{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,29]],"date-time":"2026-10-29T06:43:55Z","timestamp":1793256235239,"version":"4.5.0"},"reference-count":36,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2024,10,8]],"date-time":"2024-10-08T00:00:00Z","timestamp":1728345600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003130","name":"Fonds Wetenschappelijk Onderzoek","doi-asserted-by":"publisher","award":["11Q3024N"],"award-info":[{"award-number":["11Q3024N"]}],"id":[{"id":"10.13039\/501100003130","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004497","name":"Onderzoeksraad, KU Leuven","doi-asserted-by":"publisher","award":["C3\/20\/125"],"award-info":[{"award-number":["C3\/20\/125"]}],"id":[{"id":"10.13039\/501100004497","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Bioeng. Biotechnol."],"abstract":"<jats:p>Running poses a high risk of developing running-related injuries (RRIs). The majority of RRIs are the result of an imbalance between cumulative musculoskeletal load and load capacity. A general estimate of whole-body biomechanical load can be inferred from ground reaction forces (GRFs). Unfortunately, GRFs typically can only be measured in a controlled environment, which hinders its wider applicability. The advent of portable sensors has enabled training machine-learned models that are able to monitor GRF characteristics associated with RRIs in a broader range of contexts. Our study presents and evaluates a machine-learning method to predict the contact time, active peak, impact peak, and impulse of the vertical GRF during running from three-dimensional sacral acceleration. The developed models for predicting active peak, impact peak, impulse, and contact time demonstrated a root-mean-squared error of 0.080 body weight (BW), 0.198 BW, 0.0073 BW <jats:inline-formula><mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"m1\"><mml:mrow><mml:mo>\u22c5<\/mml:mo><\/mml:mrow><\/mml:math><\/jats:inline-formula> seconds, and 0.0101\u00a0seconds, respectively. Our proposed method outperformed a mean-prediction baseline and two established methods from the literature. The results indicate the potential utility of this approach as a valuable tool for monitoring selected factors related to running-related injuries.<\/jats:p>","DOI":"10.3389\/fbioe.2024.1440033","type":"journal-article","created":{"date-parts":[[2024,10,8]],"date-time":"2024-10-08T04:28:15Z","timestamp":1728361695000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":14,"title":["Predicting vertical ground reaction force characteristics during running with machine learning"],"prefix":"10.3389","volume":"12","author":[{"given":"Sieglinde","family":"Bogaert","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jesse","family":"Davis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Benedicte","family":"Vanwanseele","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2024,10,8]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"e11199","DOI":"10.7717\/peerj.11199","article-title":"Sacral acceleration can predict whole-body kinetics and stride kinematics across running speeds","volume":"9","author":"Alcantara","year":"2021","journal-title":"PeerJ"},{"key":"B3","doi-asserted-by":"publisher","first-page":"1170","DOI":"10.1111\/sms.12883","article-title":"A framework for the etiology of running-related injuries","volume":"27","author":"Bertelsen","year":"2017","journal-title":"Scand. 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