CN 11-5366/S     ISSN 1673-1530
"Landscape Architecture is more than a journal."
WANG Liya, LI Zhe, GAO Ying, ZHANG Qixin. Measurement, Characterization and Empirical Study of Brain Fatigue in Repetitive Landscape Experience: A Case Study of Xiangyang City Wall Park[J]. Landscape Architecture, 2023, 30(S2): 106-112. DOI: 10.12409/j.fjyl.2023.S2.0106.07
Citation: WANG Liya, LI Zhe, GAO Ying, ZHANG Qixin. Measurement, Characterization and Empirical Study of Brain Fatigue in Repetitive Landscape Experience: A Case Study of Xiangyang City Wall Park[J]. Landscape Architecture, 2023, 30(S2): 106-112. DOI: 10.12409/j.fjyl.2023.S2.0106.07

Measurement, Characterization and Empirical Study of Brain Fatigue in Repetitive Landscape Experience: A Case Study of Xiangyang City Wall Park

  • Objective As one of the scientific characterizations of repetitive experience,brain fatigue can provide a professional basis for the objective description and quantitative measurement of the performance and quality of regular experiential landscape. Based on electroencephalogram(EEG) technology, scientific exploration and precise assessment are conducted on the brain fatigue during repetitive landscape experience. This aims to reveal the cognitive pattern and underlying logic of the change in brain fatigue during repetitive landscape experience, thereby promoting landscape renewal design in response to the development demand for enhancing the quality and efficiency of the people's city.Methods This research establishes a research mechanism to explore the correlation between scene and brain fatigue, and constructs a brain fatigue measurement model by integrating EEG sensitivity analysis technology and variance analysis method. Taking the Xiangyang City Wall Park as an example,the research selects universal scene samples, and conducts brain fatigue measurement experiment and EEG data analysis for single-element and multielement scenes in five rounds.Results Based on experimental analysis and mathematical statistics, the repetitive landscape experience measurement model can quantitatively describe the tendency, amplitude, and correlation and significance feature indices of brain fatigue, while reflecting the impact and effect of basic scene composition elements and the combination thereof on brain fatigue.Conclusion The findings can help deepen the research on brain fatigue measurement in repetitive landscape experience, and can also provide EEG theory foundation, experimental optimization approach, and expanded professional technology for landscape experience and its evidence-based research.
  • loading

Catalog

    Turn off MathJax
    Article Contents

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return