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Electroencephalogram Application for the Analysis of Stress Relief in the Seasonal Landscape

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  • Yuting Wang

    (Henan Key Laboratory of Earth System Observation and Modeling, Henan University, Kaifeng 475004, China
    College of Geography and Environmental Science, Henan University, Kaifeng 475004, China
    Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Henan University, Ministry of Education, Kaifeng 475004, China)

  • Ming Xu

    (Henan Key Laboratory of Earth System Observation and Modeling, Henan University, Kaifeng 475004, China
    College of Geography and Environmental Science, Henan University, Kaifeng 475004, China
    Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Henan University, Ministry of Education, Kaifeng 475004, China)

Abstract

This study proposes an integrated approach to assess the psychological and physiological responses of people in natural seasonal landscapes. The questionnaire of restoration outcomes scale (ROS), willingness to visit (WTV), cultural ecosystem services (CES) cognitive classification, and the neuroscientific technique based on electroencephalogram (EEG) measurements were applied. The effects of different landscapes on human perception were studied by comparing the EEG data of different landscape types and different seasons. The coupling relationship between EEG data and stress recovery was also examined. The results showed the following: First, there was a significant difference between the winter landscape and the summer natural landscape. Second, only the winter landscape showed significant gender differences. Third, the values of ROS and WTV in the summer landscape were greater than those in the winter landscape. Fourth, the number of CES in the summer landscape was significantly higher than that in the winter landscape, and the number of CES in water was higher than that in the forest and grassland. Thus, brain wave data and quantified values from questionnaires including ROS, WTV, and CES showed significant seasonality. Therefore, an EEG can be used as a new, more objective tool and method for landscape evaluation and planning in the future.

Suggested Citation

  • Yuting Wang & Ming Xu, 2021. "Electroencephalogram Application for the Analysis of Stress Relief in the Seasonal Landscape," IJERPH, MDPI, vol. 18(16), pages 1-14, August.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:16:p:8522-:d:613125
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    References listed on IDEAS

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    1. Ronghua Wang & Jingwei Zhao, 2020. "Effects of evergreen trees on landscape preference and perceived restorativeness across seasons," Landscape Research, Taylor & Francis Journals, vol. 45(5), pages 649-661, July.
    2. 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.
    3. Eli Paddle & Jason Gilliland, 2016. "Orange Is the New Green: Exploring the Restorative Capacity of Seasonal Foliage in Schoolyard Trees," IJERPH, MDPI, vol. 13(5), pages 1-18, May.
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    Cited by:

    1. Nowak-Olejnik, Agnieszka & Schirpke, Uta & Tappeiner, Ulrike, 2022. "A systematic review on subjective well-being benefits associated with cultural ecosystem services," Ecosystem Services, Elsevier, vol. 57(C).
    2. Yuting Wang & Shujian Wang & Ming Xu, 2022. "Landscape Perception Identification and Classification Based on Electroencephalogram (EEG) Features," IJERPH, MDPI, vol. 19(2), pages 1-12, January.

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