Facilitators and barriers to real-life mobility in community-dwelling older adults: a narrative review of accelerometry- and global positioning system-based studies

Abstract

Real-life mobility, also called "enacted" mobility, characterizes an individual's activity and participation in the community. Real-life mobility may be facilitated or hindered by a variety of factors, such as physical abilities, cognitive function, psychosocial aspects, and external environment characteristics. Advances in technology have allowed for objective quantification of real-life mobility using wearable sensors, specifically, accelerometry and global positioning systems (GPSs). In this review article, first, we summarize the common mobility measures extracted from accelerometry and GPS. Second, we summarize studies assessing the associations of facilitators and barriers influencing mobility of community-dwelling older adults with mobility measures from sensor technology. We found the most used accelerometry measures focus on the duration and intensity of activity in daily life. Gait quality measures, e.g., cadence, variability, and symmetry, are not usually included. GPS has been used to investigate mobility behavior, such as spatial and temporal measures of path traveled, location nodes traversed, and mode of transportation. Factors of note that facilitate/hinder community mobility were cognition and psychosocial influences. Fewer studies have included the influence of external environments, such as sidewalk quality, and socio-economic status in defining enacted mobility. Increasing our understanding of the facilitators and barriers to enacted mobility can inform wearable technology-enabled interventions targeted at delaying mobility-related disability and improving participation of older adults in the community.

Characteristics and Range of Reviews About Technologies for Aging in Place: Scoping Review of Reviews

“…The first and most common strategy (n=140 reviews) is to refer to technology by using descriptive technical terms such as “sensors” [ 39 - 48 ], “artificial intelligence” [ 49 - 52 ], “GPS” [ 53 - 55 ], or “games” [ 56 - 60 ]. The reviews that used this strategy covered 31 different types of technology exclusively or in combination with each other.…”

WEARDA: Recording Wearable Sensor Data for Human Activity Monitoring

“…The WEARDA software package was initially created for the project "Dementia back at the heart of the community" [2]. 6 While developed for this project, the WEARDA package is designed in a generic manner to allow reuse in other contexts. Depending on the research, the configurations can be set to collect only the necessary data and at a frequency that is useful to the researcher (see Table 2 for an overview).…”

“…In the social sciences (e.g., [6,5]) and health sciences (e.g., [3,8]), consumer smartwatches are often used to measure human activity levels or movement. These smartwatches are typically chosen because of their convenience: they are affordable, small, and have a plethora of sensors built-in.…”

Monitoring mobility in older adults using a Global Positioning System (GPS) smartwatch and accelerometer: A validation study

“…Together, accelerometry and GPS allow for the estimation of the quantity and quality of everyday activities that could help identify early declines in mobility. However, few studies to date have used both technologies simultaneously to comprehensively measure real-life mobility [ 17 ], with much of the work to date requiring participants to carry a second device to collect the GPS information…”

“…Together, accelerometry and GPS allow for the estimation of the quantity and quality of everyday activities that could help identify early declines in mobility. However, few studies to date have used both technologies simultaneously to comprehensively measure real-life mobility [17], with much of the work to date requiring participants to carry a second device to collect the GPS information Of the available devices, wrist-worn activity monitors have become increasingly popular and are well-accepted among older adults, thereby improving study compliance [13,18,19]. These smartwatches have been validated for physical activity energy expenditure and have been successfully used in large cohort studies [13].…”