Wearable Biosensor and Collective
Sensing–Based Approach for Detecting
Older Adults’ Environmental Barriers
Gaang Lee, S.M.ASCE
1
; Byungjoo Choi
2
; Houtan Jebelli, A.M.ASCE
3
;
Changbum Ryan Ahn, A.M.ASCE
4
; and SangHyun Lee, M.ASCE
5
Abstract: In this rapidly aging society, the mobility of older adults is critical for the prosperity and well-being of communities. Despite such
importance, various types of environmental barriers (e.g., steep slopes and uneven sidewalks) have limited their mobility. Recent wearable
biosensors have shown the potential to less invasively, less laboriously, and continuously detect environmental barriers by measuring stress in
older adults’ daily trips. However, stress alone could not be indicative of environmental barriers because various stress stimuli (e.g., emotions
and physical fatigue) are mixed up in their daily trips. To fill this gap, the authors propose and test a computational approach that spatially
identifies stress resulting from environmental barriers by aggregating multiple people’ s physiological and location data. The proposed ap-
proach measures stress commonly sensed from multiple people in a specific location (collective stress) as an indication of environmental
barriers, applying wearable biosensors, signal processing, and geocoding. To test the feasibility of the proposed approach, collective stress
was compared between locations with and without environmental barriers based on 2 weeks of field data collected from the daily trips of 16
subjects. As a result, the collective stress was statistically higher in the locations with environmental barriers than without. This result shows
that the proposed approach is feasible to compute collective stress measures that are indicative of environmental barriers. This finding con-
tributes to the body of knowledge by confirming the feasibility of a new computational approach that understands locational stress-inducing
factors by spatially aggregating multiple people’ s physiological signals using wearable biosensors, signal processing, and geocoding. Given
the feasibility of the proposed approach to detect environmental barriers, future studies can generate and validate a less invasive, less labo-
rious, and continuous method to detect environmental barriers, which can facilitate mobility improvement. DOI: 10.1061/(ASCE)CP.1943-
5487.0000879. © 2020 American Society of Civil Engineers.
Author keywords: Aging population; Mobility; Environmental barrier; People-centric sensing; Wearable biosensor; Collective sensing;
Electrodermal activity.
Introduction
The US population over the age of 65 has been rapidly increasing
and is expected to reach 20% before 2030 (US Census Bureau
2017). Active aging is closely related not only to an individual’ s
wellbeing but also to societal prosperity (Vodopivec and Dolenc
2008; Walker 2002). Active aging refers to the desire and
ability of older adults to integrate physical and social activities into
their daily routines (Michael et al. 2006). Specifically, mobility, the
ability to achieve access to desired people and places (Metz 2000),
is one of the most important factors for active aging because mobil-
ity significantly affects health and social participation (Glass and
Balfour 2003). For example, previous research efforts have shown
that adults over age 65 with a lower level of mobility are more
likely to have physical and mental health related problems such
as obesity (King et al. 2011), depression (Berke et al. 2007),
and limited interactions with their friends and family members
(Mollenkopf et al. 1997).
Despite mobility’ s central importance, many adults in this age
cohort are suffering from significant declines in mobility (Centers
for Disease Control and Prevention 2018; Guralnik et al. 1993;
Manton 1988). Various mobility indices such as trip frequency, trip
distance, use of public transportation, and unmet travel demands
indicate that an individual’ s mobility rapidly decreases as they get
older (Mattson 2011). As a result, the mobility of older adults is
significantly less than that of young adults (Santos et al. 2011). In
particular, the current built environment furthers aging individuals’
mobility decline by exposing them to various environmental barriers.
An environmental barrier is defined as an environmental feature that
restricts access to or use of the built environment by a person (Sales
et al. 2013). The environmental barrier is a relative concept because it
is the result of interaction between individuals’ capability and exces-
sive environmental demands (Iwarsson et al. 2006; Rantakokko
et al. 2013). When demands of an environmental feature exceed an
1
Ph.D. Candidate, Tishman Construction Management Program, Dept.
of Civil and Environmental Engineering, Univ. of Michigan, 2350 Hayward
St., G.G Brown Bldg., Ann Arbor, MI 48109. Email: gaang@umich.edu
2
Assistant Professor, Dept. of Architectural Engineering, Ajou Univ.,
206, World cup-ro, Suwon-si, Gyeonggi-do 16499, Republic of Korea.
Email: bchoi@ajou.ac.kr
3
Assistant Professor, Dept. of Architectural Engineering, Pennsylvania
State Univ., 104 Engineering Unit A, University Park, PA 16802. Email:
hjebelli@psu.edu
4
Associate Professor, Dept. of Construction Science, Texas A&M
Univ., 3137 TAMU, College Station, TX 77843. ORCID: https://orcid
.org/0000-0002-6733-2216. Email: ryanahn@tamu.edu
5
Professor, Tishman Construction Management Program, Dept. of Civil
and Environmental Engineering, Univ. of Michigan, 2350 Hayward St.,
G.G Brown Bldg., Ann Arbor, MI 48109 (corresponding author). Email:
shdpm@umich.edu
Note. This manuscript was submitted on March 14, 2019; approved on
August 1, 2019; published online on January 7, 2020. Discussion period
open until June 7, 2020; separate discussions must be submitted for in-
dividual papers. This paper is part of the Journal of Computing in Civil
Engineering, © ASCE, ISSN 0887-3801.
© ASCE 04020002-1 J. Comput. Civ. Eng.
J. Comput. Civ. Eng., 2020, 34(2): 04020002
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