Joint kinematics alone can distinguish hip or knee osteoarthritis patients from asymptomatic controls with high accuracy

Jill Emmerzaal, Sam Van Rossom, Rob van der Straaten, Arne De Brabandere, Kristoff Corten, Liesbet De Baets, Jesse Davis, Ilse Jonkers, Annick Timmermans, Benedicte Vanwanseele

Onderzoeksoutput: Articlepeer review

1 Citaat (Scopus)


Osteoarthritis (OA) is one of the leading musculoskeletal disabilities worldwide, and several interventions intend to change the gait pattern in OA patients to more healthy patterns. However, an accessible way to follow up the biomechanical changes in a clinical setting is still missing. Therefore, this study aims to evaluate whether we can use biomechanical data collected from a specific activity of daily living to help distinguish hip OA patients from controls and knee OA patients from controls using features that potentially could be measured in a clinical setting. To achieve this goal, we considered three different classes of statistical models with different levels of data complexity. Class 1 is kinematics based only (clinically applicable), class 2 includes joint kinetics (semi-applicable under the condition of access to a force plate or prediction models), and class 3 uses data from advanced musculoskeletal modeling (not clinically applicable). We used a machine learning pipeline to determine which classification model was best. We found 100% classification accuracy for KneeOA-vs-Asymptomatic and 93.9% for HipOA-vs-Asymptomatic using seven features derived from the lumbar spine and hip kinematics collected during ascending stairs. These results indicate that kinematical data alone can distinguish hip or knee OA patients from asymptomatic controls. However, to enable clinical use, we need to validate if the classifier also works with sensor-based kinematical data and whether the probabilistic outcome of the logistic regression model can be used in the follow-up of patients with OA.

Originele taal-2English
Pagina's (van-tot)2229-2239
Aantal pagina's11
TijdschriftJournal of orthopaedic research : official publication of the Orthopaedic Research Society
Nummer van het tijdschrift10
StatusPublished - okt 2022

Bibliografische nota

© 2022 Orthopaedic Research Society. Published by Wiley Periodicals LLC.


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