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March 14, 2026Frontiers in Bioengineering and Biotechnology0 citationsOpen Access

Effects of load carriage methods on fall risk and gait variability during stair ascent: a functional data analysis approach

XZXingchen ZhangYLYuan LiYFYuling Fang

Key Points

  • This study aims to investigate how three different load carriage methods affect gait variability and fall risk during stair ascent in healthy adult males.
  • Nineteen healthy young male participants were recruited.
  • Kinematic and kinetic data were collected using a three-dimensional motion capture system and force plates.
  • Functional principal component analysis was used to analyze joint angle time series.
  • One-way ANOVA was applied to compare gait parameters and center of pressure measures across load conditions.
  • Significant differences were found in step length, single support time, and second double support time across load conditions.
  • The center of pressure trajectory showed significant variations in the mediolateral direction.
  • Notable differences in joint kinematics were identified for the hip, knee, and ankle joints under different loading conditions.

Abstract

Objective Based on the existing research that predominantly focuses on loaded level walking or employs discrete-point methods to analyze stair negotiation, this study utilizes functional data analysis to systematically investigate the effects of three load carriage methods on gait variability during upstairs walking in healthy adult males, aiming to elucidate the specific neuromuscular adaptation strategies induced by different loading conditions. Methods Nineteen healthy young male participants were recruited for this study. Kinematic and kinetic data were collected during stair walking under three load carriage conditions using a three-dimensional motion capture system and force plates. Gait parameters, center of pressure (COP) trajectories, and lower-limb joint angle time series in the sagittal and frontal planes for the hip, knee, and ankle joints were extracted. Functional principal component analysis (fPCA) was employed to reduce the dimensionality and process the joint angle curves, aiming to identify the dominant modes of variability throughout the entire gait cycle. One-way analysis of variance (ANOVA) was subsequently applied to compare between-group differences in gait parameters and COP measures. Results Significant differences were observed across different load carriage conditions in step length, single support time, and second double support time ( P 0.05). The center of pressure (COP) trajectory in the mediolateral direction also showed significant differences ( P 0.05). Regarding joint kinematics, functional principal component analysis revealed significant between-condition differences in the sagittal plane hip angle for principal component 1 (PC1), as well as in PC1 and principal component 3 (PC3) for the frontal plane hip angle ( P 0.05). For the knee joint, a significant difference was found in PC1 of the frontal plane angle time series ( P 0.05). At the ankle joint, significant differences were identified in PC3 of the sagittal plane angle and in PC1 of the frontal plane angle ( P 0.05). Conclusion By employing a functional data analysis framework, this study provides a more nuanced understanding of phase-specific compensatory mechanisms during loaded stair ascent, revealing that the shoulder load poses a greater fall risk than hand load. This elevated risk is primarily due to an elevated and asymmetric center of mass, which induces a forward trunk inclination and compromises stability in both the frontal and sagittal planes, necessitating more extensive gait adaptations.

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Cite This Study

Zhang et al. (2026) studied this question.

synapsesocial.com/papers/69b4fa9ab39f7826a300b4d7https://doi.org/10.3389/fbioe.2026.1740819
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