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The purpose of this study was to develop accelerometry\u2010based equations to predict both pGRF and pLR during walking and running. One hundred and thirty one subjects (79 females; 76.9\u2009\u00b1\u200919.6\u2005kg) walked and ran at different speeds (2\u201314\u2005km\u00b7h<jats:sup>\u22121<\/jats:sup>) on a force plate\u2013instrumented treadmill while wearing accelerometers at their ankle, lower back and hip. Regression equations were developed to predict pGRF and pLR from accelerometry data. Leave\u2010one\u2010out cross\u2010validation was used to calculate prediction accuracy and Bland\u2013Altman plots. Our pGRF prediction equation was compared with a reference equation previously published. Body mass and peak acceleration were included for pGRF prediction and body mass and peak acceleration rate for pLR prediction. All pGRF equation coefficients of determination were above 0.96, and a good agreement between actual and predicted pGRF was observed, with a mean absolute percent error (MAPE) below 7.3%. Accuracy indices from our equations were better than previously developed equations. All pLR prediction equations presented a lower accuracy compared to those developed to predict pGRF. Walking and running pGRF can be predicted with high accuracy by accelerometry\u2010based equations, representing an easy way to determine mechanical loading in free\u2010living conditions. The pLR prediction equations yielded a somewhat lower prediction accuracy compared with the pGRF equations.<\/jats:p>","DOI":"10.1080\/17461391.2022.2102437","type":"journal-article","created":{"date-parts":[[2022,7,15]],"date-time":"2022-07-15T10:22:52Z","timestamp":1657880572000},"page":"1518-1527","update-policy":"https:\/\/doi.org\/10.1080\/tandf_crossmark_01","source":"Crossref","is-referenced-by-count":7,"title":["Mechanical loading prediction through accelerometry data during walking and running"],"prefix":"10.1002","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0562-5803","authenticated-orcid":false,"given":"Lucas","family":"Veras","sequence":"first","affiliation":[{"name":"Research Center in Physical Activity, Health and Leisure (CIAFEL) Faculty of Sport University of Porto Porto Portugal"},{"name":"Laboratory for Integrative and Translational Research in Population Health (ITR) University of Porto Porto 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