TY - JOUR
T1 - Virtual reality and electroencephalography in architectural design
T2 - A systematic review of empirical studies
AU - Taherysayah, Fatemeh
AU - Malathouni, Christina
AU - Liang, Hai Ning
AU - Westermann, Claudia
N1 - Publisher Copyright:
© 2024 Elsevier Ltd
PY - 2024/5/15
Y1 - 2024/5/15
N2 - Integrating human needs and desires into the design process has long been a crucial aim of design research. Despite advancements, architectural design still often overlooks the diverse dimensions of human experiences. In this context, the recent development of affordable and mobile brain-imaging devices using electroencephalography (EEG) presents an opportunity for a new approach to human-centered architectural design, especially in combination with virtual reality (VR). Despite existing EEG/VR studies in architecture, a comprehensive review of the methods used to translate EEG data into architectural design is lacking. To address this gap, this article presents a systematic review of empirical studies that use EEG in VR and investigate the impact of designed environments on users. Searches in the databases of Scopus, Web of Science and Science Direct resulted in nineteen articles utilizing both EEG and VR and focusing on an architectural perspective. The data analysis was performed qualitatively and is presented in summary-of-findings tables. The results indicate that in all reviewed studies, the framing environments affect specific brain regions and support different physiological, psychological, and cognitive functions. However, reliable conclusions about the impact spectrum of specific environmental features and associated event-related dynamics require further studies. Several gaps and challenges were identified. These include the need to develop comprehensive strategies for synthesizing data from a variety of sources, considering the distinct effects of familiar and new environments, and addressing limitations posed by sample sizes and demographic diversity. Additionally, long-term studies and investigations of the environmental impact on groups remain areas for future research.
AB - Integrating human needs and desires into the design process has long been a crucial aim of design research. Despite advancements, architectural design still often overlooks the diverse dimensions of human experiences. In this context, the recent development of affordable and mobile brain-imaging devices using electroencephalography (EEG) presents an opportunity for a new approach to human-centered architectural design, especially in combination with virtual reality (VR). Despite existing EEG/VR studies in architecture, a comprehensive review of the methods used to translate EEG data into architectural design is lacking. To address this gap, this article presents a systematic review of empirical studies that use EEG in VR and investigate the impact of designed environments on users. Searches in the databases of Scopus, Web of Science and Science Direct resulted in nineteen articles utilizing both EEG and VR and focusing on an architectural perspective. The data analysis was performed qualitatively and is presented in summary-of-findings tables. The results indicate that in all reviewed studies, the framing environments affect specific brain regions and support different physiological, psychological, and cognitive functions. However, reliable conclusions about the impact spectrum of specific environmental features and associated event-related dynamics require further studies. Several gaps and challenges were identified. These include the need to develop comprehensive strategies for synthesizing data from a variety of sources, considering the distinct effects of familiar and new environments, and addressing limitations posed by sample sizes and demographic diversity. Additionally, long-term studies and investigations of the environmental impact on groups remain areas for future research.
KW - Architectural design
KW - Brain imaging
KW - Electroencephalography (EEG)
KW - Machine learning (ML)
KW - Neuroarchitecture
KW - Virtual reality (VR)
KW - Desgn Research
KW - computational design
UR - http://www.scopus.com/inward/record.url?scp=85184005696&partnerID=8YFLogxK
UR - https://authors.elsevier.com/c/1iYEh8MyS9AJi5
U2 - 10.1016/j.jobe.2024.108611
DO - 10.1016/j.jobe.2024.108611
M3 - Review article
AN - SCOPUS:85184005696
SN - 2352-7102
VL - 85
JO - Journal of Building Engineering
JF - Journal of Building Engineering
M1 - 108611
ER -