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Published on: August 23, 2017
Compensatory load shifting in response to combined muscle weakness and neural delay during uneven-terrain walking: A
1RISE Center, Industry-Academic Cooperation Foundation, Wonkwang Health Science University, 514, Iksan-daero, Iksan-si, Jeonbuk-do 54538, Republic of Korea.
Background:
Age-related falls are often associated with muscle weakness (MW) and neural response delays (ND), but their combined influence on gait stability on complex terrain is not well understood. We examined how MW and ND jointly shape stability and compensatory motor strategies in a predictive neuromusculoskeletal model.
Methods:
We used predictive simulations of a 2D sagittal-plane walker on uneven terrain. A factorial design (8 MW × 6 ND levels) varied quadriceps weakness (0-70%) and reflex pathway delays (0-100%). The objective used a mechanics-driven task formulation that prioritized completion of 15-s walking at a minimum forward speed of 1.0 m/s; stability was assessed post hoc from anterior-posterior Margin of Stability (MoS) and joint loading.
Results:
The stability landscape was nonlinear. Up to 60% weakness, the controller maintained mean MoS between approximately -0.38 m and -0.31 m across all ND levels. At 70% weakness, stable 15-s walking emerged only for selected delays, and these solutions exhibited markedly increased MoS variability and more extreme negative minima, indicating more fragile gait. In the most impaired yet viable condition (70% weakness with 100% delay), ankle load decreased by 10.2% and hip load increased by 44.5% relative to baseline, while knee loading did not show a parallel increase, indicating a pronounced distal-to-proximal redistribution.
Conclusion:
In this mechanics-driven model, combined neuromuscular impairments did not degrade stability in a linear manner but shifted gait toward hip-dominant, more variable patterns that preserved average MoS while increasing extreme destabilizing events. These model-based findings illustrate how interacting impairments can reshape the stability landscape, but they should be interpreted as hypothesis-generating rather than direct clinical predictions.
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