• International Journal of Vascular Biomedical Engineering
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• v.3 no.1
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• pp.14-22
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• 2005

In the present study, our aim is to investigate whether responses to the head-up tilt (HUT) on nonlinear properties of heart rate variability (HRV) in young and elderly subjects are different or not. Thirteen young-healthy subjects ($24.5{\pm}3.7$ years) and 18 old-aged healthy subjects ($74.5{\pm}7.4$ years) participated in this study. An electrocardiogram (ECG) in the supine posture, at $0^{\circ}$, and in the standing posture, at $70^{\circ}$ of head-up tilt, was recorded. Detrended fluctuation analysis (DFA) and approximate entropy (ApEn), measures of short-/long-term correlation properties and overall complexity of heart rate (HR) respectively, along with spectral components of HR variability (HRV) were analyzed for both the supine and HUT postures. We observed that the short-term fractal exponent ${\alpha}_1$ increased during HUT posture (F(1, 29) = 39.79, P = 0.000), especially, the young subjects showed a significantly higher values compared to the elderly subjects. ApEn significantly decreased (F(1, 29) = 8.61, P = 0.006) during HUT posture. HUT posture decreased the complexity in HR dynamics and increased short-term fractal exponent values in young subjects but not in elderly subjects. These results imply that there are differences of response to HUT on nonlinear properties between young and elderly subjects.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.1
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• pp.191-198
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• 2020

In this study, we proposed a real-time ECG analytical method for predicting stress and dangerous heart condition using the ECG signal in playing AR/VR device. A real-time diagnosis is used as R-R interval based HRV(:Heart rate variability), BPM(:Beats Per Minitue) and autonomic nervous research with through mapping method of two-dimensional planes. The ECG data were analyzed every 5 minutes and derived from autonomic nervous system diagnosis.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.61 no.1
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• pp.55-58
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• 2012

By using EEG and HRV, subjects were estimated on their psychological and physiological reaction when reading psychrometric chart in 7 point century font, in an environmental test room in the condition of temperature 25[$^{\circ}C$], relative humidity 50[RH%], air current speed 0.02[m/sec], giving variation in illuminance to 0.1, 300, 600, 1000, 1300 and 1600[lux]. As a result, it was at 1300[lux] that absolute ${\alpha}$ wave, SMR, SDNN were most vitalized, and also both sides ${\alpha}$ wave asymmetry index, SEF50, HRT, stress and fatigue degree were at the lowest. It was found that a certain illuminance which minimizes psychological stress and fatigue degree while enhancing concentration and task achievement stably does exist.

• Science of Emotion and Sensibility
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• v.1 no.1
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• pp.93-103
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• 1998

In this paper, we present change of human sensiblity when the 26 healthy female subjects were exposed with visual picture stimulus. We used Intermational Affective Picture System as the visual stimulus. The methods are AutoRegressive(AR) spectrum which is a linear method and Return Map which is a nonlinear mithod. SR spectrum may variability(HRV). The LF/HF of HRV and the variation of Return Map were analyzed from ECG signal of the female subjects. Return Map of RR intervals were analyzed by computiong the variation. When the subjets were stimulated by the pleasant pictures, LF/HF and variation were decreased compared with unpleasant stimulus, We may obtain good parameters for the measurement of the change of human sensibility for the visual picture stimulus.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.1
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• pp.37-42
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• 2010

Final year students are normally encountering high pressing in their study. In view of this fact, this research focuses on determining mental states condition of college student in final year based on the psycho-physiological information. The experiments were conducted in two times, i.e., prior- and post- graduation seminar examination. The early results indicated that the student profile of mood states (POMS) in prior final graduation seminar showed higher scores than students in post final graduation seminar. Thus, in this research, relation between biosignal representing by heart rate variability (HRV) and questionnaire responses were evaluated by hidden Markov model (HMM) and neural networks (NN).

• Journal of the Korea Society of Computer and Information
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• v.22 no.6
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• pp.87-93
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• 2017

In this paper, we design a small low power single channel ECG(Electrocardiogram) system of Chest Belt type with fiber-type electrodes to measure emotional state change of game addict. HRV(Heart Rate Variability) is analyzed through heart rate signal measurement and the psychological stress state is judged by using it. And it verifies its effectiveness through prototype. First, we design HR measurement module through low power MCU(Micro Controller Unit) and implement prototype level measurement system. The results showed that the difference between the addiction group and the general group was confirmed and that the system was effective. The result of this study can be used for health management such as reduction of stress of the user through music and breathing that lowers the stress by detecting the stress state of the general person or the chronic ill person.

• Journal of Digital Contents Society
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• v.8 no.3
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• pp.355-363
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• 2007

One of major factors for learning achievement is the student's learning preference according to his character type. In course of learning, if a student studies e-learning contents opposed to his preference, then he would be under stress and his blood pressure and heart beat be changed. For measuring unwillingness, we used spectral components in frequency domain known as stress measure. For 13 children attending kindergarten we examined S(sensing)/ N(intuition) of MBTI and presented same learning contents during 10 minutes. During learning we gathered ECG signals, changed into HRV(heart rate variability), transformed time-varying HRV signal into spectral density in frequency domain. And then, we divided it into three areas of low(LF), middle(MF), and high-frequency(HF) and calculated stress measures by rates of those frequency area. We compared estimated stress measures of S group with them of N group whether students in different group preferred different contents or not. Experimental shows that students according to MBTI type prefer different contents.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.23 no.1
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• pp.76-85
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• 2010

In general, anesthetic depth is evaluated by experience of anesthesiologist based on the changes of blood pressure and pulse rate. So it is difficult to guarantee the accuracy in evaluation of anesthetic depth. The efforts to develop the objective index for evaluation of anesthetic depth were continued but there was few progression in this area. Heart rate variability provides much information of autonomic activity of cardiovascular system and almost all anesthetics depress the autonomic activity. Novel monitoring system which can simply and exactly analyze the autonomic activity of cardiovascular system will provide important information for evaluation of anesthetic depth. We investigated the anesthetic depth as following 7 stages. These are pre-anesthesia, induction, skin incision, before extubation, after extubation, Post-anesthesia. In this study, temporal, frequency and chaos analysis method were used to analyze the HRV time series from electrocardiogram signal. There were NN10-NN50, mean, SDNN and RMS parameter in the temporal method. In the frequency method, there are LF and HF and LF/HF ratio, 1/f noise, alphal and alpha2 of DFA analysis parameter. In the chaos analysis, there are CD, entropy and LPE. Chaos analysis method was valuable to estimate the anesthetic depth compared with temporal and frequency method. Because human body was involved the choastic character.

• 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.

• Journal of the Korea Computer Industry Society
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• v.7 no.4
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• pp.437-446
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• 2006

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