@Article{info:doi/10.2196/66123,
author="Naef, Aileen C
and Duarte, Guichande
and Neumann, Saskia
and Shala, Migjen
and Branscheidt, Meret
and Easthope Awai, Chris",
title="Toward Unsupervised Capacity Assessments for Gait in Neurorehabilitation: Validation Study",
journal="J Med Internet Res",
year="2025",
month="Mar",
day="26",
volume="27",
pages="e66123",
keywords="gait analysis; gait rehabilitation; 10-meter walk test; stroke; unsupervised assessments; supervised assessments; sensors; motivation; capacity; monitoring; wearables; stroke survivors; quality of life",
abstract="Background: Gait impairments are common in stroke survivors, negatively impacting their overall quality of life. Therefore, gait rehabilitation is often targeted during in-clinic rehabilitation. While standardized assessments are available for inpatient evaluation, the literature often reports variable results when these assessments are conducted in a home environment. Several factors, such as the presence of an observer, the environment itself, or the technology used, may contribute to these differing results. Therefore, it is relevant to establish unsupervised capacity assessments for both in-clinic use and across the continuum of care. Objective: This study aimed to investigate the effect of supervision on the outcomes of a sensor-based 10-meter walk test conducted in a clinical setting, maintaining a controlled environment and setup. Methods: In total, 21 stroke survivors (10 female, 11 male; age: mean 63.9, SD 15.5 years) were assigned alternately to one of two data collection sequences and tested over 4 consecutive days, alternating between supervised test (ST) and unsupervised test (UST) assessments. For both assessments, participants were required to walk a set distance of 10 meters as fast as possible while data were collected using a single wearable sensor (Physilog 5) attached to each shoe. After each walking assessment, the participants completed the Intrinsic Motivation Inventory. Statistical analyses were conducted to examine the mean speed, stride length, and cadence, across repeated measurements and between assessment conditions. Results: The intraclass correlation coefficient indicated good to excellent reliability for speed (ST: $\kappa$=0.93, P<.001; UST: $\kappa$=0.93, P<.001), stride length (ST: $\kappa$=0.92, P<.001; UST: $\kappa$=0.88, P<.001), and cadence (ST: $\kappa$=0.91, P<.001; UST: $\kappa$=0.95, P<.001) across repeated measurements for both ST and UST assessments. There was no significant effect of testing order (ie, sequence A vs B). Comparing ST and UST, there were no significant differences in speed (t39=--0.735, P=.47, 95{\%} CI 0.06-0.03), stride length (z=0.835, P=.80), or cadence (t39=--0.501, P=.62, 95{\%} CI 3.38-2.04) between the 2 assessments. The overall motivation did not show any significant differences between the ST and UST conditions (P>.05). However, the self-reported perceived competence increased during the unsupervised assessment from the first to the second measurement. Conclusions: Unsupervised gait capacity assessments offer a reliable alternative to supervised assessments in a clinical environment, showing comparable results for gait speed, stride length, and cadence, with no differences in overall motivation between the two. Future work should build upon these findings to extend unsupervised assessment of both capacity and performance in home environments. Such assessments could allow improved and more specific tracking of rehabilitation progress across the continuum of care. ",
issn="1438-8871",
doi="10.2196/66123",
url="https://www.jmir.org/2025/1/e66123",
url="https://doi.org/10.2196/66123"
}