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Validity and Reliability of a Smartphone App for Gait and Balance Assessment

Advances in technology provide an opportunity to enhance the accuracy of gait and balance assessment, improving the diagnosis and rehabilitation processes for people with acute or chronic health conditions. This study investigated the validity and reliability of a smartphone-based application to mea...

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Autores principales: Rashid, Usman, Barbado, David, Olsen, Sharon, Alder, Gemma, Elvira, Jose L. L., Lord, Sue, Niazi, Imran Khan, Taylor, Denise
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8747233/
https://www.ncbi.nlm.nih.gov/pubmed/35009667
http://dx.doi.org/10.3390/s22010124
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author Rashid, Usman
Barbado, David
Olsen, Sharon
Alder, Gemma
Elvira, Jose L. L.
Lord, Sue
Niazi, Imran Khan
Taylor, Denise
author_facet Rashid, Usman
Barbado, David
Olsen, Sharon
Alder, Gemma
Elvira, Jose L. L.
Lord, Sue
Niazi, Imran Khan
Taylor, Denise
author_sort Rashid, Usman
collection PubMed
description Advances in technology provide an opportunity to enhance the accuracy of gait and balance assessment, improving the diagnosis and rehabilitation processes for people with acute or chronic health conditions. This study investigated the validity and reliability of a smartphone-based application to measure postural stability and spatiotemporal aspects of gait during four static balance and two gait tasks. Thirty healthy participants (aged 20–69 years) performed the following tasks: (1) standing on a firm surface with eyes opened, (2) standing on a firm surface with eyes closed, (3) standing on a compliant surface with eyes open, (4) standing on a compliant surface with eyes closed, (5) walking in a straight line, and (6) walking in a straight line while turning their head from side to side. During these tasks, the app quantified the participants’ postural stability and spatiotemporal gait parameters. The concurrent validity of the smartphone app with respect to a 3D motion capture system was evaluated using partial Pearson’s correlations (r(p)) and limits of the agreement (LoA%). The within-session test–retest reliability over three repeated measures was assessed with the intraclass correlation coefficient (ICC) and the standard error of measurement (SEM). One-way repeated measures analyses of variance (ANOVAs) were used to evaluate responsiveness to differences across tasks and repetitions. Periodicity index, step length, step time, and walking speed during the gait tasks and postural stability outcomes during the static tasks showed moderate-to-excellent validity (0.55 ≤ r(p) ≤ 0.98; 3% ≤ LoA% ≤ 12%) and reliability scores (0.52 ≤ ICC ≤ 0.92; 1% ≤ SEM% ≤ 6%) when the repetition effect was removed. Conversely, step variability and asymmetry parameters during both gait tasks generally showed poor validity and reliability except step length asymmetry, which showed moderate reliability (0.53 ≤ ICC ≤ 0.62) in both tasks when the repetition effect was removed. Postural stability and spatiotemporal gait parameters were found responsive (p < 0.05) to differences across tasks and test repetitions. Along with sound clinical judgement, the app can potentially be used in clinical practice to detect gait and balance impairments and track the effectiveness of rehabilitation programs. Further evaluation and refinement of the app in people with significant gait and balance deficits is needed.
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spelling pubmed-87472332022-01-11 Validity and Reliability of a Smartphone App for Gait and Balance Assessment Rashid, Usman Barbado, David Olsen, Sharon Alder, Gemma Elvira, Jose L. L. Lord, Sue Niazi, Imran Khan Taylor, Denise Sensors (Basel) Article Advances in technology provide an opportunity to enhance the accuracy of gait and balance assessment, improving the diagnosis and rehabilitation processes for people with acute or chronic health conditions. This study investigated the validity and reliability of a smartphone-based application to measure postural stability and spatiotemporal aspects of gait during four static balance and two gait tasks. Thirty healthy participants (aged 20–69 years) performed the following tasks: (1) standing on a firm surface with eyes opened, (2) standing on a firm surface with eyes closed, (3) standing on a compliant surface with eyes open, (4) standing on a compliant surface with eyes closed, (5) walking in a straight line, and (6) walking in a straight line while turning their head from side to side. During these tasks, the app quantified the participants’ postural stability and spatiotemporal gait parameters. The concurrent validity of the smartphone app with respect to a 3D motion capture system was evaluated using partial Pearson’s correlations (r(p)) and limits of the agreement (LoA%). The within-session test–retest reliability over three repeated measures was assessed with the intraclass correlation coefficient (ICC) and the standard error of measurement (SEM). One-way repeated measures analyses of variance (ANOVAs) were used to evaluate responsiveness to differences across tasks and repetitions. Periodicity index, step length, step time, and walking speed during the gait tasks and postural stability outcomes during the static tasks showed moderate-to-excellent validity (0.55 ≤ r(p) ≤ 0.98; 3% ≤ LoA% ≤ 12%) and reliability scores (0.52 ≤ ICC ≤ 0.92; 1% ≤ SEM% ≤ 6%) when the repetition effect was removed. Conversely, step variability and asymmetry parameters during both gait tasks generally showed poor validity and reliability except step length asymmetry, which showed moderate reliability (0.53 ≤ ICC ≤ 0.62) in both tasks when the repetition effect was removed. Postural stability and spatiotemporal gait parameters were found responsive (p < 0.05) to differences across tasks and test repetitions. Along with sound clinical judgement, the app can potentially be used in clinical practice to detect gait and balance impairments and track the effectiveness of rehabilitation programs. Further evaluation and refinement of the app in people with significant gait and balance deficits is needed. MDPI 2021-12-25 /pmc/articles/PMC8747233/ /pubmed/35009667 http://dx.doi.org/10.3390/s22010124 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Rashid, Usman
Barbado, David
Olsen, Sharon
Alder, Gemma
Elvira, Jose L. L.
Lord, Sue
Niazi, Imran Khan
Taylor, Denise
Validity and Reliability of a Smartphone App for Gait and Balance Assessment
title Validity and Reliability of a Smartphone App for Gait and Balance Assessment
title_full Validity and Reliability of a Smartphone App for Gait and Balance Assessment
title_fullStr Validity and Reliability of a Smartphone App for Gait and Balance Assessment
title_full_unstemmed Validity and Reliability of a Smartphone App for Gait and Balance Assessment
title_short Validity and Reliability of a Smartphone App for Gait and Balance Assessment
title_sort validity and reliability of a smartphone app for gait and balance assessment
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8747233/
https://www.ncbi.nlm.nih.gov/pubmed/35009667
http://dx.doi.org/10.3390/s22010124
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