{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T00:08:02Z","timestamp":1792022882764,"version":"4.4.0"},"reference-count":36,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T00:00:00Z","timestamp":1767312000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"DOI":"10.13039\/100012352","name":"Universit\u00e0 degli Studi di Milano","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100012352","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,1,2]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Outdoor running gait analysis using wearable sensors requires establishing minimum step requirements for reliable parameter measurement.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Sources of data<\/jats:title>\n                    <jats:p>Fourteen trained runners completed 10-minute trials at critical speed. RunScribe\u2122 captured kinetic\/kinematic data at 500\u00a0Hz. Convergence analysis determined minimum steps when cumulative means stabilized within \u00b12% for \u226510 consecutive steps.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Areas of agreement<\/jats:title>\n                    <jats:p>Most parameters achieved excellent reliability (ICC &amp;gt;\u20090.900). Metabolic parameters (V\u0307O\u2082: 108\u2009\u00b1\u200932 steps) and step rate (124\u2009\u00b1\u200936 steps) converged fastest, while kinematic variables required moderate sampling (stride length: 152\u2009\u00b1\u200948 steps; contact time: 198\u2009\u00b1\u200952 steps).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Areas of controversy<\/jats:title>\n                    <jats:p>Complex biomechanical metrics showed substantial variability: leg stiffness (kleg: 342\u2009\u00b1\u200978 steps; kvert: 298\u2009\u00b1\u200971 steps) and gait variability (246\u2009\u00b1\u200912 steps) required substantially more data, challenging brief field assessment feasibility.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Growing points<\/jats:title>\n                    <jats:p>This study establishes parameter-specific sampling protocols for outdoor gait analysis, demonstrating that different measurement domains require tailored data collection strategies to optimize ecological validity.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Areas timely for developing research<\/jats:title>\n                    <jats:p>Future research should examine how speed, terrain, and environmental conditions affect sampling requirements. Adaptive protocols and machine learning approaches offer promising opportunities for optimizing data collection efficiency.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bmb\/ldaf025","type":"journal-article","created":{"date-parts":[[2025,12,25]],"date-time":"2025-12-25T12:45:40Z","timestamp":1766666740000},"source":"Crossref","is-referenced-by-count":4,"title":["Determining the minimum number of steps required for reliable kinetic, kinematic, gait variability, and V\u0307O2 parameters in outdoor running"],"prefix":"10.1093","volume":"157","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4254-3105","authenticated-orcid":false,"given":"Johnny","family":"Padulo","sequence":"first","affiliation":[{"name":"Department of Biomedical Sciences for Health, Universit\u00e0 degli Studi di Milano , 20133 Milan 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