| 논문명 |
VR-EEG 기반 치유공간 시지각 요소 최적화 모델 구축 방안에 관한 연구 / Plans to Construct a VR-EEG Based on the Healing Space Visual Perception Element Optimization Model |
| 저자명 |
김상희(Kim, Sang-Hee) ; 이권형(Lee, Kweon-Hyoung) ; 추승연(Choo, Seung-Yeon) |
| 수록사항 |
대한건축학회논문집, Vol.38 No.6 (2022-06) |
| 주제어 |
VR-EEG; 치유공간; 시지각 요소; 최적화 모델 ; VR-EEG; Healing Space; Visual Perceptual Element; optimization model |
| 요약1 |
본 연구는 몰입형 가상현실로 재현된 치유공간의 시지각 요소 변화에 대한 사용자의 EEG 반응을 분석하였고, 분석 결과를 바탕으로 치유공간에 최적화된 시지각 요소 조합안을 도출할 수 있는 모델을 구축하였다. 연구결과를 통해 EEG 데이터 분석 Framework와 Matrix를 통합한 최적화 모델을 제시하였으며, 이 모델은 치유공간 시지각 요소와 EEG 지표 등을 변화시킬 수 있는 가변적 모델로써 향후 생리반응을 적용한 치유공간 계획에 유용한 도구로 활용될 수 있을 것이다. |
| 요약2 |
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. |
