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Effects of Physical Disorders in Neighborhoods on Pedestrians' Physiological Responses

Cited 9 time in Web of Science Cited 0 time in Scopus
Authors

Bisadi, Mohammad; Kim, Hyunsoo; Ahn, Changbum R.; Nam, Yunwoo

Issue Date
2017
Publisher
AMER SOC CIVIL ENGINEERS
Citation
COMPUTING IN CIVIL ENGINEERING 2017: SMART SAFETY, SUSTAINABILITY, AND RESILIENCE, pp.183-190
Abstract
With the growth of interest in the relationships between neighborhoods and physical activity, public health, and pedestrian safety, various efforts have been made to identify and assess Physical Disorders (PD) (e.g. garbage, litter, broken glass, damaged/disconnected sidewalk/driveway, shrubs on the sidewalk, graffiti, and strong odors) in the neighborhoods. Traditional assessment approaches mainly rely on trained inspectors, which require significant cost and time, and most of these methods lack reliability as they depend on subjective judgment to determine the conditions of the physical environment. In this context, this study explores the potential for using crowd-sourced physiological sensory data from pedestrians (e.g., gait and heart rate data) to identify and assess PDs in the neighborhoods. Though previous studies indicate that humans present diverse physiological responses in their interactions with their environment, there is a lack of empirical research exploring the physiological effects of the neighborhoods on walking activity. In an experiment conducted in a neighborhood of Lincoln, Nebraska, participants were asked to walk on a pre-defined path consisting of sixty measurement units. Three types of data (wearable Inertial Measurement Units (IMU), photoplethysmography (PPG), and Global Positioning System (GPS)) were collected for each participant in order to examine the relationship between their physiological responses and the existing PDs they encounter. The results of this test indicate that the average values of physiological responses of participants in locations with PDs is significantly different than the average values of physiological responses of participants in locations without PDs. The results of this study will help improve the detection of PDs, thereby enhancing walkability.
URI
https://hdl.handle.net/10371/203378
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  • College of Engineering
  • Department of Architecture & Architectural Engineering
Research Area Computing in Construction, Management in Construction

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