Model for Impacts of Urban Water Blue Visual Index and Flow Velocity on Human Brain State and Its Practical Application

This study develops a predictive model to assess the impacts of urban water blue visual index (BVI) and flow velocity on human brain states using EEG and HRV data in virtual reality simulations. By integrating Gaussian process regression (GPR) and artificial neural networks (ANN), the model accurate...

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Bibliographic Details
Published inBuildings (Basel) Vol. 15; no. 3; p. 339
Main Authors Zhang, Yiming, Zhu, Xuezhou, Li, Qingbin
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.02.2025
Subjects
Artificial neural networks
blue visual index
Brain
Brain research
brain state
Cognitive ability
Computer applications
Flow velocity
Gaussian process
Heart rate
Mental health
Neural networks
Physiology
practical application
Prediction models
Regional development
Regression models
Remote sensing
Urban planning
Velocity
Virtual networks
Virtual reality
Visual observation
Water
Well being
British Virgin Islands
China
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Summary:This study develops a predictive model to assess the impacts of urban water blue visual index (BVI) and flow velocity on human brain states using EEG and HRV data in virtual reality simulations. By integrating Gaussian process regression (GPR) and artificial neural networks (ANN), the model accurately captures the relationships between BVI, flow velocities, and brain states, reflecting experimental observations with high precision. Applied across 31 provinces in China, the model effectively predicted regional brain state levels, aligning closely with the birthplace distribution of high-level talents, such as academicians and Changjiang scholars. These results highlight the model’s practical application in optimizing urban water features to enhance mental health, cognitive performance, and societal development.
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ISSN:2075-5309
2075-5309
DOI:10.3390/buildings15030339