Mechanical loading prediction through accelerometry data during walking and running

Eur J Sport Sci. 2023 Aug;23(8):1518-1527. doi: 10.1080/17461391.2022.2102437. Epub 2022 Aug 11.


Currently, there is no way to assess mechanical loading variables such as peak ground reaction forces (pGRF) and peak loading rate (pLR) in clinical settings. The purpose of this study was to develop accelerometry-based equations to predict both pGRF and pLR during walking and running. One hundred and thirty one subjects (79 females; 76.9 ± 19.6 kg) walked and ran at different speeds (2-14 km·h-1) on a force plate-instrumented treadmill while wearing accelerometers at their ankle, lower back and hip. Regression equations were developed to predict pGRF and pLR from accelerometry data. Leave-one-out cross-validation was used to calculate prediction accuracy and Bland-Altman 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-based equations, representing an easy way to determine mechanical loading in free-living conditions. The pLR prediction equations yielded a somewhat lower prediction accuracy compared with the pGRF equations.

Keywords: Activity monitor; force plates; ground reaction force; loading rate; locomotion; raw acceleration.

Plain language summary

Peak ground reaction forces can be accurately predicted through raw accelerometry data.These predictions are valid for a broad range of body masses and for ankle, lower back and hip accelerometer placements.Peak loading rate prediction presented lower accuracy compared with peak ground reaction force prediction.These findings result in a simple method to predict mechanical loading in clinical practice, which is relevant in some areas of sports medicine such as bone health and injury prevention.

MeSH terms

  • Accelerometry
  • Ankle
  • Ankle Joint
  • Biomechanical Phenomena
  • Female
  • Humans
  • Running*
  • Walking*