利用脑电图和虚拟现实技术探索布拉迪斯拉发的恢复性环境:一种神经城市主义方法

Mirame Elsayed, A. Elshater, Dina Shehayeb, M. Finka, Samy Afifi
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引用次数: 0

摘要

目的居住在人口稠密的城市地区有其诱惑力;然而,由于城市环境中固有的持续压力和信息超载,它可能会严重影响身心健康。本研究旨在引入一个神经城市主义框架,以指导城市规划者和设计者对个人对虚拟模拟环境的反应进行定量评估。 设计/方法/途径我们的研究分为两个阶段,在斯洛伐克布拉迪斯拉发随机选择了代表三种城市区域的六个地点:城市空间、城市街道和公共公园。首先,我们进行了一次 Mentimeter 现场投票(对话式调查融合),随后进行了一项由斯洛伐克理工大学志愿者参与的实验。这项实验采用了脑电图(EEG)和虚拟现实耳机,以虚拟方式探索参与者对所选地点的反应。研究结果脑电信号分析表明,在这项研究中所选地点的放松程度存在显著差异。有商业活动的城市街道比公共公园更有效地促进心理健康,这对认为恢复性环境仅限于公共公园的先入之见提出了挑战。原创性/价值研究结果展示了一个可复制的神经城市主义框架,该框架包括三个不同的阶段:植根于神经科学的基于问题的技术、实验设置和可交付成果,以及恢复性环境的识别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exploring the restorative environments in Bratislava using EEG and VR: a neuro-urbanism approach
PurposeResiding in a densely populated urban area possesses its allure; nonetheless, it can significantly impact physical and mental well-being owing to the persistent stress and information overload inherent in urban settings. This study aims to introduce a neuro-urbanism framework that can guide urban planners and designers in quantitatively evaluating individuals' responses to virtual simulated environments.Design/methodology/approachOur study consisted of two phases after randomly selecting six locations representing three types of urban areas in Bratislava, Slovakia: urban spaces, urban streets, and public parks. First, we conducted a Mentimeter live polling (dialogic survey fusion), followed by an experiment involving volunteer participants from the Slovak University of Technology. This experiment employed an electroencephalogram (EEG) with virtual reality headsets to virtually explore participants' responses to the selected locations.FindingsThe EEG signal analysis revealed significant differences in relaxation levels across the selected locations in this study. Urban streets with commercial activities promote mental well-being more effectively than public parks, challenging the preconception that restorative environments are exclusively confined to public parks.Originality/valueThe results demonstrate a replicable neuro-urbanism framework comprising three distinct stages: problem-based technology rooted in neuroscience, experimental setup and deliverables, and identification of restorative environments.
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