{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,8]],"date-time":"2026-02-08T08:38:23Z","timestamp":1770539903141,"version":"3.49.0"},"reference-count":51,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2022,9,4]],"date-time":"2022-09-04T00:00:00Z","timestamp":1662249600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper proposes an innovative methodology for finding how many lifting techniques people with chronic low back pain (CLBP) can demonstrate with camera data collected from 115 participants. The system employs a feature extraction algorithm to calculate the knee, trunk and hip range of motion in the sagittal plane, Ward\u2019s method, a combination of K-means and Ensemble clustering method for classification algorithm, and Bayesian neural network to validate the result of Ward\u2019s method and the combination of K-means and Ensemble clustering method. The classification results and effect size show that Ward clustering is the optimal method where precision and recall percentages of all clusters are above 90, and the overall accuracy of the Bayesian Neural Network is 97.9%. The statistical analysis reported a significant difference in the range of motion of the knee, hip and trunk between each cluster, F (9, 1136) = 195.67, p &lt; 0.0001. The results of this study suggest that there are four different lifting techniques in people with CLBP. Additionally, the results show that even though the clusters demonstrated similar pain levels, one of the clusters, which uses the least amount of trunk and the most knee movement, demonstrates the lowest pain self-efficacy.<\/jats:p>","DOI":"10.3390\/s22176694","type":"journal-article","created":{"date-parts":[[2022,9,8]],"date-time":"2022-09-08T04:18:32Z","timestamp":1662610712000},"page":"6694","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Machine Learning Derived Lifting Techniques and Pain Self-Efficacy in People with Chronic Low Back Pain"],"prefix":"10.3390","volume":"22","author":[{"given":"Trung C.","family":"Phan","sequence":"first","affiliation":[{"name":"School of Science, Computing and Engineering Technologies, Swinburne University of Technology, Hawthorn, VIC 3122, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7877-1679","authenticated-orcid":false,"given":"Adrian","family":"Pranata","sequence":"additional","affiliation":[{"name":"School of Health Sciences, Swinburne University of Technology, Hawthorn, VIC 3122, Australia"},{"name":"School of Kinesiology, Shanghai University of Sports, Shanghai 200438, China"}]},{"given":"Joshua","family":"Farragher","sequence":"additional","affiliation":[{"name":"School of Health Sciences, Swinburne University of Technology, Hawthorn, VIC 3122, Australia"},{"name":"Centre for Health, Exercise and Sports Medicine, Department of Physiotherapy, The University of Melbourne, Melbourne, VIC 3010, Australia"}]},{"given":"Adam","family":"Bryant","sequence":"additional","affiliation":[{"name":"Centre for Health, Exercise and Sports Medicine, Department of Physiotherapy, The University of Melbourne, Melbourne, VIC 3010, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3373-8178","authenticated-orcid":false,"given":"Hung T.","family":"Nguyen","sequence":"additional","affiliation":[{"name":"School of Science, Computing and Engineering Technologies, Swinburne University of Technology, Hawthorn, VIC 3122, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1922-7024","authenticated-orcid":false,"given":"Rifai","family":"Chai","sequence":"additional","affiliation":[{"name":"School of Science, Computing and Engineering Technologies, Swinburne University of Technology, Hawthorn, VIC 3122, Australia"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"299","DOI":"10.21037\/atm.2020.02.175","article-title":"Global low back pain prevalence and years lived with disability from 1990 to 2017: Estimates from the Global Burden of Disease Study 2017","volume":"8","author":"Wu","year":"2020","journal-title":"Ann. 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