• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.1
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• pp.55-63
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• 2003

In this study was proposed that a new estimating method for investigation of contractile state changes which generated from continuous isometric contraction of skeletal muscle. The physiological changes(EMG, ECG) and the psychological changes by CNS(central nervous system) were measured by experiments, while the muscle of subjects contracted continuously with isometric contraction in constant load. The psychological changes were represented as three-step-change named 'fatigue', 'pain' and 'sick(greatly pain)' from oral test, and the method which compared physiological change with psychological change on basis of these three steps was developed. The result of analyzing the physiological signals, EMG and ECG signal changes were observed at the vicinity of judging point in time of psychological changes. Namely, it is supposed that contractile states have three kind of states pattern (stable, fatigue, pain) instead of two states (stable, fatigue).

• Journal of People, Plants, and Environment
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• v.22 no.1
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• pp.109-118
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• 2019

Physical activities in the forest environment stimulate the parasympathetic nervous system of humans and have positive effects on the autonomic nervous system as well as moods and emotions. However, there are almost no studies on the benefits of exercise in the forest environment for patients with myocardial infarction. The aim of this study was to investigate the effects of 15-minute single session walking by myocardial infarction patients in the forest and urban environment on the physiological and psychological states. The heart rate variability was measured in 10 patients with myocardial infarction to assess physiological state after single session walking for 15 minutes in the forest environment and urban environment. In order to evaluate the psychological state, a profile of mood scale (POMS) and semantic differential (SD) questionnaire were used. The results of this study showed that 15-minute single session walking in the forest environment activated the parasympathetic nervous system of adult myocardial infarction patients more than 15 minutes of single session walking in the urban environment, and also made them feel more positive in terms of the POMS and SD. Therefore, this study suggests that even single session walking in the forest environment can positively influence the physiological and psychological states of adult heart disease patients and may also contribute to health care.

• Journal of Environmental Science International
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• v.30 no.1
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• pp.1-10
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• 2021

The purpose of this study is to verify the physiological and psychological benefits of indoor garden to humans and to analyze the comparison according to Type A behavior pattern. The subjects included 18 male university students. Heart rate variation was used as a parameter of physiological assessment, and Semantic Differential (SD), Profile of Mood States-Brief (POMS), and State-Trait Anxiety Inventory (STAI) were used as tools for psychological evaluation. The participants were subjected to a psychological evaluation when they were present in a garden. As a result, the parasympathetic nervous activity was increased in the indoor garden. In the analysis of psychological evaluation, indoor garden improved the positive mood states and decreased negative feelings with significant changes only in Type A group. This study supported that indoor garden can have physiological and psychological relaxing effects, which could be more significant in Type A group than Type B.

• Journal of the Ergonomics Society of Korea
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• v.30 no.6
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• pp.705-713
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• 2011

Objective: The aim of this study is to compare results of emotion recognition by several algorithms which classify three different emotional states(happiness, neutral, and surprise) using physiological features. Background: Recent emotion recognition studies have tried to detect human emotion by using physiological signals. It is important for emotion recognition to apply on human-computer interaction system for emotion detection. Method: 217 students participated in this experiment. While three kinds of emotional stimuli were presented to participants, ANS responses(EDA, SKT, ECG, RESP, and PPG) as physiological signals were measured in twice first one for 60 seconds as the baseline and 60 to 90 seconds during emotional states. The obtained signals from the session of the baseline and of the emotional states were equally analyzed for 30 seconds. Participants rated their own feelings to emotional stimuli on emotional assessment scale after presentation of emotional stimuli. The emotion classification was analyzed by Linear Discriminant Analysis(LDA, SPSS 15.0), Support Vector Machine (SVM), and Multilayer perceptron(MLP) using difference value which subtracts baseline from emotional state. Results: The emotional stimuli had 96% validity and 5.8 point efficiency on average. There were significant differences of ANS responses among three emotions by statistical analysis. The result of LDA showed that an accuracy of classification in three different emotions was 83.4%. And an accuracy of three emotions classification by SVM was 75.5% and 55.6% by MLP. Conclusion: This study confirmed that the three emotions can be better classified by LDA using various physiological features than SVM and MLP. Further study may need to get this result to get more stability and reliability, as comparing with the accuracy of emotions classification by using other algorithms. Application: This could help get better chances to recognize various human emotions by using physiological signals as well as be applied on human-computer interaction system for recognizing human emotions.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.6
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• pp.513-519
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• 2013

The current vision-based approaches for emotion recognition, such as facial expression analysis, have many technical limitations in real circumstances, and are not suitable for applications that use them solely in practical environments. In this paper, we propose an approach for emotion recognition by combining extrinsic representations and intrinsic activities among the natural responses of humans which are given specific imuli for inducing emotional states. The intrinsic activities can be used to compensate the uncertainty of extrinsic representations of emotional states. This combination is done by using PRMs (Probabilistic Relational Models) which are extent version of bayesian networks and are learned by greedy-search algorithms and expectation-maximization algorithms. Previous research of facial expression-related extrinsic emotion features and physiological signal-based intrinsic emotion features are combined into the attributes of the PRMs in the emotion recognition domain. The maximum likelihood estimation with the given dependency structure and estimated parameter set is used to classify the label of the target emotional states.

• Journal of Environmental Science International
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• v.25 no.9
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• pp.1213-1222
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• 2016

Given the growing attention to nature and health in modern society, this study considered the role of a waterscape facility as a key element in a landscape's influence on users' physiological and psychological responses. The subjects were 28 university students, and the collected data included systolic and diastolic blood pressure, salivary amylase concentration, semantic differential (SD) scales, and profile of mood states (POMS). As compared to a space without any waterscape element (Type G), relaxation in a space with a waterscape element (Type W) was found to significantly reduce of systolic and diastolic blood pressure and salivary amylase concentration. The SD scale and POMS findings showed that Type W evoked active, bright, dynamic, free, vital, interesting, and cheerful images and improved mood states by enhancing vigor while inhibiting depressive feelings. These findings indicate waterscape facilities can improves users' mood states and may enhance their health.

• Journal of the Ergonomics Society of Korea
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• v.31 no.2
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• pp.271-279
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• 2012

Objective: This study classified three different emotional states(boredom, pain, and surprise) using physiological signals. Background: Emotion recognition studies have tried to recognize human emotion by using physiological signals. It is important for emotion recognition to apply on human-computer interaction system for emotion detection. Method: 122 college students participated in this experiment. Three different emotional stimuli were presented to participants and physiological signals, i.e., EDA(Electrodermal Activity), SKT(Skin Temperature), PPG(Photoplethysmogram), and ECG (Electrocardiogram) were measured for 1 minute as baseline and for 1~1.5 minutes during emotional state. The obtained signals were analyzed for 30 seconds from the baseline and the emotional state and 27 features were extracted from these signals. Statistical analysis for emotion classification were done by DFA(discriminant function analysis) (SPSS 15.0) by using the difference values subtracting baseline values from the emotional state. Results: The result showed that physiological responses during emotional states were significantly differed as compared to during baseline. Also, an accuracy rate of emotion classification was 84.7%. Conclusion: Our study have identified that emotions were classified by various physiological signals. However, future study is needed to obtain additional signals from other modalities such as facial expression, face temperature, or voice to improve classification rate and to examine the stability and reliability of this result compare with accuracy of emotion classification using other algorithms. Application: This could help emotion recognition studies lead to better chance to recognize various human emotions by using physiological signals as well as is able to be applied on human-computer interaction system for emotion recognition. Also, it can be useful in developing an emotion theory, or profiling emotion-specific physiological responses as well as establishing the basis for emotion recognition system in human-computer interaction.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1245-1246
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• 2022

Walkability is an indicator of how much pedestrians are willing to walk and how well a walking environment is created. As walking can promote pedestrians' mental and physical health, there has been increasing focus on improving walkability in different ways. Thus, plenty of research has been undertaken to measure walkability. When measuring walkability, there are many objective and subjective variables. Subjective variables include a feeling of safety, pleasure, or comfort, which can significantly affect perceived walkability. However, these subjective factors are difficult to measure by making the walkability index more reliant on objective and physical factors. Because many subjective variables are associated with human emotional states, understanding pedestrians' emotional states provides an opportunity to measure the subjective walkability variables more quantitatively. Pedestrians' emotions can be examined through surveys, but there are social and economic difficulties involved when conducting surveys. Recently, an increasing number of studies have employed physiological data to measure pedestrians' stress responses when navigating unpleasant environmental barriers on their walking paths. However, studies investigating the emotional states of pedestrians in the walking environment, including assessing their positive emotions felt, such as pleasure, have rarely been conducted. Using wearable devices, this study examined the various emotional states of pedestrians affected by the walking environment. Specifically, this study aimed to demonstrate the feasibility of monitoring biometric data, such as electrodermal activity (EDA) and heart rate variability (HRV), using wearable devices as an indicator of pedestrians' emotional states-both pleasant-unpleasant and aroused-relaxed states. To this end, various walking environments with different characteristics were set up to collect and analyze the pedestrians' biometric data. Subsequently, the subjects wearing the wearable devices were allowed to walk on the experimental paths as usual. After the experiment, the valence (i.e., pleasant or unpleasant) and arousal (i.e., activated or relaxed) scale of the pedestrians was identified through a bipolar dimension survey. The survey results were compared with many potentially relevant EDA and HRV signal features. The research results revealed the potential for physiological responses to indicate the pedestrians' emotional states, but further investigation is warranted. The research results were expected to provide a method to measure the subjective factors of walkability by measuring emotions and monitoring pedestrians' positive or negative feelings when walking to improve the walking environment. However, due to the lack of samples and other internal and external factors influencing emotions (which need to be studied further), it cannot be comprehensively concluded that the pedestrians' emotional states were affected by the walking environment.

• Journal of Korean Academy of Nursing
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• v.30 no.1
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• pp.171-182
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• 2000

This study was performed to investigate the effect of kangaroo care on body weight, physiological responses and behavioral states in premature infants. The subjects were 32 premature infants, fifteen for the kangaroo care group and seventeen for the control group, who hospitalized in a neonatal intensive care unit at a university-affiliated hospital. The kangaroo care was applied 8 times during the twenty five days with 40 minutes for each session. The kangaroo care provides the skin-to-skin contact during which a premature infant wearing a diaper and a hat is placed on its mother's chest. As for the measures, body weight was measured everyday. The levels of epinephrine, norepinephrine and 17-OHCS were measured twice, before beginning the first intervention and after finishing the last intervention. While each session of the care is undergoing, such physiological responses were measured periodically as heart rate, respiration rate, oxygen saturation, core temperature and skin temperature. The results were as follows : 1. The weight gain was significantly greater in the kangaroo care group than that in the control group during the period of performing the kangaroo care. 2. No significant difference was revealed between the two groups in heart rate, respiration rate, oxygen saturation and core temperature. The kangaroo care group also showed significant increases in the skin temperature. 3. The differences in the levels of epinephrine, norepinephrine and 17-OHCS were not significant between the kangaroo care and the control groups. The level of norepinephrine in the two groups was significantly increased over time. 4. Sleep pattern changed significantly in the kangaroo group from a very restless sleep to a very quiet sleep. These results suggest that kangaroo care is an effective nursing intervention for premature infants in gaining weight, achieving stable physiological responses and facilitating a quiet sleep.

• Journal of Korea Technology Innovation Society
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• v.6 no.4
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• pp.411-428
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• 2003

We have examined and analyzed the status of policy, R＆D investments, patents and market share of physiological signal measurement technologies for major countries including Korea, the United States, European Union and Japan. Korea is generally inferior to the others in terms of priority of industrial policy, R＆D investment, number of patents, technological level and world market share. However, Korea could recover competitiveness, with intensive government supports for this technology.