{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T14:48:06Z","timestamp":1781016486586,"version":"3.54.1"},"reference-count":26,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2018,1,12]],"date-time":"2018-01-12T00:00:00Z","timestamp":1515715200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"This study has been conducted with the support of the Korea Institute of Industrial Technology as &quot;Development of smart textronic products based on electronic fibers and textiles","award":["KITECH JA-18-0002"],"award-info":[{"award-number":["KITECH JA-18-0002"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Sitting posture monitoring systems (SPMSs) help assess the posture of a seated person in real-time and improve sitting posture. To date, SPMS studies reported have required many sensors mounted on the backrest plate and seat plate of a chair. The present study, therefore, developed a system that measures a total of six sitting postures including the posture that applied a load to the backrest plate, with four load cells mounted only on the seat plate. Various machine learning algorithms were applied to the body weight ratio measured by the developed SPMS to identify the method that most accurately classified the actual sitting posture of the seated person. After classifying the sitting postures using several classifiers, average and maximum classification rates of 97.20% and 97.94%, respectively, were obtained from nine subjects with a support vector machine using the radial basis function kernel; the results obtained by this classifier showed a statistically significant difference from the results of multiple classifications using other classifiers. The proposed SPMS was able to classify six sitting postures including the posture with loading on the backrest and showed the possibility of classifying the sitting posture even though the number of sensors is reduced.<\/jats:p>","DOI":"10.3390\/s18010208","type":"journal-article","created":{"date-parts":[[2018,1,15]],"date-time":"2018-01-15T04:01:55Z","timestamp":1515988915000},"page":"208","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":103,"title":["Sitting Posture Monitoring System Based on a Low-Cost Load Cell Using Machine Learning"],"prefix":"10.3390","volume":"18","author":[{"given":"Jongryun","family":"Roh","sequence":"first","affiliation":[{"name":"Human Convergence Technology Group, Korea Institute of Industrial Technology, 143 Hanggaulro, Ansan 426-910, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hyeong-jun","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Biomedical Science and Engineering (BMSE), Institute of Integrated Technology (IIT), Gwangju Institute of Science and Technology (GIST), Gwangju 61005, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kwang","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Biomedical Science and Engineering (BMSE), Institute of Integrated Technology (IIT), Gwangju Institute of Science and Technology (GIST), Gwangju 61005, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joonho","family":"Hyeong","sequence":"additional","affiliation":[{"name":"Human Convergence Technology Group, Korea Institute of Industrial Technology, 143 Hanggaulro, Ansan 426-910, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sayup","family":"Kim","sequence":"additional","affiliation":[{"name":"Human Convergence Technology Group, Korea Institute of Industrial Technology, 143 Hanggaulro, Ansan 426-910, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7233-5833","authenticated-orcid":false,"given":"Boreom","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Biomedical Science and Engineering (BMSE), Institute of Integrated Technology (IIT), Gwangju Institute of Science and Technology (GIST), Gwangju 61005, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2018,1,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1016\/j.apergo.2007.12.009","article-title":"The effects of an office ergonomics training and chair intervention on worker knowledge, behavior and musculoskeletal risk","volume":"40","author":"Robertson","year":"2009","journal-title":"Appl. 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