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Emotional Responses to the Visual Patterns of Urban Streets: Evidence from Physiological and Subjective Indicators

Author

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  • Zijiao Zhang

    (College of Architecture and Landscape Architecture, Peking University, Beijing 100871, China)

  • Kangfu Zhuo

    (College of Architecture and Landscape Architecture, Peking University, Beijing 100871, China)

  • Wenhan Wei

    (College of Architecture and Landscape Architecture, Peking University, Beijing 100871, China)

  • Fu Li

    (College of Architecture and Landscape Architecture, Peking University, Beijing 100871, China)

  • Jie Yin

    (College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China)

  • Liyan Xu

    (College of Architecture and Landscape Architecture, Peking University, Beijing 100871, China)

Abstract

Despite recent progress in the research of people’s emotional response to the environment, the built—rather than natural—environment’s emotional effects have not yet been thoroughly examined. In response to this knowledge gap, we recruited 26 participants and scrutinized their emotional response to various urban street scenes through an immersive exposure experiment using virtual reality. We utilized new physiological monitoring technologies that enable synchronized observation of the participants’ electroencephalography, electrodermal activity, and heart rate, as well as their subjective indicators. With the newly introduced measurement for the global visual patterns of the built environment, we built statistical models to examine people’s emotional response to the physical element configuration and color composition of street scenes. We found that more diverse and less fragmented scenes inspired positive emotional feelings. We also found (in)consistency among the physiological and subjective indicators, indicating a potentially interesting neural−physiological interpretation for the classic form−function dichotomy in architecture. Besides the practical implications on promoting physical environment design, this study combined objective physiology-monitoring technology and questionnaire-based research techniques to demonstrate a better approach to quantify environment−emotion relationships.

Suggested Citation

  • Zijiao Zhang & Kangfu Zhuo & Wenhan Wei & Fu Li & Jie Yin & Liyan Xu, 2021. "Emotional Responses to the Visual Patterns of Urban Streets: Evidence from Physiological and Subjective Indicators," IJERPH, MDPI, vol. 18(18), pages 1-20, September.
  • Handle: RePEc:gam:jijerp:v:18:y:2021:i:18:p:9677-:d:635206
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    References listed on IDEAS

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    1. Mintai Kim & SangHyun Cheon & Youngeun Kang, 2019. "Use of Electroencephalography (EEG) for the Analysis of Emotional Perception and Fear to Nightscapes," Sustainability, MDPI, vol. 11(1), pages 1-15, January.
    2. Tian Gao & Tian Zhang & Ling Zhu & Yanan Gao & Ling Qiu, 2019. "Exploring Psychophysiological Restoration and Individual Preference in the Different Environments Based on Virtual Reality," IJERPH, MDPI, vol. 16(17), pages 1-14, August.
    3. Philip Salesses & Katja Schechtner & César A Hidalgo, 2013. "The Collaborative Image of The City: Mapping the Inequality of Urban Perception," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-12, July.
    4. Sara Tilley & Chris Neale & Agnès Patuano & Steve Cinderby, 2017. "Older People’s Experiences of Mobility and Mood in an Urban Environment: A Mixed Methods Approach Using Electroencephalography (EEG) and Interviews," IJERPH, MDPI, vol. 14(2), pages 1-20, February.
    5. Yu Ye & Wei Zeng & Qiaomu Shen & Xiaohu Zhang & Yi Lu, 2019. "The visual quality of streets: A human-centred continuous measurement based on machine learning algorithms and street view images," Environment and Planning B, , vol. 46(8), pages 1439-1457, October.
    6. Kuo, F.E. & Faber Taylor, A., 2004. "A potential natural treatment for attention-deficit/hyperactivity disorder: Evidence from a national study," American Journal of Public Health, American Public Health Association, vol. 94(9), pages 1580-1586.
    7. Hadi Zamanifard & Tooran Alizadeh & Caryl Bosman & Eddo Coiacetto, 2019. "Measuring experiential qualities of urban public spaces: users’ perspective," Journal of Urban Design, Taylor & Francis Journals, vol. 24(3), pages 340-364, May.
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    Cited by:

    1. Xueshun Li & Kuntong Huang & Ruinan Zhang & Yang Chen & Yu Dong, 2024. "Visual Perception Optimization of Residential Landscape Spaces in Cold Regions Using Virtual Reality and Machine Learning," Land, MDPI, vol. 13(3), pages 1-33, March.

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