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

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 ( 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.