bioRxivBioengineeringPreprint
Mechanical Equilibrium of Step Transition Governs Vertical Ground Reaction Force Morphology in Human Walking
Abstract
Understanding the vertical ground reaction force (vGRF) profile offers important insight into how humans regulate mechanical work during walking. Although the characteristic double-hump vGRF pattern is well documented, the mechanical factors underlying asymmetry in peak amplitudes and midstance trough timing remain unclear. Using a simple powered walking model and an inverted pendulum simulation with constant hip torque, we examined how step-transition work--collision and push-off--shapes the vGRF trajectory. We further compared these predictions to empirical data spanning walking speeds from 0.8-1.4 m. s-1. The simple walking model predicted symmetric vGRF profiles across speeds because collision and push-off impulses were equal, resulting in passive single-support motion. In contrast, adding hip torque within the pendular model produced stance-phase asymmetries, shifting the vGRF trough earlier when torque added energy and later when torque dissipated energy. Empirical analysis revealed that collision and push-off impulses were generally unequal except at one speed, producing asymmetric vGRF peaks. At low speeds, push-off exceeded collision; at high speeds, the reverse occurred, consistent with a need for compensatory single-support positive work. These mechanical imbalances predicted systematic shifts in trough timing toward the dominant impulse. Therefore, we propose the Vertical GRF Trough Timing Index (vGRF-TTI), combined with collision and push-off peak amplitudes, as a clinically meaningful outcome capturing the balance of step-transition work. Earlier troughs with elevated collision peaks indicate impaired push-off or constrained gait conditions, whereas later troughs with larger push-off peaks reflect compensatory or enhanced propulsion. These metrics provide sensitive, mechanism-based indicators of gait efficiency and neuromotor control.
- organism: human
- assay: imaging
- research focus: synaptic & neural circuits
- approach: mechanistic / dynamical model
- Citations
- 0
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