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Wearable sensors to predict improvement following an exercise intervention in patients with knee osteoarthritis
BACKGROUND: Muscle strengthening exercises consistently demonstrate improvements in the pain and function of adults with knee osteoarthritis, but individual response rates can vary greatly. Identifying individuals who are more likely to respond is important in developing more efficient rehabilitatio...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5596963/ https://www.ncbi.nlm.nih.gov/pubmed/28899433 http://dx.doi.org/10.1186/s12984-017-0309-z |
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author | Kobsar, Dylan Osis, Sean T. Boyd, Jeffrey E. Hettinga, Blayne A. Ferber, Reed |
author_facet | Kobsar, Dylan Osis, Sean T. Boyd, Jeffrey E. Hettinga, Blayne A. Ferber, Reed |
author_sort | Kobsar, Dylan |
collection | PubMed |
description | BACKGROUND: Muscle strengthening exercises consistently demonstrate improvements in the pain and function of adults with knee osteoarthritis, but individual response rates can vary greatly. Identifying individuals who are more likely to respond is important in developing more efficient rehabilitation programs for knee osteoarthritis. Therefore, the purpose of this study was to determine if pre-intervention multi-sensor accelerometer data (e.g., back, thigh, shank, foot accelerometers) and patient reported outcome measures (e.g., pain, symptoms, function, quality of life) can retrospectively predict post-intervention response to a 6-week hip strengthening exercise intervention in a knee OA cohort. METHODS: Thirty-nine adults with knee osteoarthritis completed a 6-week hip strengthening exercise intervention and were sub-grouped as Non-Responders, Low-Responders, or High-Responders following the intervention based on their change in patient reported outcome measures. Pre-intervention multi-sensor accelerometer data recorded at the back, thigh, shank, and foot and Knee Injury and Osteoarthritis Outcome Score subscale data were used as potential predictors of response in a discriminant analysis of principal components. RESULTS: The thigh was the single best placement for classifying responder sub-groups (74.4%). Overall, the best combination of sensors was the back, thigh, and shank (81.7%), but a simplified two sensor solution using the back and thigh was not significantly different (80.0%; p = 0.27). CONCLUSIONS: While three sensors were best able to identify responders, a simplified two sensor array at the back and thigh may be the most ideal configuration to provide clinicians with an efficient and relatively unobtrusive way to use to optimize treatment. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12984-017-0309-z) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5596963 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-55969632017-09-15 Wearable sensors to predict improvement following an exercise intervention in patients with knee osteoarthritis Kobsar, Dylan Osis, Sean T. Boyd, Jeffrey E. Hettinga, Blayne A. Ferber, Reed J Neuroeng Rehabil Research BACKGROUND: Muscle strengthening exercises consistently demonstrate improvements in the pain and function of adults with knee osteoarthritis, but individual response rates can vary greatly. Identifying individuals who are more likely to respond is important in developing more efficient rehabilitation programs for knee osteoarthritis. Therefore, the purpose of this study was to determine if pre-intervention multi-sensor accelerometer data (e.g., back, thigh, shank, foot accelerometers) and patient reported outcome measures (e.g., pain, symptoms, function, quality of life) can retrospectively predict post-intervention response to a 6-week hip strengthening exercise intervention in a knee OA cohort. METHODS: Thirty-nine adults with knee osteoarthritis completed a 6-week hip strengthening exercise intervention and were sub-grouped as Non-Responders, Low-Responders, or High-Responders following the intervention based on their change in patient reported outcome measures. Pre-intervention multi-sensor accelerometer data recorded at the back, thigh, shank, and foot and Knee Injury and Osteoarthritis Outcome Score subscale data were used as potential predictors of response in a discriminant analysis of principal components. RESULTS: The thigh was the single best placement for classifying responder sub-groups (74.4%). Overall, the best combination of sensors was the back, thigh, and shank (81.7%), but a simplified two sensor solution using the back and thigh was not significantly different (80.0%; p = 0.27). CONCLUSIONS: While three sensors were best able to identify responders, a simplified two sensor array at the back and thigh may be the most ideal configuration to provide clinicians with an efficient and relatively unobtrusive way to use to optimize treatment. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12984-017-0309-z) contains supplementary material, which is available to authorized users. BioMed Central 2017-09-12 /pmc/articles/PMC5596963/ /pubmed/28899433 http://dx.doi.org/10.1186/s12984-017-0309-z Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Kobsar, Dylan Osis, Sean T. Boyd, Jeffrey E. Hettinga, Blayne A. Ferber, Reed Wearable sensors to predict improvement following an exercise intervention in patients with knee osteoarthritis |
title | Wearable sensors to predict improvement following an exercise intervention in patients with knee osteoarthritis |
title_full | Wearable sensors to predict improvement following an exercise intervention in patients with knee osteoarthritis |
title_fullStr | Wearable sensors to predict improvement following an exercise intervention in patients with knee osteoarthritis |
title_full_unstemmed | Wearable sensors to predict improvement following an exercise intervention in patients with knee osteoarthritis |
title_short | Wearable sensors to predict improvement following an exercise intervention in patients with knee osteoarthritis |
title_sort | wearable sensors to predict improvement following an exercise intervention in patients with knee osteoarthritis |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5596963/ https://www.ncbi.nlm.nih.gov/pubmed/28899433 http://dx.doi.org/10.1186/s12984-017-0309-z |
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