Predicting normative walking biomechanics across the lifespan using seven simple features

The assessment of gait impairments requires a normative reference for comparison. For a fair assessment, comparisons must be made against a reference standing after controlling for sex, anthropometry, and walking characteristics. This study aimed to develop statistical models that predict the lower-limb kinematics and kinetics of walking across the lifespan of healthy participants, using seven simple covariates. Sixteen statistical models predicted 16 joint kinematics and kinetics during walking using the covariates of sex, age, height, mass, side (laterality), walking speed, and cadence, which were developed based on 301 participants between three to 91 years old. The root mean squared error (RMSE) ranged from 4.71° to 7.97° for joint angles, within 0.07 N/kg for ground reaction forces, 0.09 to 0.15 Nm/kg for joint moments, and 0.33 to 0.39 W/kg for joint powers. We provide both online and local apps which can be easily used by clinicians and scientists to generate normative walking data with uncertainty values, which can be used for movement impairment analysis ( https://github.com/EmanuelSommer/ShinyFOSR ) .

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Publication Details

Journal
Journal of NeuroEngineering and Rehabilitation
Published
2025-10-24
DOI
https://doi.org/10.1186/s12984-025-01768-9
Citations
1
Primary Topic
Lower Extremity Biomechanics and Pathologies
Type
article
Field-Weighted Citation Impact
0.67

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article

Predicting normative walking biomechanics across the lifespan using seven simple features

Richard J. Foster, Qichang Mei, Bernard X. W. Liew, David Rügamer et al.
1 citations
Journal of NeuroEngineering and Rehabilitation
Lower Extremity Biomechanics and Pathologies
0.67
article

Predicting normative walking biomechanics across the lifespan using seven simple features

Richard J. Foster, Qichang Mei, Bernard X. W. Liew, David Rügamer, Rachel Senden, Kenneth Meijer, Matthew Taylor, Emanuel Sommer
article en
1 citations

Abstract

The assessment of gait impairments requires a normative reference for comparison. For a fair assessment, comparisons must be made against a reference standing after controlling for sex, anthropometry, and walking characteristics. This study aimed to develop statistical models that predict the lower-limb kinematics and kinetics of walking across the lifespan of healthy participants, using seven simple covariates. Sixteen statistical models predicted 16 joint kinematics and kinetics during walking using the covariates of sex, age, height, mass, side (laterality), walking speed, and cadence, which were developed based on 301 participants between three to 91 years old. The root mean squared error (RMSE) ranged from 4.71° to 7.97° for joint angles, within 0.07 N/kg for ground reaction forces, 0.09 to 0.15 Nm/kg for joint moments, and 0.33 to 0.39 W/kg for joint powers. We provide both online and local apps which can be easily used by clinicians and scientists to generate normative walking data with uncertainty values, which can be used for movement impairment analysis ( https://github.com/EmanuelSommer/ShinyFOSR ) .

Journal of NeuroEngineering and RehabilitationVol. 22(1)
Ningbo University (CN), University of Essex (GB), University of Auckland (NZ), Maastricht University Medical Centre (NL), Maastricht University (NL), Liverpool John Moores University (GB), Ludwig-Maximilians-Universität München (DE)
Medical Research Council
Openalex Percentile: Top 25%
Lower Extremity Biomechanics and Pathologies
0.67
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