Abstract
Research has shown that cognitive and physical functioning of older adults can be reflected in indicators such as walking speed. While changes in cognition, mobility, or health cause changes in gait speed, often gradual variations in walking speed go undetected until severe problems arise. Discrete clinical assessments during clinical consultations often fail to detect changes in day-to-day walking speeds and do not reflect walking speeds in everyday environments, where most of the mobility issues happen. In this paper, we compare four walking speed measurement technologies to a GAITRite mat (gold standard): (1) an ultra wideband radar (covering the band from 3.3 GHz to 10 GHz), (2) a narrow band 24-GHz radar (with a bandwidth of 250 MHz), (3) a perception Neuron Motion Tracking suit, and (4) a thermal camera. Data were collected in parallel using all sensors at the same time for 10 healthy adults for normal and slow walking paces. A comparison of the sensors indicates better performance at lower gait speeds, with offsets (when compared to GAITRite) between 0.1 and 20% for the ultra wideband radar, 1.9 and 17% for the narrowband radar, 0.1 and 38% for the thermal camera, and 1.7 and 38% for the suit. This paper supports the potential of unobtrusive radar-based sensors and thermal camera technologies for ambient autonomous gait speed monitoring for contextual, privacy-preserving monitoring of participants in the community.
Highlights
Previous research has shown gait speed to be a valuable and reliable indicator for the assessment of an individual’s health, mobility and cognitive status [13, 36]
We investigated radarbased walking speed measurement using a 24-GHz radar that achieved an accuracy of 90.5% versus ground truth data from a GAITRite mat at slower walking speeds [5]
Motion Tracking Suit This study investigated the performance of the Perception Neuron Accelerometer Suit (PNAS) [29] in estimating gait speed wirelessly using accelerometers
Summary
Previous research has shown gait (walking) speed to be a valuable and reliable indicator for the assessment of an individual’s health, mobility and cognitive status [13, 36]. People with age-related conditions, such as Alzheimer’s disease and frailty, often present changes in gait speed that are challenging or impossible to monitor during clinical visits [11]. Ubiquitous and unobtrusive technologies that detect changes in gait speed of older adults in clinical (long-term care, hospitals) and non-clinical environments (retirement homes, independent living, etc.) could support detection, evaluation, and monitoring of parameters related to changes in mobility, cognition, and frailty. As shown by previous studies (e.g., [18, 34]), the ability to recognize and handle such conditions is critical for supporting health and quality of life for older adults, especially for those who choose to live independently
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