Estimating the Gait Speed of Older Adults in Smart Home Environments

Abstract

Mobility is one of the key performance indicators of the health condition of older adults. One important parameter is the gait speed. The mobility is usually assessed under the supervision of a professional by standardised geriatric assessments. Using sensors in smart home environments for continuous monitoring of the gait speed enables physicians to detect early stages of functional decline and to initiate appropriate interventions. This in combination with a floor plan smart home sensors were used to calculate the distance that a person walked in the apartment and the inertial measurement unit data for estimating the actual walking time. A Gaussian kernel density estimator was applied to the computed values and the maximum of the kernel density estimator was considered as the gait speed. The proposed method was evaluated on a real-world dataset and the estimations of the gait speed had a deviation smaller than $$0.10 \, \frac{\mathrm{m}}{\mathrm{s}}$$ 0.10 m s , which is smaller than the minimal clinically important difference, compared to a baseline from a standardised geriatrics assessment.

Automatic Radar-Based Step Length Measurement in the Home for Older Adults Living with Frailty

“…In-home track selection for step length measurement is dependent on three parameters: RDP threshold ε (Section 4.4.2), length of linear track segment D (12), and orientation threshold γ (12). Both ε and γ are set empirically as ε = 0.5 m and γ = 15 • .…”

“…Building upon the insights gleaned from these studies [ 4 , 5 , 6 , 7 , 8 , 9 ], it becomes evident that gait speed and step length play pivotal roles in evaluating frailty, fall risk, and hospitalization risk in older adults. While several methods have been proposed for the continuous monitoring of gait speed in a home environment [ 10 , 11 , 12 , 13 , 14 , 15 ], a significant gap exists concerning step length measurement in the home.…”