{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,19]],"date-time":"2026-09-19T05:01:50Z","timestamp":1789794110778,"version":"4.0.1"},"reference-count":57,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2026,9,17]],"date-time":"2026-09-17T00:00:00Z","timestamp":1789603200000},"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>Walking is a key movement of interest in biomechanics, yet gold-standard data collection methods are time- and cost-expensive. This paper presents a real-time, multimodal, high sample rate lower-limb motion capture framework, based on wireless wearable sensors and machine learning algorithms. Random Forests are used to estimate joint angles from IMU data, and ground reaction force (GRF) is predicted from an instrumented insole, while joint moments are predicted from angles and GRF using deep learning based on the ResNet-16 architecture. All three models achieve good accuracy compared to the literature, and the predictions are logged at 1 kHz with a minimal delay of 23 ms for 20s worth of input data.<\/jats:p>","DOI":"10.3390\/s26185885","type":"journal-article","created":{"date-parts":[[2026,9,17]],"date-time":"2026-09-17T11:41:35Z","timestamp":1789645295000},"page":"5885","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Real-Time Prediction of Lower-Limb Joint Kinematics, Kinetics, and Ground Reaction Force Using Wearable Sensors and Machine Learning"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-3814-825X","authenticated-orcid":false,"given":"Jos\u00e9e","family":"Mallah","sequence":"first","affiliation":[{"name":"Electrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge CB3 0FA, UK"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"software","vocabulary":"credit"},{"role":"validation","vocabulary":"credit"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"},{"role":"data-curation","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"visualization","vocabulary":"credit"}]},{"given":"Yu","family":"Zhu","sequence":"additional","affiliation":[{"name":"Electrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge CB3 0FA, UK"},{"name":"Department of Electronic Systems, Aalborg University, 9220 Aalborg, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"data-curation","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-6427-5049","authenticated-orcid":false,"given":"Kailang","family":"Xu","sequence":"additional","affiliation":[{"name":"Electrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge CB3 0FA, UK"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"software","vocabulary":"credit"}]},{"given":"Gurvinder S.","family":"Virk","sequence":"additional","affiliation":[{"name":"Endoenergy Systems Ltd., Cambridge CB25 0HG, UK"},{"name":"Huzhou Wuxing District Intelligent Robot Innovation Research Institute, Huzhou 313000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5882-9768","authenticated-orcid":false,"given":"Shaoping","family":"Bai","sequence":"additional","affiliation":[{"name":"Department of Materials and Production, Aalborg University, 9220 Aalborg, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9067-2534","authenticated-orcid":false,"given":"Luigi G.","family":"Occhipinti","sequence":"additional","affiliation":[{"name":"Electrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge CB3 0FA, UK"},{"name":"Wolfson School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Loughborough LE11 3TU, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"222","DOI":"10.5435\/00124635-200205000-00009","article-title":"A Practical Guide to Gait Analysis","volume":"10","author":"Chambers","year":"2002","journal-title":"J. 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