{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,10]],"date-time":"2026-08-10T12:29:03Z","timestamp":1786364943371,"version":"build-2736575974"},"reference-count":189,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2026,8,10]],"date-time":"2026-08-10T00:00:00Z","timestamp":1786320000000},"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>Accurate assessment of joint kinematics is fundamental to biomechanics, rehabilitation, and sports science. Although optical motion capture (OMC) remains the laboratory reference standard for biomechanical validation, its cost, infrastructure requirements, and limited applicability outside controlled environments restrict its broader use. Wearable inertial measurement units (IMUs) and vision-based markerless systems have consequently emerged as complementary alternatives, offering portability, reduced subject preparation, and applicability in ecological settings. Their rapid development, however, has not always been accompanied by an equally rigorous metrological interpretation of performance. This narrative review provides a comparative analysis of IMU- and vision-based approaches for joint kinematics estimation, focusing on biomechanical validation metrics and measurement error. Because the primary literature reports fundamentally different quantities under widely differing experimental conditions, evidence is presented stratified by outcome class, joint, plane of motion, task, and acquisition dimensionality, and values belonging to different outcome classes are not pooled. For sagittal-plane lower-limb angles during level walking in healthy adults, with careful sensor-to-segment calibration and an optoelectronic reference, IMU-based systems show the most consistent performance, with RMSE commonly between 3\u00b0 and 6\u00b0. Vision-based systems achieve comparable accuracy for selected outcomes, particularly spatiotemporal gait parameters and sagittal-plane angles in controlled views, while degrading with occlusion, motion blur, and depth ambiguity. Accuracy is therefore not an intrinsic property of the sensing modality but of the entire measurement chain, including calibration, biomechanical modeling, acquisition geometry, and reporting conventions. Rather than ranking technologies by accuracy alone, the measurement requirements should be derived from the intended application.<\/jats:p>","DOI":"10.3390\/s26165063","type":"journal-article","created":{"date-parts":[[2026,8,10]],"date-time":"2026-08-10T11:38:09Z","timestamp":1786361889000},"page":"5063","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["IMU- and Vision-Based Measurement Techniques for Joint Kinematics: A Narrative Review"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-0287-485X","authenticated-orcid":false,"given":"Luca","family":"Ceriola","sequence":"first","affiliation":[{"name":"Department of Engineering, University Niccol\u00f2 Cusano, 00166 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9030-1998","authenticated-orcid":false,"given":"Luca","family":"Molinaro","sequence":"additional","affiliation":[{"name":"Department of Theoretical and Applied Sciences (DiSTA), eCampus University, 22060 Novedrate, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8997-7605","authenticated-orcid":false,"given":"Juri","family":"Taborri","sequence":"additional","affiliation":[{"name":"Department of Economics Engineering Society and Business Organization (DEIM), University of Tuscia, 01100 Viterbo, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0488-6139","authenticated-orcid":false,"given":"Fabrizio","family":"Patan\u00e8","sequence":"additional","affiliation":[{"name":"Department of Engineering, University Niccol\u00f2 Cusano, 00166 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1064-7962","authenticated-orcid":false,"given":"Ilaria","family":"Mileti","sequence":"additional","affiliation":[{"name":"Department of Engineering, University Niccol\u00f2 Cusano, 00166 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,8,10]]},"reference":[{"key":"ref_1","first-page":"186","article-title":"Human movement analysis using stereophotogrammetry. 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