• Proceedings of the ESK Conference
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• 1997.04a
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• pp.165-175
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• 1997

Brain potential is described by using Euler Lagrange equation derived from Lagrangian based on SMNI(Statistical Mechanics of Neocortical Interaction). It is assumed that excitatory neuron firing is amplitude-modulated dominantly by the sum of two modes of frequency ${\omega}and 2 {\omega}$ . Time series of this neuron firing is numerically calculated. $I_{L}$related to low frequency distribution of power spectrum, $I_{H}$high frequency, and S(standard deviation) are introduced for the effective extraction of the dynamic property in this simulated brain potential. $I_{L}$,$I_{H}$, and S are obtained from EEG of 4 persons in rest state and are compared with thoretical results. It is of importance in various fields related to human well-being such as comfort-pursued industrial design, psychology, medicine to characterize human emotional states by EEG analysis. The pleasant and unpleasant sensation among various emotional states would be demonstrated to be determined in terms of ${\epsilon}$ and ${\gamma}$ parameters estimated by the simulated $I_{L}$-$I_{H}$-S relations.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.455-458
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• 1997

We are exposed to the various external stimuli input from the environment, which cause emotional changes based on the characteristics of the stimuli. Unfortunately, there are no quantitative results on relationship between human sensibility and the characteristics of physiological signals. The objective of this study was to quantify EEG signals evoked by visual stimulation based on the assumption that the analysis of the variability on the characteristics of the EEG waveform may provide the significant information regarding changes in psychological states of the subject. Seven university students were participated in this study. The experiment was devised with eleven experimental conditions, which are control and ten different types of visual stimulation based on IAPS (International Affective Picture Systems). Wavelet transformation was employed to analyze the EEG signals. Most positive and negative emotional response were compared in pairs. The results showed that the reconstructed signals at the decomposition level revealed the different energy value on the EEG signals. Also, general patterns of EEG signals in rest state compare with positive and negative stimulus were found. This study could be extended to establish an algorithm which distinguishes psychophysiological states of the subjects exposed to the visual stimulation.

• Proceedings of the ESK Conference
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• 1997.10a
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• pp.477-481
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• 1997

We are exposed to the various external stimuli input from the environment, which cause emotional changes based on the characteristics of the stimuli. Unfortunately, there are noquantitative results on relationship between human sensibility and the characteristics of physiological signals. The objective of this study was to quantify EEG signals evoked by visual stimulation based on the assumption that the analysis of the variability on the characteristics of the EEG waveform may provide the significant information regarding changes in psychological states of the subject. Seven university students were participated in this study. The experiment was devised with eleven experimental conditions, which are control and ten different types of visual stimulation based on IAPS(International Affective Picture Systems). Seven subjects were used to obtain EEGs while introducing visual stimulation. Wavelet transformation was employed to analyze the EEG signals. Most Positive and negative emotional response were pairely compared. The results showed that the reconstructed signals at the decomposition level revealed the different energy value on the EEG signals. Also, general patterns of EEG signals in rest state compare with negative and positive stimulus were found. This study could be extended to estabish an algorithm which distinguishes psychophysiological states of the subjects exposed to the visual stimulation.

• ETRI Journal
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• v.44 no.3
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• pp.426-437
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• 2022

To understand the multilateral characteristics of human behavior and physiological markers related to physical, emotional, and environmental states, extensive lifelog data collection in a real-world environment is essential. Here, we propose a data collection method using multimodal mobile sensing and present a long-term dataset from 22 subjects and 616 days of experimental sessions. The dataset contains over 10 000 hours of data, including physiological, data such as photoplethysmography, electrodermal activity, and skin temperature in addition to the multivariate behavioral data. Furthermore, it consists of 10 372 user labels with emotional states and 590 days of sleep quality data. To demonstrate feasibility, human activity recognition was applied on the sensor data using a convolutional neural network-based deep learning model with 92.78% recognition accuracy. From the activity recognition result, we extracted the daily behavior pattern and discovered five representative models by applying spectral clustering. This demonstrates that the dataset contributed toward understanding human behavior using multimodal data accumulated throughout daily lives under natural conditions.

• Journal of English Language & Literature
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• v.58 no.4
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• pp.783-807
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• 2012

This study compares and contrasts Freud's "work of mourning" which mostly appears in his memorable essay "Mourning and Melancholia" and Derrida's theory of mourning which appears in various works such as MEMOIRES for Paul de Man, The Work of Mourning, and others. Freud maintains that the mourner begins to sever emotional ties to the lost object through a labor of memory and eventually completes the work of mourning. It is a "testing of reality" that motivates the mourner to begin to relinquish emotional attachment to the lost object. Derrida, however, challenges Freudian work of mourning by saying that true mourning lies in "respecting the Otherness of the Other." Derrida suggests that Freud's "normal work of mourning" is "unjust betrayal" of the lost object because it "kills" and "devours" the other and thereby makes it part of the self. So he proposes that work of mourning has "to fail in order to succeed": "success fails" and "failure succeeds." There is an enormous, even epistemological, chasm between Freud who states that mourning, "however painful it may be, comes to a spontaneous end" and Derrida who states that "mourning is interminable. Inconsolable. Irreconcilable." and "I mourn Therefore I am." The former is the voice of "testing of reality" and common sense whereas the latter is that of utopian ethical vision. Yet neither seems to get the upper hand and they are kind of forced to maintain an ongoing dialogue with each other, for true mourning seems to lie somewhere in between.

• Journal of Animal Science and Technology
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• v.64 no.3
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• pp.539-563
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• 2022

Nine pig farms were evaluated for the welfare quality in Korea using animal- and environment-based parameters (particularly air quality parameters) during the winter of 2013. The Welfare Quality^® (WQ^®) protocol consists of 12 criteria within four principles. The WQ^® protocol classifies farms into four categories ranging from 'excellent' to 'not classified'. Each of these criteria has specific measures for calculating scores. Calculations for the welfare scores were conducted online using the calculation model in the WQ^® protocol. Environment-based parameters like microclimate (i.e., temperature, relative humidity, air speed, and particulate matter), bacteria (total airborne bacteria, airborne total coliform, and airborne total Escherichia coli), concentration of gases (carbon dioxide, ammonia, and hydrogen sulfide) were measured to investigate the relationship between animal- and environment-based parameters. Correlations between the results of animal- and environment-based parameters were estimated using spearman correlation coefficient. The overall assessments found that five out of nine farms were 'acceptable', and four farms were 'enhanced'; no farm was 'not classified'. The average score for the four principles across the nine farms, in decreasing order, were 'good feeding' (63.13 points) > 'good housing' (59.26 points) > 'good health' (33.47 points) > 'appropriate behaviors' (25.48 points). In the result of the environment aspect, the relative humidity of farms 2 (93.4%), 3 (100%), and 9 (98%) was much higher than the recommended maximum relative humidity of 80%, and four out of the nine farms had ammonia concentrations greater than 40 ppm. Ammonia had negative correlations with 'positive social behaviors' and positive emotional states: content, enjoying, sociable, playful, lively, happy and it had positive correlations with negative emotional states: aimless, distressed. The concentration of carbon dioxide had negative correlations with positive emotional states; calm, sociable, playful, happy and it had a positive correlation with negative emotional state; aimless. Our results indicate that the control of the environment for growing pigs can help improve their welfare, particularly via good air quality (carbon dioxide, ammonia, hydrogen sulfide).

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.133-153
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• 2023

In this paper, we propose a novel approach to investigating brain-signal measurement technology using Electroencephalography (EEG). Traditionally, researchers have combined EEG signals with bio-signals (BSs) to enhance the classification performance of emotional states. Our objective was to explore the synergistic effects of coupling EEG and BSs, and determine whether the combination of EEG+BS improves the classification accuracy of emotional states compared to using EEG alone or combining EEG with pseudo-random signals (PS) generated arbitrarily by random generators. Employing four feature extraction methods, we examined four combinations: EEG alone, EG+BS, EEG+BS+PS, and EEG+PS, utilizing data from two widely-used open datasets. Emotional states (task versus rest states) were classified using Support Vector Machine (SVM) and Long Short-Term Memory (LSTM) classifiers. Our results revealed that when using the highest accuracy SVM-FFT, the average error rates of EEG+BS were 4.7% and 6.5% higher than those of EEG+PS and EEG alone, respectively. We also conducted a thorough analysis of EEG+BS by combining numerous PSs. The error rate of EEG+BS+PS displayed a V-shaped curve, initially decreasing due to the deep double descent phenomenon, followed by an increase attributed to the curse of dimensionality. Consequently, our findings suggest that the combination of EEG+BS may not always yield promising classification performance.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.2
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• pp.150-155
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• 2004

In this paper, an emotion recognition method using speech signal is presented. Six basic human emotions including happiness, sadness, anger, surprise, fear and dislike are investigated. The proposed recognizer have each codebook constructed by using the wavelet transform for the emotional state. Here, we first verify the emotional state at each filterbank and then the final recognition is obtained from a multi-decision method scheme. The database consists of 360 emotional utterances from twenty person who talk a sentence three times for six emotional states. The proposed method showed more 5% improvement of the recognition rate than previous works.

• Journal of The Korean Association For Science Education
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• v.29 no.7
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• pp.783-791
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• 2009

This study was conducted to examine my hypothesis that how teacher's teaching style influences emotional and physiological states of students in the secondary school science classroom. Sixty healthy secondary school students were participated in this study and divided into two groups: manipulation and non-manipulation. Each group underwent different styles of teaching on the scientific hypothesis-generating of com starch experiment. Before and after the class, the strength of emotion was measured using adjective emoticon check lists and they extracted their saliva sample for salivary hormone analysis. Here are the results of this study. First, the intensity of positive emotions in the manipulation group was significantly stronger than the one in the non-manipulation group, whereas the intensity of negative emotions in the non-manipulation group was significantly stronger than the one in the manipulation group. Second, the cortisol level, an indicator of stress, was decreased in the manipulation group whereas it was increased in non-manipulation group. Third, the quality of scientific hypotheses which is generated by students during the class had no connection with types of instructions. Fourth, this study found significantly negative correlation between students' emotional intensity of interest and concentration changes of salivary cortisol. Therefore, the different teaching styles have influence upon students' attitude and interest in science.

• The Journal of Korean Academy of Sensory Integration
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• v.14 no.1
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• pp.50-59
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• 2016

Objective : The goal of this study was to investigate neurological mechanism of emotional regulation and to examine the relationship between the regulation and sensory processing. Subjective : Emotional regulations are mainly processed in limbic system, particularly the basal-lateral group of amygdala takes on a major role in the regulations. The basal-lateral group of amygdala links to thalamus directly and/or indirectly which processes sensory information together. This sensory information connects to orbital and medial prefrontal cortex. Inadequate sensory processing may cause difficulties in emotional regulations and behaviors because of a circuit linking the amygdala, the thalamus, and the orbital and medial prefrontal cortex. These difficulties and impairments has been reported in neurological studies for children with ASD and ADHD. Conclusion : Neurological states are different between the normal children and children with ASD and ADHD and these represent various aspects in sensory processing, emotional regulations and behaviors. Thus, therapists working with children with ASD and ADHD need to understand mechanisms of sensory processing and emotional regulations in order to provide adequate treatments.