Evaluation of the Validity and Reliability of Connected Insoles to Measure Gait Parameters in Healthy Adults

Abstract

The continuous, accurate and reliable estimation of gait parameters as a measure of mobility is essential to assess the loss of functional capacity related to the progression of disease. Connected insoles are suitable wearable devices which allow precise, continuous, remote and passive gait assessment. The data of 25 healthy volunteers aged 20 to 77 years were analysed in the study to validate gait parameters (stride length, velocity, stance, swing, step and single support durations and cadence) measured by FeetMe® insoles against the GAITRite® mat reference. The mean values and the values of variability were calculated per subject for GAITRite® and insoles. A t-test and Levene’s test were used to compare the gait parameters for means and variances, respectively, obtained for both devices. Additionally, measures of bias, standard deviation of differences, Pearson’s correlation and intraclass correlation were analysed to explore overall agreement between the two devices. No significant differences in mean and variance between the two devices were detected. Pearson’s correlation coefficients of averaged gait estimates were higher than 0.98 and 0.8, respectively, for unipedal and bipedal gait parameters, supporting a high level of agreement between the two devices. The connected insoles are therefore a device equivalent to GAITRite® to estimate the mean and variability of gait parameters.

CCR5‐Δ32polymorphism—a possible protective factor from gait impairment amongst post‐stroke patients

“…CCR5 ‐Δ32 carriers had higher walking speed, and lower stride and swing variability of step length and swing time percent 6 and 12 months after the index event compared with non‐carriers. In fact, CCR5 ‐Δ32 carriers had gait characteristics that were similar to those of elderly healthy subjects [ 26 , 27 , 28 ]. Disease states, including stroke, can affect the variability of the spatiotemporal characteristics of gait [ 4 , 5 , 29 ].…”

Current Technology Developments Can Improve the Quality of Research and Level of Evidence for Rehabilitation Interventions: A Narrative Review

“…In addition, continuous, objective monitoring can reveal disease characteristics not observed in the clinic [ 62 ]. Different sensors can be used to perform this longitudinal data collection and assessment; for example, single- [ 63 ] or multiple-accelerometer/inertial sensor systems [ 64 ], smartwatches [ 65 ], connected insoles [ 66 ], etc., or other types of technologies (e.g., markerless camera, smartmat), can be used to assess and monitor patients at home. Due to their huge availability, another important field of development is the use of smartphone-based digital biomarkers for both assessment and to drive the rehabilitation process [ 67 ].…”

Advancing Digital Medicine with Wearables in the Wild

“…For example, one paper introduces SensorHub [8], which provides a framework for combining data from consumer-grade wearables to enable multimodal observational studies. Other papers present detailed evaluations of connected insoles for quantifying mobility impairment outside of the clinic [9] and a wrist wearable for robust activity recognition and energy expenditure estimation in older adults with high and low physical function [10]. Three others present the evaluation of technologies that enable ambulatory electrocardiogram (ECG) monitoring [11][12][13] for capturing atrial fibrillation and general arrhythmias, and even with three-lead ECG [13], providing the data necessary to inform treatment for these conditions.…”