The influence of urban visuospatial configuration on older adults’ stress: A wearable physiological-perceived stress sensing and data mining based-approach

Research output: Journal article publicationJournal articleAcademic researchpeer-review

1 Citation (Scopus)

Abstract

Population ageing raises many fundamental questions, including how the urban environment can be configured to promote active ageing. The perceived element for older adults' involvement in the environment differs from the average person. Despite this difference, there is little to no research into understanding how the perceived elements (specifically, the visuospatial configuration) of the environment influence older adults' involvement—most studies focused on younger adults. The focus here is stress, which occurs when environmental demand exceeds a person's capability. As stress impacts a person's involvement in the environment and older adults are more likely to feel stress due to their decline in functional capability, it is important to understand how the visuospatial configuration of urban environment influence stress. Older adults were recruited to participate in an urban environment walk while their physiological responses (Photoplethysmogram) were monitored using wearable sensors. Their perceived stress responses were also collected. Spatial clustering and hot spot analysis were conducted to detect locations with clusters of physiological responses caused by spatial factors. These locations were subsequently labelled as stress or non-stress based on participants' perceived stress. The perceived visual elements of the urban environment were extracted using isovist analysis. Principal component analysis, self-organising map and machine learning algorithms were used to understand the relationship. The results demonstrate that isovist minimum visibility, occlusivity, and isovist area are the most influential determinants of older adults' physiological stress. Older adults prefer urban configurations where they can be seen. This study can be used to inform urban design and planning.

Original languageEnglish
Article number108298
JournalBuilding and Environment
Volume206
DOIs
Publication statusPublished - Dec 2021

Keywords

  • Isovist analysis
  • Machine learning
  • Older adult
  • Person-environment interaction
  • Physiological stress
  • Self-organising map

ASJC Scopus subject areas

  • Environmental Engineering
  • Civil and Structural Engineering
  • Geography, Planning and Development
  • Building and Construction

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