https://jneuroengrehab.biomedcentral.com/articles/10.1186/s12984-017-0309-z
- Dylan KobsarEmail authorView ORCID ID profile,
- Sean T. Osis,
- Jeffrey E. Boyd,
- Blayne A. Hettinga and
- Reed Ferber
Journal of NeuroEngineering and Rehabilitation201714:94
© The Author(s). 2017
Received: 7 February 2017
Accepted: 7 September 2017
Published: 12 September 2017
Abstract
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.
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