基于虚拟现实技术定量评估水域空间尺度对大脑综合状态影响

张一鸣, 朱学舟, 李庆斌

清华大学学报(自然科学版) ›› 2026, Vol. 66 ›› Issue (2) : 299-308.

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清华大学学报(自然科学版) ›› 2026, Vol. 66 ›› Issue (2) : 299-308. DOI: 10.16511/j.cnki.qhdxxb.2025.21.034
水利水电工程

基于虚拟现实技术定量评估水域空间尺度对大脑综合状态影响

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Quantitative assessment of the impact of water space scales on the comprehensive state of the brain using virtual reality

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摘要

蓝色空间与积极的身心健康有关。然而, 以往的研究缺乏对这些关联的定量证据。该文通过引入虚拟现实技术, 构建沉浸式水环境实验平台, 定量评估不同水域空间尺度对人脑综合状态的影响, 突破了传统问卷调查在蓝色空间研究中主观性强、缺乏生理依据的局限。通过采集受试者脑电图(EEG)和心率变异性(HRV) 2项生理指标, 结合Gauss过程回归(GPR)模型, 建立了可视水域面积占比与流速等水域空间特征与大脑状态之间的非线性耦合关系。进一步采用聚类分析识别出人群响应的显著差异性, 并构建基于支持向量机(SVM)的分类预测模型, 实现在个体背景信息基础上对其大脑响应模式的精准预测。结果表明, 水域空间尺度对大脑放松与创造性状态具有非线性影响, 不同个体对尺度变化的生理反应具有显著分型特征。该研究在水环境健康效益的量化评估方法上实现了突破, 为城市水域空间设计提供了科学依据, 推动蓝色空间从普适性营造迈向个性化优化, 展现出重要的技术增量与实践价值。

Abstract

Objective: Blue spaces have been gradually recognized due to their positive impact on human mental and physical well-being. However, existing works have greatly depended on subjective questionnaires and lack objective and quantitative evidence, especially regarding the effects of specific spatial scales of water environments on brain activity. Methods: To address this gap, this study uses virtual reality (VR) technology to construct immersive waterbody environments with systematically varied visual and auditory properties, which enables controlled experimental exposure to different water space scales. A total of 52 healthy participants aged 18-36 from Tsinghua University were involved in experiencing 35 water scenarios characterized by five levels of visible water area (0%, 30%, 50%, 80%, and 100%) and seven flow velocity levels (0-3.0 m/s). During the VR exposure, two neurophysiological indicators—electroencephalogram (EEG) alpha power and heart rate variability (HRV)—were concurrently recorded to reflect the cognitive and autonomic brain states of the participants. EEG alpha activity, which is associated with relaxation and creative ideation, and HRV, which is an index of emotional regulation and adaptive capacity, served as core outcome measures. After signal preprocessing and normalization, Gaussian process regression was adopted to model the nonlinear coupling between water environment features and physiological responses. Results: Results revealed significant interindividual variability in responses to water scale. For the majority of participants (Class I), moderate visible water areas (10%-30%) combined with low flow velocities (0.5-1.5 m/s) exhibited the most favorable neurophysiological responses, with EEG alpha power and HRV values increasing beyond resting baseline levels. However, these values decreased substantially in scenes with excessively large water areas (>50%) or higher flow velocities, which suggests that overstimulation from water features may suppress cognitive readiness and emotional stability. By contrast, a minority group (Class II) displayed the opposite pattern, which exhibited stronger EEG and HRV responses under conditions of larger water areas and either very low or high flow speeds. This divergence emphasizes the important role of individual backgrounds in shaping responses to blue space. Furthermore, a support vector machine classification model was developed based on the demographic and environmental background data of participants (including birthplace precipitation, humidity, and surface water ratio), which accurately predicted individual response categories with an accuracy of 95%. In addition, a single-factor analysis of water sound levels disclosed that moderate auditory stimuli (~30 dB) improved EEG alpha activity even in the absence of visual water elements, which reinforces the cognitive benefits of natural soundscapes and implies potential for non-visual design interventions. Conclusions: Overall, this study constructs a robust experimental and modeling framework to quantify the neurocognitive impact of waterbody scale, which offers new insights into the modulating mechanism of specific aquatic features on brain states in dynamic and individualized ways. The findings show that the restorative and creativity-enhancing effects of blue space are neither universal nor linear but rather depend on environmental parameters and individual characteristics. Thus, these outcomes challenge conventional assumptions and highlight the need for tailored blue space design. The proposed method provides valuable scientific evidence for optimizing urban water landscapes not only for aesthetic or ecological purposes but also as cognitive infrastructures that support mental health, emotional resilience, and innovation across diverse populations and geographic contexts.

关键词

蓝色空间 / 虚拟现实 / 水域空间尺度 / 大脑状态 / 预测分类

Key words

blue space / virtual reality / water space scales / brain state / predictive classification

引用本文

导出引用
张一鸣, 朱学舟, 李庆斌. 基于虚拟现实技术定量评估水域空间尺度对大脑综合状态影响[J]. 清华大学学报(自然科学版). 2026, 66(2): 299-308 https://doi.org/10.16511/j.cnki.qhdxxb.2025.21.034
Yiming ZHANG, Xuezhou ZHU, Qingbin LI. Quantitative assessment of the impact of water space scales on the comprehensive state of the brain using virtual reality[J]. Journal of Tsinghua University(Science and Technology). 2026, 66(2): 299-308 https://doi.org/10.16511/j.cnki.qhdxxb.2025.21.034
中图分类号: TU984.2   

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