Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Kobsar, Dylan, Osis, Sean T., Boyd, Jeffrey E., Hettinga, Blayne A., Ferber, Reed
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
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
_version_ 1783263628850364416
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
work_keys_str_mv AT kobsardylan wearablesensorstopredictimprovementfollowinganexerciseinterventioninpatientswithkneeosteoarthritis
AT osisseant wearablesensorstopredictimprovementfollowinganexerciseinterventioninpatientswithkneeosteoarthritis
AT boydjeffreye wearablesensorstopredictimprovementfollowinganexerciseinterventioninpatientswithkneeosteoarthritis
AT hettingablaynea wearablesensorstopredictimprovementfollowinganexerciseinterventioninpatientswithkneeosteoarthritis
AT ferberreed wearablesensorstopredictimprovementfollowinganexerciseinterventioninpatientswithkneeosteoarthritis