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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\u2010applicable 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\u2010vs\u2010Asymptomatic and 93.9% for HipOA\u2010vs\u2010Asymptomatic 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\u2010based kinematical data and whether the probabilistic outcome of the logistic regression model can be used in the follow\u2010up of patients with OA.<\/jats:p>","DOI":"10.1002\/jor.25269","type":"journal-article","created":{"date-parts":[[2022,1,19]],"date-time":"2022-01-19T03:09:26Z","timestamp":1642561766000},"page":"2229-2239","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Joint kinematics alone can distinguish hip or knee osteoarthritis patients from asymptomatic controls with high accuracy"],"prefix":"10.1002","volume":"40","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9218-7604","authenticated-orcid":false,"given":"Jill","family":"Emmerzaal","sequence":"first","affiliation":[{"name":"Human Movement Biomechanics Research Group Department of Movement Sciences  KU Leuven Belgium"},{"name":"REVAL 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