{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T20:45:13Z","timestamp":1790196313721,"version":"4.1.0"},"reference-count":46,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2025,1,10]],"date-time":"2025-01-10T00:00:00Z","timestamp":1736467200000},"content-version":"vor","delay-in-days":9,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Scandinavian Med Sci Sports"],"published-print":{"date-parts":[[2025,1]]},"abstract":"<jats:title>ABSTRACT<\/jats:title><jats:p>Measuring lower extremity impact acceleration is a common strategy to identify runners with increased injury risk. However, existing axial peak tibial acceleration (PTA) thresholds for determining high\u2010impact runners typically rely on small samples or fixed running speeds. This study aimed to describe the distribution of axial PTA among runners at their preferred running speed, determine an appropriate adjustment for investigating impact magnitude at different speeds, and compare biomechanics between runners classified by impact magnitude. A total of 171 runners ran on an instrumented treadmill at their preferred running speed during 3D motion capture. Axial PTA was collected at the distal tibia. The relationship between axial PTA and running speed was investigated using linear regression. Runners were categorized into impact sub\u2010groups, with high\u2010 and low\u2010impact runners identified if their axial PTA was \u00b11 standard deviation of the model predicted value. Differences in demographics, training, and running biomechanics between impact sub\u2010groups were compared. Mean axial PTA was 7.8\u2009g across all running speeds. Axial PTA increased with running speed, with a 1.7\u2009g increase for every 1.0\u2009m\/s increase. There were no differences in axial PTA between males and females (<jats:italic>p<\/jats:italic>\u2009=\u20090.214) and lower limbs (<jats:italic>p<\/jats:italic>\u2009=\u20090.312). High\u2010impact runners had higher vertical loading rates (<jats:italic>p<\/jats:italic>\u2009&lt;\u20090.001) and greater ankle dorsiflexion at initial contact (<jats:italic>p<\/jats:italic>\u2009&lt;\u20090.001) compared to low\u2010impact runners. No differences in age, body mass, height, or weekly running distances were observed across impact sub\u2010groups. This study proposes a method to identify the impact classification of runners based on their axial PTA for screening, monitoring, or gait retraining.<\/jats:p>","DOI":"10.1111\/sms.70002","type":"journal-article","created":{"date-parts":[[2025,1,10]],"date-time":"2025-01-10T10:14:02Z","timestamp":1736504042000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Classifying Impact Loading Using Axial Peak Tibial Acceleration and Impact\u2010Related Biomechanical Differences During Treadmill Running"],"prefix":"10.1111","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8618-6410","authenticated-orcid":false,"given":"Eoin W.","family":"Doyle","sequence":"first","affiliation":[{"name":"Faculty of Medicine, Health, and Human Sciences Macquarie University  Sydney New South Wales Australia"},{"name":"Biomechanics, Physical Performance, and Exercise Research Group Macquarie University  Sydney New South Wales Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1227-6835","authenticated-orcid":false,"given":"Tim L. 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