{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T18:23:19Z","timestamp":1775067799299,"version":"3.50.1"},"reference-count":29,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2023,7,14]],"date-time":"2023-07-14T00:00:00Z","timestamp":1689292800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>An erroneous squat movement might cause different injuries in amateur athletes who are not experts in workout exercises. Even when personal trainers watch out for the athletes\u2019 workout performance, light variations in ankles, knees, and lower back movements might not be recognized. Therefore, we present a smart wearable to alert athletes whether their squats performance is correct. We collect data from people experienced with workout exercises and from learners, supervising personal trainers in annotation of data. Then, we use data preprocessing techniques to reduce noisy samples and train Machine Learning models with a small memory footprint to be exported to microcontrollers to classify squats\u2019 movements. As a result, the k-Nearest Neighbors algorithm with k = 5 achieves an 85% performance and weight of 40 KB of RAM.<\/jats:p>","DOI":"10.3390\/info14070402","type":"journal-article","created":{"date-parts":[[2023,7,14]],"date-time":"2023-07-14T08:40:06Z","timestamp":1689324006000},"page":"402","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Smart Wearable to Prevent Injuries in Amateur Athletes in Squats Exercise by Using Lightweight Machine Learning Model"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6960-1718","authenticated-orcid":false,"given":"Ricardo P.","family":"Arciniega-Rocha","sequence":"first","affiliation":[{"name":"Doctoral School on Safety and Security Sciences, Don\u00e1t B\u00e1nki Faculty of Mechanical and Safety Engineering, \u00d3buda University, 1081 Budapest, Hungary"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0732-0384","authenticated-orcid":false,"given":"Vanessa C.","family":"Erazo-Chamorro","sequence":"additional","affiliation":[{"name":"Doctoral School on Safety and Security Sciences, Don\u00e1t B\u00e1nki Faculty of Mechanical and Safety Engineering, \u00d3buda University, 1081 Budapest, Hungary"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1995-400X","authenticated-orcid":false,"given":"Pa\u00fal D.","family":"Rosero-Montalvo","sequence":"additional","affiliation":[{"name":"Computer Science Department, IT University of Copenhagen, 2300 Copenhagen, Denmark"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3963-2916","authenticated-orcid":false,"given":"Gyula","family":"Szab\u00f3","sequence":"additional","affiliation":[{"name":"Doctoral School on Safety and Security Sciences, Don\u00e1t B\u00e1nki Faculty of Mechanical and Safety Engineering, \u00d3buda University, 1081 Budapest, Hungary"}]}],"member":"1968","published-online":{"date-parts":[[2023,7,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"284","DOI":"10.1519\/JSC.0b013e31818546bb","article-title":"A biomechanical comparison of back and front squats in healthy trained individuals","volume":"23","author":"Gullett","year":"2009","journal-title":"J. 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