{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T15:46:05Z","timestamp":1778168765080,"version":"3.51.4"},"reference-count":39,"publisher":"Cambridge University Press (CUP)","license":[{"start":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T00:00:00Z","timestamp":1751241600000},"content-version":"unspecified","delay-in-days":180,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0"}],"content-domain":{"domain":["cambridge.org"],"crossmark-restriction":true},"short-container-title":["Wearable Technol."],"published-print":{"date-parts":[[2025]]},"abstract":"<jats:title>Abstract<\/jats:title>\n\t  <jats:p>This study addresses challenges in sensor fusion for accurate and robust joint orientation estimation in human movement analysis using wearable inertial measurement units (IMUs). A magnetometer-free refined Kalman filter (KF) approach is presented and validated to address various indoor environmental constraints and challenges posed by human movement. These include variability in motion and dynamics, as well as magnetic disturbances caused by ferromagnetic materials or electronic interferences. Our proposed approach utilizes a Kalman-filter-based framework that analyzes the accelerometer\u2019s alignment with the Earth\u2019s frame to estimate orientation and correct gyroscope readings, eliminating reliance on magnetometer inputs. The algorithm was tested on both controlled robotic movements and real-world upper-limb-motion-monitoring scenarios. First, a comparative analysis was conducted on the double-stage Kalman filter (DSKF) and complementary filter using the collected robot motion encoder data. The results demonstrated superior performance in orientation estimation, particularly in yaw measurements, where the proposed method significantly improved accuracy. It achieved a lower root mean square error (RMSE = <jats:inline-formula>\n\t      <jats:alternatives>\n\t\t<jats:inline-graphic xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" mime-subtype=\"png\" xlink:href=\"S2631717625100030_inline1.png\"\/>\n\t\t<jats:tex-math>$ {2.447}^{\\circ } $<\/jats:tex-math>\n\t      <\/jats:alternatives>\n\t    <\/jats:inline-formula>) and mean absolute error (MAE = <jats:inline-formula>\n\t      <jats:alternatives>\n\t\t<jats:inline-graphic xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" mime-subtype=\"png\" xlink:href=\"S2631717625100030_inline2.png\"\/>\n\t\t<jats:tex-math>$ {2.006}^{\\circ } $<\/jats:tex-math>\n\t      <\/jats:alternatives>\n\t    <\/jats:inline-formula>), outperforming both the DSKF and complementary filter approaches. Additionally, the study\u2019s findings were validated against a standard motion capture system, revealing error metrics within generally acceptable ranges (<jats:inline-formula>\n\t      <jats:alternatives>\n\t\t<jats:inline-graphic xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" mime-subtype=\"png\" xlink:href=\"S2631717625100030_inline3.png\"\/>\n\t\t<jats:tex-math>$ \\le 12.4\\% $<\/jats:tex-math>\n\t      <\/jats:alternatives>\n\t    <\/jats:inline-formula> of the joint range of motion [ROM]) and strong correlation coefficients (<jats:inline-formula>\n\t      <jats:alternatives>\n\t\t<jats:inline-graphic xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" mime-subtype=\"png\" xlink:href=\"S2631717625100030_inline4.png\"\/>\n\t\t<jats:tex-math>$ {r}^2&gt;0.89 $<\/jats:tex-math>\n\t      <\/jats:alternatives>\n\t    <\/jats:inline-formula>). However, some deviations were observed during complex motion cycle intervals, highlighting opportunities for further refinement. These findings suggest that the proposed approach presents a promising alternative for human joint orientation estimation in industrial settings with magnetic distortions.<\/jats:p>","DOI":"10.1017\/wtc.2025.10003","type":"journal-article","created":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T00:45:17Z","timestamp":1751244317000},"update-policy":"https:\/\/doi.org\/10.1017\/policypage","source":"Crossref","is-referenced-by-count":2,"title":["Novel magnetometer-free inertial-measurement-unit-based orientation estimation approach for measuring upper limb kinematics"],"prefix":"10.1017","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1863-7689","authenticated-orcid":false,"given":"Souha","family":"Baklouti","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Taysir","family":"Rezgui","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abdelbadia","family":"Chaker","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anis","family":"Sahbani","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sami","family":"Bennour","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"56","published-online":{"date-parts":[[2025,6,30]]},"reference":[{"key":"S2631717625100030_r35","doi-asserted-by":"publisher","DOI":"10.3390\/s22082953"},{"key":"S2631717625100030_r33","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2015.2498998"},{"key":"S2631717625100030_r2","first-page":"215","volume-title":"Design and Modeling of Mechanical Systems - V","author":"Baklouti","year":"2022"},{"key":"S2631717625100030_r36","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2007.911646"},{"key":"S2631717625100030_r25","doi-asserted-by":"publisher","DOI":"10.1055\/s-2007-965468"},{"key":"S2631717625100030_r14","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2022.10.014"},{"key":"S2631717625100030_r6","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbiomech.2009.08.004"},{"key":"S2631717625100030_r28","doi-asserted-by":"publisher","DOI":"10.3390\/s111009182"},{"key":"S2631717625100030_r30","doi-asserted-by":"publisher","DOI":"10.1115\/1.4028822"},{"key":"S2631717625100030_r8","doi-asserted-by":"publisher","DOI":"10.3390\/s24051675"},{"key":"S2631717625100030_r19","doi-asserted-by":"publisher","DOI":"10.1016\/j.clinbiomech.2010.12.001"},{"key":"S2631717625100030_r39","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2016.2521823"},{"key":"S2631717625100030_r18","doi-asserted-by":"publisher","DOI":"10.1515\/auto-2020-0085"},{"key":"S2631717625100030_r15","doi-asserted-by":"publisher","DOI":"10.3390\/s22041504"},{"key":"S2631717625100030_r31","doi-asserted-by":"publisher","DOI":"10.1101\/2023.02.21.526496"},{"key":"S2631717625100030_r1","doi-asserted-by":"publisher","DOI":"10.3390\/s24113419"},{"key":"S2631717625100030_r11","doi-asserted-by":"publisher","DOI":"10.4249\/scholarpedia.6232"},{"key":"S2631717625100030_r13","doi-asserted-by":"publisher","DOI":"10.1109\/PLANS.2004.1309003"},{"key":"S2631717625100030_r12","article-title":"Artificial neural network for tilt compensation in yaw estimation","author":"Halitim","year":"2023","journal-title":"Transactions of the Institute of Measurement and Control"},{"key":"S2631717625100030_r20","doi-asserted-by":"publisher","DOI":"10.1123\/jab.2016-0120"},{"key":"S2631717625100030_r7","doi-asserted-by":"publisher","DOI":"10.1007\/s11517-007-0296-5"},{"key":"S2631717625100030_r17","doi-asserted-by":"publisher","DOI":"10.1109\/ICORR.2011.5975346"},{"key":"S2631717625100030_r16","doi-asserted-by":"publisher","DOI":"10.1007\/BF02345966"},{"key":"S2631717625100030_r34","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2019.2953006"},{"key":"S2631717625100030_r24","doi-asserted-by":"publisher","DOI":"10.1016\/j.gaitpost.2008.04.003"},{"key":"S2631717625100030_r9","doi-asserted-by":"publisher","DOI":"10.3390\/s18010076"},{"key":"S2631717625100030_r3","doi-asserted-by":"publisher","DOI":"10.14198\/JoPha.2017.8.1.03"},{"key":"S2631717625100030_r22","doi-asserted-by":"publisher","DOI":"10.1016\/j.jse.2011.07.032"},{"key":"S2631717625100030_r23","unstructured":"Pedley, M (2013) Tilt Sensing Using a Three-Axis Accelerometer (Application Note No. AN3461). 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Published by Cambridge University Press","name":"copyright","label":"Copyright","group":{"name":"copyright_and_licensing","label":"Copyright and Licensing"}},{"value":"This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial licence (http:\/\/creativecommons.org\/licenses\/by-nc\/4.0), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original article is properly cited. The written permission of Cambridge University Press must be obtained prior to any commercial use.","name":"license","label":"License","group":{"name":"copyright_and_licensing","label":"Copyright and Licensing"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}],"article-number":"e28"}}