• Journal of the Korea Society of Computer and Information
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• v.15 no.10
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• pp.105-112
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• 2010

In this paper, the bio-signals, such as EEG, ECG were measured with a sensor and their characters were drawn out and analyzed. With results from the analysis, four emotion of rest, concentration, tension and depression were inferred. In order to assess one's emotion, the characteristic vectors were drawn out by applying various ways, including the frequency analysis of the bio-signals like the measured EEG and HRV. RBFN, a neural network of the complex structure of unsupervised and supervised learning, was applied to classify and infer the deducted information. Through experiments, the system suggested in this thesis showed better capability to classify and infer than other systems using a different neural network. As follow-up research tasks, the recognizance rate of the measured bio-signals should be improved. Also, the technology which can be applied to the wired or wireless sensor measuring the bio-signals more easily and to wearable computing should be developed.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.749-754
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• 2022

High adhesion and water resistance of the skin surface are required for wearable and skin-attachable electronic patches in various medical applications. In this study, we report a stretchable electronic patch that mimics the drainable structure pattern of the hexagonal channels of frog's pads and the sucker of an octopus based on carbon-based conductive polymer composite materials. The hexagonal channel structure that mimics the pads of frogs drains water and improves adhesion through crack arresting effect, and the suction structure that mimics an octopus sucker shows high adhesion on wet surfaces. In addition, the high-adhesive electronic patch has excellent adhesion to various surfaces such as silicone wafer (max. 4.06 N/cm²) and skin replica surface (max. 1.84 N/cm²) in dry and wet conditions. The high skin-adhesive electronic patch made of a polymer composite material based on a polymer matrix and carbon particles can reliably detect electrocardiogram (ECG) in dry and humid environments. The proposed electronic patch presents potential applications for wearable and skin-attachable electronic devices for detecting various biosignals.

• Science of Emotion and Sensibility
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• v.10 no.2
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• pp.273-280
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• 2007

The study is to examine the psychophysiological responses evoked by negative emotions(fear and disgust) in children. 47 children(11-13 years old, 23 boys) participated in the study. While the children were experiencing fear or disgust emotion induced by audio-visual film clips, ECG, EDA, PPG and SKT are measured. Emotion assessment scale was used to confirm that emotions elicited by the film clips were significantly noticeable, which was measured self-report. The results turned out to be 100% and 89.4% of appropriate for fear and disgust emotions, respectively. Emotional intensity the children had experienced was rated as 4.05, 4.07 on 1-5 scale based on effectiveness of measurement of fear and disgust emotion. ANS reponses by fear and disgust were significantly between the resting state and emotional state induced. The result obtained from the fear emotion showed significant increases in SCL, NSCR, HR, RSA, RESP and HF. There was a significant difference in SCL and NSCR between the two emotions.

• Science of Emotion and Sensibility
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• v.22 no.1
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• pp.45-54
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• 2019

Empathy has been observed to be pivotal in enhancing both social relations and the efficiency of task performance. Empathetic interaction has been shown to begin with individuals mirroring each other's facial expressions, vocal tone, actions, and so on. The internal responses of the cardiovascular activity of people engaged in empathetic interaction are also known to be synchronized. This study attempted to objectively and quantitatively define the rules of empathy with regard to the synchronization of cardiac rhythm between persons. Seventy-four subjects participated in the investigation and were paired to imitate the facial expressions of their partner. An electrocardiogram (ECG) measurement was taken as the participants conducted the task. Quantitative indicators were extracted from the heart rhythm pattern (HRP) and the heart rhythm coherence (HRC) to determine the difference of synchronization of heart rhythms between two individuals as they pertained to empathy. Statistical significance was confirmed by an independent sample t-test. The HRP and HRC correlation(r) between persons increased significantly with empathy in comparison to an interaction that was not empathetic. A difference of the standard deviation of NN intervals (SDNN) and the dominant peak frequency decreased. Therefore, significant parameters to evaluate empathy have been proposed through a step-wise discrimination analysis. Empathic interactions may thus be managed and monitored for high quality social interaction and communication.

• Science of Emotion and Sensibility
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• v.10 no.3
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• pp.471-480
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• 2007

Negative emotions play an important function as to human's existence. In this research, we employed the audio-visual film clips to induce negative emotions and examined the classified responses in the autonomic nervous system(ANS) due to each negative emotion.30 adults(22.6 years $old{\pm}1.24$, 15 males and 15 females) took part in this experiment. Through the preliminary experiment, 2 minutes film's stimuli were selected as the emotion-induced stimuli. During the period when participants were viewing and listening to the selected movie, EDA and ECG were examined as soon as one stimulus was displayed, participants were tested by completing the psychological appraisals of their experienced emotion due to each emotional stimulus. With regard to the result of analyzing the psychological responses, each negative emotion appropriately and effectively induced its target emotion. While concerning the result of analyzing ANS responses, each negative emotion induced its respective activation in ANS. What is more, compared with other types of negative emotional stimuli, the scaring stimulus induced higher activation of the sympathetic nervour system(SNS) as to the indexes in EDh and ECG. This research made segmentation of ANS responses to each negative emotion, which has its significance.

• Science of Emotion and Sensibility
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• v.13 no.1
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• pp.61-68
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• 2010

The objective of this study was to test the estimation possibility of driver's stress degrees with the HRV analysis. For this, first, HRV analysis was applied to the 5 driver's ECG signals which were acquired in 7 different stress situations. From this, the facts that HRV trend was different from that in long-distance driving and 6 parameters - meanRR, sdRR, HF, LF/HF, LFnorm, HFnorm were useful for the stress estimation in stress varying driving situation. Next, we designed 5 personalized linear regression models in which 6 HRV parameters were input and the outcomes were 7 different stress degrees. Finally, we tested each model for 5min-long 16 segments individually. Consequently, the models could not hit the stress degrees exactly in some segments but the correlation coefficients between original stress pattern and estimated stress pattern during entire driving showed reasonably high.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.2
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• pp.450-460
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• 2017

T wave is cardiac parameters that represent ventricular repolarization, it is very important to diagnose arrhythmia. Several methods for detecting T wave have been proposed, such as frequency analysis and non-linear approach. However, detection accuracy is at the lower level. This is because of the overlap of the P wave and T wave depending on the heart condition. We propose T wave detection algorithm based on target area extraction through QRS cancellation and moving average. For this purpose, we detected Q, R, S wave from noise-free ECG(electrocardiogram) signal through the preprocessing method. And then we extracted P, T target area by applying decision rule for four PAC(premature atrial contraction) pattern another arrhythmia through moving average and detected T wave using RT interval and threshold of RR interval. The performance of T wave detection is evaluated by using 48 record of MIT-BIH arrhythmia database. The achieved scores indicate the average detection rate of 95.32%.

• 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.

• Journal of Biomedical Engineering Research
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• v.16 no.1
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• pp.95-100
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• 1995

In this study, we have evaluated the effect of amplitude and frequency perturbation of EGG signal for single vowels associated with laryngeal pathology. The normal EGG signal was properly characterized by an autoregressive model which has an optimal order of ninth using the parametric method. This can be analyzed by determining the transfer function. Perturbations in the fundamental pitch and in the peak amplitude of EGG signal measured with a four-electrode system using the modulation/demodulation techniques were investigated for the purpose of developing a decision criteria for the laryngeal function analysis. The abnormal EGG signal has nonperiodic and unstable characteristics. It can be discriminated by the calculation of opening and closing time of glottis using the EGG signal. In case of normal and abnormal subjects, m$\pm$0.5*sd was discriminating line for frequency perturbation and m$\pm$2*sd for normal amplitude perturbations, respectively. Also, The normal and abnormal cases of the subjects can be discriminated effectively using the pattern of attractor derived with Hilbert transform of EGG signal.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.8
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• pp.3925-3932
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• 2013

Emotion is closely related to the life of human, so has effect on many parts such as concentration, learning ability, etc. and makes to have different behavior patterns. The purpose of this paper is to extract important features based on physiological signals to recognize negative emotion. In this paper, after acquisition of electrocardiography(ECG), electroencephalography(EEG), skin temperature(SKT) and galvanic skin response(GSR) measurements based on physiological signals, we designed an accurate and fast algorithm using combination of linear discriminant analysis(LDA) and genetic algorithm(GA), then we selected important features. As a result, the accuracy of the algorithm is up to 96.4% and selected features are Mean, root mean square successive difference(RMSSD), NN intervals differing more than 50ms(NN50) of heart rate variability(HRV), ${\sigma}$ and ${\alpha}$ frequency power of EEG from frontal region, ${\alpha}$, ${\beta}$, and ${\gamma}$ frequency power of EEG from central region, and mean and standard deviation of SKT. Therefore, the features play an important role to recognize negative emotion.