A computational framework to study neural-structural interactions in human walking

[摘要] (cont.) We cross-validate our framework against independent datasets, and nd good model-empirical ankle torque agreement (R 2 = 0.96). The resulting muscle length and velocity predictions are consistent with in vivo ultra- sound scan measures. Further, model predictions reveal how leg structure and neural control come together to (a) dene roles of individual plantar exor muscles and (b) boost their joint performance. We nd that the Soleus operates as a steady ecient force source, while the Gastrocnemius functions as a burst mechanical power source. An analysis of the estimated states and optimized parameters reveals that the plantar exors operate jointly at a net mechanical eciency of 0.69 ±0.12. This is roughly three times higher than the maximal eciency of skeletal muscle performing positive work. Our results suggest that neural control may be tuned to exploit the elasticity of tendinous structures in the leg and achieve the high walking economy of humans.

[发布机构] Massachusetts Institute of Technology