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Gait Asymmetry Post-Stroke: Determining Valid and Reliable Methods Using a Single Accelerometer Located on the Trunk

Lookup NU author(s): Dr Christopher Buckley, Michael Dunne-Willows, Professor Lynn Rochester, Dr Silvia Del Din, Sarah Moore

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

Asymmetry is a cardinal symptom of gait post-stroke that is targeted during rehabilitation. Technological developments have allowed accelerometers to be a feasible tool to provide digital gait variables. Many acceleration-derived variables are proposed to measure gait asymmetry. Despite a need for accurate calculation, no consensus exists for what is the most valid and reliable variable. Using an instrumented walkway (GaitRite) as the reference standard, this study compared the validity and reliability of multiple acceleration-derived asymmetry variables. Twenty-five post-stroke participants performed repeated walks over GaitRite whilst wearing a tri-axial accelerometer (Axivity AX3) on their lower back, on two occasions, one week apart. Harmonic ratio, autocorrelation, gait symmetry index, phase plots, acceleration, and jerk root mean square were calculated from the acceleration signals. Test–retest reliability was calculated, and concurrent validity was estimated by comparison with GaitRite. The strongest concurrent validity was obtained from step regularity from the vertical signal, which also recorded excellent test–retest reliability (Spearman’s rank correlation coefficients (rho) = 0.87 and Intraclass correlation coefficient (ICC21) = 0.98, respectively). Future research should test the responsiveness of this and other step asymmetry variables to quantify change during recovery and the effect of rehabilitative interventions for consideration as digital biomarkers to quantify gait asymmetryhttps://doi.org/10.3390/s20010037


Publication metadata

Author(s): Buckley C, Micó-Amigo ME, Dunne-Willows M, Godfrey A, Hickey A, Lord S, Rochester L, Del Din S, Moore SA

Publication type: Article

Publication status: Published

Journal: Sensors

Year: 2020

Volume: 20

Issue: 1

Online publication date: 19/12/2019

Acceptance date: 17/12/2019

Date deposited: 19/12/2019

ISSN (electronic): 1421-8220

Publisher: MDPI

URL: https://doi.org/10.3390/s20010037

DOI: 10.3390/s20010037


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