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자료유형
학술저널
저자정보
김상희 (경북대) 이권형 (동의대) 추승연 (경북대)
저널정보
대한건축학회 대한건축학회논문집 大韓建築學會論文集 第38卷 第6號(通卷 第404號)
발행연도
2022.6
수록면
77 - 88 (12page)

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This study aims to analyze users’ EEG responses of visual perception elements for a reproduced healing space in an immersive virtual reality setting to construct a model that can produce a visual perception element combination scheme. A brain wave measurement experiment was carried out targeting a total of 33 females that measured their changes in arousal and stress levels before and after stimulation using RAB and RHB indices to apply the analysis results for model construction. Statistically, it was verified that changes in visual perception elements such as aspect ratio of space, ceiling height and window area ratio influenced EEG, which is involved in the relaxation-arousal and stress levels of research participants. This implied that reflecting on users’ physiological responses in planning a healing space is essential. Arousal and stress levels of research participants differed in each virtual reality space, applying changes in spatial and visual perception elements. There was a specific part of the brain that responded sensitively, which signified a need for a model that can perform an integrated analysis. Standardization was applied to correct the RAB and RHB indices to extract the arousal and stress level ranges using the deviation percentage of the median values from the corrected indices. An integrated matrix of arousal and stress levels were devised to suggest a standard domain for selecting a combination of visual perception elements optimized for a healing space. Lastly, an optimized model integrating an EEG data analysis framework and matrix were designed. This model is a variable model where the result value can change depending on the healing space visual perception element and EEG indicators. In the future, this research would be useful for planning a healing space that applies physiological responses.

목차

Abstract
1. 서론
2. 이론적 고찰
3. VR-EEG 실험 및 분석방법
4. EEG 반응 분석 및 최적화 모델 구축
5. 결론
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UCI(KEPA) : I410-ECN-0101-2022-540-001328224