{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T01:06:40Z","timestamp":1779325600218,"version":"3.51.4"},"reference-count":15,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,8,23]],"date-time":"2022-08-23T00:00:00Z","timestamp":1661212800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JSAN"],"abstract":"<jats:p>Knee osteoarthritis is one of the most prevalent chronic diseases. It leads to pain, stiffness, decreased participation in activities of daily living and problems with balance recognition. Force platforms have been one of the tools used to analyse balance in patients. However, identification in early stages and assessing the severity of osteoarthritis using parameters derived from a force plate are yet unexplored to the best of our knowledge. Combining artificial intelligence with medical knowledge can provide a faster and more accurate diagnosis. The aim of our study is to present a novel algorithm to classify the occurrence and severity of knee osteoarthritis based on the parameters derived from a force plate. Forty-four sway movements graphs were measured. The different machine learning algorithms, such as K-Nearest Neighbours, Logistic Regression, Gaussian Naive Bayes, Support Vector Machine, Decision Tree Classifier and Random Forest Classifier, were implemented on the dataset. The proposed method achieves 91% accuracy in detecting sway variation and would help the rehabilitation specialist to objectively identify the patient\u2019s condition in the initial stage and educate the patient about disease progression.<\/jats:p>","DOI":"10.3390\/jsan11030048","type":"journal-article","created":{"date-parts":[[2022,8,24]],"date-time":"2022-08-24T00:22:48Z","timestamp":1661300568000},"page":"48","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Use of Machine Learning for Early Detection of Knee Osteoarthritis and Quantifying Effectiveness of Treatment Using Force Platform"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5801-6185","authenticated-orcid":false,"given":"Ashish John","family":"Prabhakar","sequence":"first","affiliation":[{"name":"Department of Physiotherapy, Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3826-1084","authenticated-orcid":false,"given":"Srikanth","family":"Prabhu","sequence":"additional","affiliation":[{"name":"Department of Computer Science & Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4599-6695","authenticated-orcid":false,"given":"Aayush","family":"Agrawal","sequence":"additional","affiliation":[{"name":"Department of Computer Science & Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Siddhisa","family":"Banerjee","sequence":"additional","affiliation":[{"name":"Department of Information Technology, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abraham M.","family":"Joshua","sequence":"additional","affiliation":[{"name":"Department of Physiotherapy, Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yogeesh Dattakumar","family":"Kamat","sequence":"additional","affiliation":[{"name":"Consultant Knee & Hip Surgeon, KMC Hospital, Ambedkar Circle, Mangaluru, Department of Orthopedics, KMC Mangalore MAHE, Manipal, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2300-101X","authenticated-orcid":false,"given":"Gopal","family":"Nath","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Statistics, Murray State University, Murray, KY, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1114-343X","authenticated-orcid":false,"given":"Saptarshi","family":"Sengupta","sequence":"additional","affiliation":[{"name":"Department of Computer Science, San Jos\u00e9 State University, San Jos\u00e9, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"330","DOI":"10.1016\/j.clinbiomech.2015.02.011","article-title":"Laboratory-based measurement of standing balance in individuals with knee osteoarthritis: A systematic review","volume":"30","author":"Lawson","year":"2015","journal-title":"Clin. 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