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Can kinematic variables deduce functional scales among chronic stroke survivors? A proof of concept for inertial sensors

Can kinematic variables deduce functional scales among chronic stroke survivors? A proof of... This study aims to leverage inertial sensors via a walk test to associate kinematic variables with functional assessment results among walkable subjects with chronic stroke.Design/methodology/approachAdults with first-ever stroke survivors were recruited for this study. First, functional assessments were obtained by using Fugl–Meyer Assessment for lower extremity and Berg balance scales. A self-assembled inertial measurement system obtained walking variables from a walk test after being deployed on subjects’ affected limbs and lower back. The average walking speeds, average range of motion in the affected limbs and a new gait symmetry index were computed and correlated with the two functional assessment scales using Spearman’s rank correlation test.FindingsThe average walking speeds were moderately correlated with both Fugl–Meyer assessment scales (γ = 0.62, p < 0.01, n = 23) and Berg balance scales (γ = 0.68, p < 0.01, n = 23). After being modified by the subjects’ height, the new gait symmetry index revealed moderate negative correlations with the Fugl–Meyer assessment scales (γ = −0.51, p < 0.05) and Berg balance scales (γ = −0.52, p < 0.05). The other kinematics failed to correlate well with the functional scales.Practical implicationsNeuromotor and functional assessment results from inertial sensors can facilitate their application in telemonitoring and telerehabilitation.Originality/valueThe average walking speeds and modified gait symmetry index are valuable parameters for inertial sensors in clinical research to deduce neuromotor and functional assessment results. In addition, the lower back is the optimal location for the inertial sensors. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Sensor Review Emerald Publishing

Can kinematic variables deduce functional scales among chronic stroke survivors? A proof of concept for inertial sensors

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References (39)

Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
0260-2288
eISSN
0260-2288
DOI
10.1108/sr-10-2021-0357
Publisher site
See Article on Publisher Site

Abstract

This study aims to leverage inertial sensors via a walk test to associate kinematic variables with functional assessment results among walkable subjects with chronic stroke.Design/methodology/approachAdults with first-ever stroke survivors were recruited for this study. First, functional assessments were obtained by using Fugl–Meyer Assessment for lower extremity and Berg balance scales. A self-assembled inertial measurement system obtained walking variables from a walk test after being deployed on subjects’ affected limbs and lower back. The average walking speeds, average range of motion in the affected limbs and a new gait symmetry index were computed and correlated with the two functional assessment scales using Spearman’s rank correlation test.FindingsThe average walking speeds were moderately correlated with both Fugl–Meyer assessment scales (γ = 0.62, p < 0.01, n = 23) and Berg balance scales (γ = 0.68, p < 0.01, n = 23). After being modified by the subjects’ height, the new gait symmetry index revealed moderate negative correlations with the Fugl–Meyer assessment scales (γ = −0.51, p < 0.05) and Berg balance scales (γ = −0.52, p < 0.05). The other kinematics failed to correlate well with the functional scales.Practical implicationsNeuromotor and functional assessment results from inertial sensors can facilitate their application in telemonitoring and telerehabilitation.Originality/valueThe average walking speeds and modified gait symmetry index are valuable parameters for inertial sensors in clinical research to deduce neuromotor and functional assessment results. In addition, the lower back is the optimal location for the inertial sensors.

Journal

Sensor ReviewEmerald Publishing

Published: May 4, 2022

Keywords: Rehabilitation; Stroke; Inertial sensors; Functional assessment; Walk test

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