Journal of the Architectural Institute of Korea (대한건축학회논문집)

Architectural Institute of Korea (대한건축학회)
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Plans to Construct a VR-EEG Based on the Healing Space Visual Perception Element Optimization Model

VR-EEG 기반 치유공간 시지각 요소 최적화 모델 구축 방안에 관한 연구

  • Kim, Sang-Hee (Dept. of Architectural Engineering, Kyung-pook National University) ;
  • Lee, Kweon-Hyoung (Dept. of Architectural Engineering, Dong-eui University) ;
  • Choo, Seung-Yeon (Dept. of Architectural Engineering, Kyung-pook National University)
  • Received : 2022.03.14
  • Accepted : 2022.05.27
  • Published : 2022.06.30
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Abstract

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.

Keywords

Acknowledgement

이 논문은 2019년 대한민국 교육부와 한국연구재단의 지원을 받아 수행된 연구임(과제번호:2019S1A5B5A07111430).

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