Radwan, A., Mohammed, M., Mahmoud, H. (2025). Review of Biometric Sensors for Assessing Human Emotional Responses in Virtual Reality Architectural Studies. JES. Journal of Engineering Sciences, 53(3), 288-305. doi: 10.21608/jesaun.2025.354434.1415
Ahmed Radwan; Mohammed Abdel-Sameea Eid Mohammed; Hatem Mahmoud. "Review of Biometric Sensors for Assessing Human Emotional Responses in Virtual Reality Architectural Studies". JES. Journal of Engineering Sciences, 53, 3, 2025, 288-305. doi: 10.21608/jesaun.2025.354434.1415
Radwan, A., Mohammed, M., Mahmoud, H. (2025). 'Review of Biometric Sensors for Assessing Human Emotional Responses in Virtual Reality Architectural Studies', JES. Journal of Engineering Sciences, 53(3), pp. 288-305. doi: 10.21608/jesaun.2025.354434.1415
Radwan, A., Mohammed, M., Mahmoud, H. Review of Biometric Sensors for Assessing Human Emotional Responses in Virtual Reality Architectural Studies. JES. Journal of Engineering Sciences, 2025; 53(3): 288-305. doi: 10.21608/jesaun.2025.354434.1415
Review of Biometric Sensors for Assessing Human Emotional Responses in Virtual Reality Architectural Studies
1Architecture Engineering Dept., Faculty of Engineering, Assiut University, Assiut, Egypt
2Environmental engineering Dept., Egypt-Japan of Science and Technology, Alexanderia, Egypt
Abstract
This paper presents a comprehensive review of biometric sensors used to assess architectural design’s impact on human emotional responses within Virtual Reality (VR) environments. The research integrates a Wireless Body Area Network (WBAN) equipped with Electroencephalogram (EEG), Galvanic Skin Response (GSR), and Photoplethysmogram (PPG) sensors to capture real-time physiological data. These tools measure brain activity, emotional arousal, and cardiovascular responses as participants engage with virtual spaces designed to evoke varying emotional experiences. The findings emphasize the value of biometric tools in providing objective, real-time data that complement traditional subjective evaluations. This review explores the methodologies, advantages, and limitations of EEG, GSR, and PPG, while also addressing their integration within WBANs for synchronized data collection. Key applications include evaluating stress-reducing environments, stimulating spaces, and iterative design feedback. Challenges related to data accuracy, sensor synchronization, and participant variability are discussed alongside potential solutions. By bridging architecture and neuroscience, this paper highlights the potential of biometric tools in designing human-centered environments that promote well-being and enhance user experience.
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