmia database. As a result, the Abstracting algorithm provided a typical pattern to assist in reaching rapid clinical decisions for 64% of the patients. On an average, typical patterns and results generated by the abstracting algorithm summarized the results of heartbeat classification by 98.01%.

• Science of Emotion and Sensibility
• /
• v.6 no.4
• /
• pp.41-49
• /
• 2003

To inspect how the different sensitivities in BAS(or BIS) modulate on the HRV pattern stimulated by positive or negative affective sound, we measured the electrocardiogram(ECG) of 25 students(male : 14), consisted of 4 groups depending on the BAS(or BIS) sensitivity, during listening meditation music or being exposed to noise. The power spectral density(PSD) of HRV was derived from the ECG, and the power of HRV was calculated for 3 major frequency ranges(low frequency[LF], medium frequency[MF], and high frequency[HF]). We found that the index of MF/(LF+HF), during listening music, was higher significantly in the individuals with a low BIS but high BAS than in the individuals with a low sensitivity in both BIS and BAS. Especially in the former group, there was a tendency that the index was higher during listening music than during being exposed to noise. For individuals with a high BIS, regardless of the BAS sensitivity, the difference of this index values was not significant. From these results we suggest that individuals with a low BIS but high BAS are more sensitive to positive affective stimuli than other groups, and the index of MF/(LF+HF) is applicable to evaluate positive and negative affects.

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