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

Wang, Yuting; Xu, Ming

doi:10.3390/ijerph18168522

Cited by 21 publications

(10 citation statements)

References 39 publications

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“…The similarity with the classification of people’s emotions shows that different landscapes do cause subtle changes in people’s emotions. At the same time, it also proves that it is feasible to identify people’s perception of different landscapes through multi-dimensional EEG features [ 60 ]. This result is of great significance for evaluating the impact of landscapes on people, which also has important reference value for the quantification of ecosystem cultural services [ 44 , 61 ].…”

Section: Discussionmentioning

confidence: 99%

Landscape Perception Identification and Classification Based on Electroencephalogram (EEG) Features

Wang

2022

IJERPH

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This paper puts forward a new method of landscape recognition and evaluation by using aerial video and EEG technology. In this study, seven typical landscape types (forest, wetland, grassland, desert, water, farmland, and city) were selected. Different electroencephalogram (EEG) signals were generated through different inner experiences and feelings felt by people watching video stimuli of the different landscape types. The electroencephalogram (EEG) features were extracted to obtain the mean amplitude spectrum (MAS), power spectrum density (PSD), differential entropy (DE), differential asymmetry (DASM), rational asymmetry (RASM), and differential caudality (DCAU) in the five frequency bands of delta, theta, alpha, beta, and gamma. According to electroencephalogram (EEG) features, four classifiers including the back propagation (BP) neural network, k-nearest neighbor classification (KNN), random forest (RF), and support vector machine (SVM) were used to classify the landscape types. The results showed that the support vector machine (SVM) classifier and the random forest (RF) classifier had the highest accuracy of landscape recognition, which reached 98.24% and 96.72%, respectively. Among the six classification features selected, the classification accuracy of MAS, PSD, and DE with frequency domain features were higher than those of the spatial domain features of DASM, RASM and DCAU. In different wave bands, the average classification accuracy of all subjects was 98.24% in the gamma band, 94.62% in the beta band, and 97.29% in the total band. This study identifies and classifies landscape perception based on multi-channel EEG signals, which provides a new idea and method for the quantification of human perception.

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Section: Discussionmentioning

confidence: 99%

Landscape Perception Identification and Classification Based on Electroencephalogram (EEG) Features

Wang

2022

IJERPH

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“…Secondly, the Yellow Ginkgo Scenic Forest was used after the T3 stage in the experiment. Some studies have shown that there is significant seasonality in the quantitative value of brain wave data [6].This seasonality can be more pronounced in environments with high-wavelength colors, such as yellow [30], and the brain function of the subjects is more active [31]. This may also explain the differences observed in the three time periods.…”

Section: Time Effect On Physiological Restorative Effectsmentioning

confidence: 97%

“…From a research perspective, in addition to time series (season, day and night), it also includes health feedback under dynamic changes in behavior sequences (behavior patterns, behavior types) and environmental type sequences (buildings, blue spaces, green spaces). Time dynamics research mainly focuses on the significant recovery effects of changes in plant, facility, human elements, or appearance over time on stress [5,6]. For example, Zhou, Y. found that green spaces in summer significantly promote physical activity compared to winter [7].…”

Section: Introductionmentioning

confidence: 99%

“…For example, Zhou, Y. found that green spaces in summer significantly promote physical activity compared to winter [7]. Wang indicated that varying seasons have a significant impact on stress recovery in experiments [6]. This also includes more detailed discussions on differences, such as changes in natural lighting conditions [8], and measurements of greenness values [7].…”

Section: Introductionmentioning

confidence: 99%

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Adequate Green: A Study on the Impact of Continuous Green Landscape, Both Indoors and Outdoors, on the Physiological and Psychological Recovery of Adolescents

Wu,

LI,

Dong

et al. 2024

Preprint

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The benefits of green spaces as a public health resource for people's physical and mental well-being are being supported by a growing body of evidence. While most studies only employ limited-duration testing to examine a specific type of green space, our utilization of these resources is continuous and ever-changing. This study takes a unique approach by embracing a continuous green perspective, integrating the beauty of external forest greenery with the concept of vertical green buildings indoors. Using the Recovery Results Scale (ROS), 78 college students were examined for changes in markers while continuously watching a green landscape under stress, with a focus on exploring the relationship between EEG data and stress recovery. The results indicate that β waves, θ waves, RAB, and ROS indicators have a temporal influence, and the trends of physiological and psychological indicators change over time. The beta wave and reactive oxygen species (ROS) readings increase over time. The θ wave peaks at T2 and then gradually decreases, while RAB also decreases over time. EEG channels in the β wave (FP2 and T4), α wave (FP1, F3, F4), and θ wave (FP1, T5, F3, and T6) exhibit significant variations across three time periods.The research findings provide valuable insights into promoting perceptual recovery among adolescents in a continuous green environment. They encourage natural participation and interaction from a dynamic perspective to activate the green conditions of the temporal main effect. The study offers guidance for urban environmental planning and management to create a healthy environment that fosters positive emotions.

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“…The experiment noted a greater abundance of positive emotions provided by natural environments21. Wang and Xu (2021) employed EEG technology and surveys to assess psychological and physiological responses to seasonal landscapes. The experiment revealed signi cant differences between winter and summer landscapes, with only winter landscapes showing signi cant gender differences.…”

mentioning

confidence: 99%

Are multi-element combinations of natural soundscapes better for psychophysiological restoration than single-element natural soundscapes? --Evidence from a study in Zhangjiajie National Forest Park

Bai,

Zhang

2023

Preprint

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Most of the current soundscape research content is limited to the discussion of the restoration effect of single-element soundscapes, but it is the combination of sounds that is common in outdoor activities, and there is no evidence that the restoration of natural soundscapes is better with multi-element combinations. In this study, the Zhangjiajie National Forest Park in China was used as the research object, and the physiological indices of the subjects were collected through EEG signals, and the POMS short-form psychological scale was used to understand the subjective psychological responses of the subjects to the soundscape. The results showed that (1) The psychophysiological restorative ability of the natural soundscape of the National Forest Park was confirmed, and the subjects' psychological and physiological indices changed significantly and positively after listening to each section of the natural soundscape (p = 0.001). (2) The restorative effect of the multi-natural sound combination was ranked first in the overall ranking of the five natural soundscapes, and the multi-natural sound combination did indeed provide better restorative effects than the single-element sounds. (3) Gender does not usually have a significant effect on the restoration effect, and only Windy Sound among the four single-element nature sound landscapes and one multi-element combination of nature sound landscapes showed a significant gender difference, so in general, the effect of gender on the restoration effect of nature sound landscapes is not significant. In terms of research methodology, this study used cluster analysis to cluster the five types of natural soundscapes according to psychological and physiological recovery ability, and used ridge regression to construct mathematical models of the psychological and physiological recovery of each of the four natural soundscapes. The study of human physiological and psychological recovery from different types of natural soundscapes in China's national forest parks will provide a basis for soundscape planning, design, and policy formulation in national forest parks.

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

Cited by 21 publications

References 39 publications

Landscape Perception Identification and Classification Based on Electroencephalogram (EEG) Features

Landscape Perception Identification and Classification Based on Electroencephalogram (EEG) Features

Adequate Green: A Study on the Impact of Continuous Green Landscape, Both Indoors and Outdoors, on the Physiological and Psychological Recovery of Adolescents

Are multi-element combinations of natural soundscapes better for psychophysiological restoration than single-element natural soundscapes? --Evidence from a study in Zhangjiajie National Forest Park

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