Virtual reality and electroencephalography in architectural design: A systematic review of empirical studies

Fatemeh Taherysayah*, Christina Malathouni, Hai Ning Liang, Claudia Westermann

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

3 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number108611
JournalJournal of Building Engineering
Volume85
Early online date23 Jan 2024
DOIs
Publication statusPublished - 15 May 2024

Keywords

  • Architectural design
  • Brain imaging
  • Electroencephalography (EEG)
  • Machine learning (ML)
  • Neuroarchitecture
  • Virtual reality (VR)
  • Desgn Research
  • computational design

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