Environmental Distress and Physiological Signals: Examination of the Saliency Detection Method
DC Field | Value | Language |
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dc.contributor.author | Kim, Jinwoo | - |
dc.contributor.author | Yadav, Megha | - |
dc.contributor.author | Chaspari, Theodora | - |
dc.contributor.author | Ahn, Changbum R. | - |
dc.date.accessioned | 2023-05-10T02:40:23Z | - |
dc.date.available | 2023-05-10T02:40:23Z | - |
dc.date.created | 2023-05-10 | - |
dc.date.issued | 2020-11 | - |
dc.identifier.issn | 0887-3801 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/87588 | - |
dc.description.abstract | Burgeoning attention has recently been paid to measuring and assessing the effects of urban built environments on pedestrians' physiological signals (e.g., gait patterns, blood volume pulse, and electrodermal activity). Previous studies have attempted to use physiological signals obtained from naturalistic ambulatory settings to assess negative environmental stimuli (e.g., the presence of broken houses, unstable sidewalks, abandoned cars, etc.), but several unanswered questions remain regarding whether physiological signals, which include various confounding factors (e.g., noise, movement artifacts, and individual variability), can capture the impact of negative environmental stimuli on pedestrians. Additionally, our own previous research proposed a saliency detection method to capture the changes in physiological signals caused by negative environmental stimuli. However, the effect of diverse physiological signal patterns on the proposed saliency detection method is still uncertain and needs further analysis (such as analysis regarding the sensitivity of initial input data for signal segmentation, the validity of aggregation across all subjects' data, etc.). In this context, this paper aims to (1) examine the direct association between pedestrians' physiological signals and an isolated negative environmental stimulus and (2) test the use of the saliency detection method to crowdsource identification of pedestrians' environmental distress by using data sets from naturalistic ambulatory settings. The experimental and statistical results, attained from physiological signals, present distinct physiological responses to negative environmental stimuli, and the saliency detection method is also effectual in capturing prominent local patterns. We envisage that the outcome of this study will provide opportunities for advancing urban built environment assessment, especially in terms of promoting neighborhood walkability, increasing feelings of comfort and satisfaction in the urban space, and augmenting residents' quality of life. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | ASCE-AMER SOC CIVIL ENGINEERS | - |
dc.relation.isPartOf | JOURNAL OF COMPUTING IN CIVIL ENGINEERING | - |
dc.title | Environmental Distress and Physiological Signals: Examination of the Saliency Detection Method | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.description.journalClass | 1 | - |
dc.identifier.wosid | 000639432500009 | - |
dc.identifier.doi | 10.1061/(ASCE)CP.1943-5487.0000926 | - |
dc.identifier.bibliographicCitation | JOURNAL OF COMPUTING IN CIVIL ENGINEERING, v.34, no.6 | - |
dc.description.isOpenAccess | N | - |
dc.identifier.scopusid | 2-s2.0-85091457333 | - |
dc.citation.title | JOURNAL OF COMPUTING IN CIVIL ENGINEERING | - |
dc.citation.volume | 34 | - |
dc.citation.number | 6 | - |
dc.contributor.affiliatedAuthor | Kim, Jinwoo | - |
dc.type.docType | Article | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Interdisciplinary Applications | - |
dc.relation.journalWebOfScienceCategory | Engineering, Civil | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
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