{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T07:49:59Z","timestamp":1767340199322,"version":"build-2065373602"},"reference-count":38,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2024,2,24]],"date-time":"2024-02-24T00:00:00Z","timestamp":1708732800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"European Union\u2019s Horizon 2020","award":["871237","57"],"award-info":[{"award-number":["871237","57"]}]},{"name":"INAIL, Bando Ricerche in Collaborazione (BRiC) 2022 program","award":["871237","57"],"award-info":[{"award-number":["871237","57"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>When performing lifting tasks at work, the Lifting Index (LI) is widely used to prevent work-related low-back disorders, but it presents criticalities pertaining to measurement accuracy and precision. Wearable sensor networks, such as sensorized insoles and inertial measurement units, could improve biomechanical risk assessment by enabling the computation of an adaptive LI (aLI) that changes over time in relation to the actual method of carrying out lifting. This study aims to illustrate the concepts and mathematics underlying aLI computation and compare aLI calculations in real-time using wearable sensors and force platforms with the LI estimated with the standard method used by ergonomists and occupational health and safety technicians. To reach this aim, 10 participants performed six lifting tasks under two risk conditions. The results show us that the aLI value rapidly converges towards the reference value in all tasks, suggesting a promising use of adaptive algorithms and instrumental tools for biomechanical risk assessment.<\/jats:p>","DOI":"10.3390\/s24051474","type":"journal-article","created":{"date-parts":[[2024,2,26]],"date-time":"2024-02-26T03:34:04Z","timestamp":1708918444000},"page":"1474","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Adaptive Lifting Index (aLI) for Real-Time Instrumental Biomechanical Risk Assessment: Concepts, Mathematics, and First Experimental Results"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0197-6166","authenticated-orcid":false,"given":"Alberto","family":"Ranavolo","sequence":"first","affiliation":[{"name":"Department of Occupational and Environmental Medicine, Epidemiology and Hygiene, INAIL, Monte Porzio Catone, 00078 Rome, Italy"}]},{"given":"Arash","family":"Ajoudani","sequence":"additional","affiliation":[{"name":"HRI2 Laboratory, Istituto Italiano di Tecnologia, 16163 Genova, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7654-0025","authenticated-orcid":false,"given":"Giorgia","family":"Chini","sequence":"additional","affiliation":[{"name":"Department of Occupational and Environmental Medicine, Epidemiology and Hygiene, INAIL, Monte Porzio Catone, 00078 Rome, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9458-6844","authenticated-orcid":false,"given":"Marta","family":"Lorenzini","sequence":"additional","affiliation":[{"name":"HRI2 Laboratory, Istituto Italiano di Tecnologia, 16163 Genova, Italy"}]},{"given":"Tiwana","family":"Varrecchia","sequence":"additional","affiliation":[{"name":"Department of Occupational and Environmental Medicine, Epidemiology and Hygiene, INAIL, Monte Porzio Catone, 00078 Rome, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2024,2,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"102897","DOI":"10.1016\/j.apergo.2019.102897","article-title":"Understanding outcome metrics of the revised NIOSH lifting equation","volume":"81","author":"Fox","year":"2019","journal-title":"Appl. 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