• Journal of the Architectural Institute of Korea Planning & Design
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• v.36 no.4
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• pp.41-49
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• 2020

The purpose of this study was to investigate the use of the Deep Neural Networks(DNN) model to classify user's emotions, in particular Electroencephalography(EEG) toward Virtual-Reality(VR) based 3D design alternatives. Four different types of VR Space were constructed to measure a user's emotion and EEG was measured for each stimulus. In addition to the quantitative evaluation based on EEG data, a questionnaire was conducted to qualitatively check whether there is a difference between VR stimuli. As a result, there is a significant difference between plan types according to the normalized ranking method. Therefore, the value of the subjective questionnaire was used as labeling data and collected EEG data was used for a feature value in the DNN model. Google TensorFlow was used to build and train the model. The accuracy of the developed model was 98.9%, which is higher than in previous studies. This indicates that there is a possibility of VR and Fast Fourier Transform(FFT) processing would affect the accuracy of the model, which means that it is possible to classify a user's emotions toward VR based 3D design alternatives by measuring the EEG with this model.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.107-113
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• 2002

We examined the psychophysiological effects of navigation in a virtual reality (VR). Subjects were exposed to the VR, and required to detect specific objects. Ten electrophysiological signals were recorded before, during, and after navigation in the VR. Six questionnaires on the VR experience were acquired from 45 healthy subjects. There were significant changes between the VR period and the pre-VR control period in several psychophysiological measurements. During the VR period, eye blink, skin conductance level, and alpha frequency of EEG were decreased but gamma wave were increased. Physiological changes associated with cybersickness included increased heart rate, eye blink, skin conductance response, and gamma wave and decreased photoplethysmogram and skin temperature. These results suggest an attentional change during VR navigation and activation of the autonomic nervous system for cybersickness. These findings would enhance our understanding for the psychophysiological changes during VR navigation and cybersickness.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2003.05a
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• pp.78-83
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• 2003

We investigated the physiological patterns of cybersickness in a Virtual Reality(VR). Subject were exposed to the VR for 9.5 min, and required to detect specific virtual objects. Sixteen electrophysiological signals were recorded before, during, and after the virtual navigation. five questionnaires on the VR experience were acquired form 61 healthy subjects. During the virtual navigation, subjects with the high cybersickness susceptibility showed significant physiological changes, which included increased gastric tachyarrhythmia, eyeblink frequency, and EEG delta wave and decreased EEG beta wave. These results suggest that cybersickness may induce or accompany the changes in central nervous system and autonomic nervous system. Also, these results suggest that there may be increased sympathetic activation in autonomic drive for cybersickness.

• Journal of Biomedical Engineering Research
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• v.23 no.2
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• pp.155-163
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• 2002

Attention Deficit Hyperactivity Disorder(ADHD) is a childhood syndrome characterized by short attention span. impulsiveness, and hyperactivity, which often leadㄴ to learning disabilities and various behavioral problems. For the treatment of ADHD, medication and cognitive-behavior therapy is applied in recent yearn Although psycho-stimulant medication has been widely used for many rears. current findings suggest that, as the sole treatment for ADHD, it is an inadequate form of intervention in that parents don't want their child to use drug and the effects are limited to the period in which the drugs are physiologically active. On the other hand, EEG biofeedback treatment studies for ADHD have reported promising results not only in significant reductions in hyperactive, inattentive, and disruptive behaviors, but also improvements in academic performance and IQ scores. However it is too boring for children to finish the whole treatment. The recent increase in computer usage in medicine and rehabilitation has changed the way health care is delivered. Virtual Reality technology provides specific stimuli that can be used in removing distractions and providing environments that get the subjects'attention and increasing their ability to concentrate. VR technology can hold a patient's attention for a longer period of time than other methods can, because VR is immersive, interactive and imaginal. Based on these aspects, we developed Attention Enhancement System (AES) using VR technology, EEG biofeedback, and cognitive training method for enhancing attention and made a clinical trial to people who have attention difficulty and behavioral problems.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.1
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• pp.1-8
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• 2019

Motion sickness is dizziness symptom that occurs when movement detected in the vestibular organ and movement detected visually are collide with each other. When dizziness occurs, user complains of symptoms such as nausea and vomiting, sense of direction abnormality, and fatigue. These causes of dizziness are various and difficult to differentiate and treat the symptoms. Especially, among the types of dizziness VIMS(Visually Induced Motion Sickness) is a problem to solve in developing VR industry. These VIMS analysis can be done through user's vital signs measurement and feature analysis, and EEG characteristics analysis. Therefore, this paper is discuss the minimization of motion sickness caused by visual information based on EEG signal and present research trends related to it.

• Journal of the Korea Computer Graphics Society
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• v.25 no.1
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• pp.23-32
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• 2019

Cybersickness is a symptom of dizziness that occurs while experiencing Virtual Reality (VR) technology and it is presumed to occur mainly by crosstalk between the sensory and cognitive systems. However, since the sensory and cognitive systems cannot be measured objectively, it is difficult to measure cybersickness. Therefore, methodologies for measuring cybersickness have been studied in various ways. Traditional studies have collected answers to questionnaires or analyzed EEG data using machine learning algorithms. However, the system relying on the questionnaires lacks objectivity, and it is difficult to obtain highly accurate measurements with the machine learning algorithms. In this work, we apply Deep Neural Network (DNN) deep learning algorithm for objective cybersickness measurement from EEG data. We also propose a data preprocessing for learning and network structures allowing us to achieve high performance when learning EEG data with the deep learning algorithms. Our approach provides cybersickness measurement with an accuracy up to 98.88%. Besides, we analyze video characteristics where cybersickness occurs by examining the video segments causing cybersickness in the experiments. We discover that cybersickness happens even in unusually persistent changes in the darkness such as the light in a room keeps switching on and off.

• Journal of the HCI Society of Korea
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• v.12 no.4
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• pp.75-80
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• 2017

With the technological development, benefits of Virtual Reality (VR) has become a key of medium in communication research. In addition, explaining human minds with physiological data has become more popular since more accurate and detailed data can be expressed. However, reading brain signals in a virtual environment setting with psychophysiological measures (e.g. EEG and fNIRS) has remained a difficulty for researchers due to a technical constraint. Since a combination of cables for brain measures attached to a head cap obstruct wearing a Head-Mounted Display (HMD) over the cap, measuring brain activities with multiple channels on several areas of the brain is inappropriate in the VR setting. Therefore, we have developed a new brain measurement cap that includes probe connectors and brackets enabling a direct connection to the HMD. We highly expect this method would contribute to cognitive psychology research measuring brain signals with new technology.

• Journal of the Health Care and Life Science
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• v.10 no.2
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• pp.403-411
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• 2022

This study aim to investigate the effects of virtual reality (VR) intervention on stress reduction and relaxation after induced pain through capsaicin skin application for healthy college students. The control group (n=6) was to non-treatment after capsaicin-induced pain, and the experimental group (n=8) was to application VR intervention after capsaicin-induced pain. The effect was measured using VAS, EEG, HRV and as a results, the experimental group was more effective in regressing to baseline value (T_O) than the control group. Therefore, VR intervention is considered to be an effective intervention for stress relief and relaxation.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.12
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• pp.55-64
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• 2019

The purpose of this study was to analyze the affection of plan configuration on human emotion using Virtual Reality. A total of four different plan configuration was selected according to the prior study and built using Virtual Reality. The EEG was measured and then calculated using FFT to measure human emotion in different plan configurations. The measurements were shown to lead there was a significant statistical difference in four types of brainwaves between the plan types(p<0.05). This indicates that there is a possibility of plan configuration may exacerbate psychological disorder among single-person household and suggests that it is possible to counteract those stress among single-person household by changing the plan configuration in the earlier designing stage.

• Korean Journal of Environment and Ecology
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• v.37 no.6
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• pp.473-483
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• 2023

This study was conducted to find out the psychological or physiological healing effects of real natural forests and virtual forest experiences using virtual reality (VR) in an artificially-controlled digital environment. To find out this, 81 healthy undergraduate students from C University were experimented on visual forest stimulation effects in the digital environment from September 5 to December 9 in 2022. The experiment evaluated the psychological and physiological healing effects of visual forest stimulation in the digital forest environment (2D, 3D). The SRI (stress response inventory) experiment for analyzing psychological effect showed statistically significant differences among groups. As for the SRI experiment for measuring psychological stress, except Control group, 2D group in the digital environment showed little difference before and after the experiment. But 3D group showed less stress than before. As a result, it was proved that visual forest stimulation in a forest-based digital environment (2D, 3D) reduces psychological stress significantly. And when analyzing how visual forest stimulation changes EEG (electroencephalogram) in the digital environment, alpha waves (RA), which are activated during relaxation or stabilization, were more active than beta waves (RB), which are activated during tension or awakening. This study is expected to be used to create a psychological and physiological healing environment for those who cannot go to a natural forest due to mobility difficulties by providing them visual forest stimulation experiences in a digital environment. It is also expected that the results will be the basis for forest healing in the digital environment and virtual reality programs will help forest healing activities.