Department of Orthopaedic Surgery, Stanford University, CA, USA.
J Biomech. 2012 Jun 26;45(10):1842-9. doi: 10.1016/j.jbiomech.2012.03.032. Epub 2012 May 11.
The goal of this study was to identify which muscle activation patterns and gait features best predict the metabolic cost of inclined walking. We measured muscle activation patterns, joint kinematics and kinetics, and metabolic cost in sixteen subjects during treadmill walking at inclines of 0%, 5%, and 10%. Multivariate regression models were developed to predict the net metabolic cost from selected groups of the measured variables. A linear regression model including incline and the squared integrated electromyographic signals of the soleus and vastus lateralis explained 96% of the variance in metabolic cost, suggesting that the activation patterns of these large muscles have a high predictive value for metabolic cost. A regression model including only the peak knee flexion angle during stance phase, peak knee extension moment, peak ankle plantarflexion moment, and peak hip flexion moment explained 89% of the variance in metabolic cost; this finding indicates that kinematics and kinetics alone can predict metabolic cost during incline walking. The ability of these models to predict metabolic cost from muscle activation patterns and gait features points the way toward future work aimed at predicting metabolic cost when gait is altered by changes in neuromuscular control or the use of an assistive technology.
本研究旨在确定哪些肌肉活动模式和步态特征最能预测倾斜行走的代谢成本。我们在十六名受试者在跑步机上以 0%、5%和 10%的坡度行走时，测量了肌肉活动模式、关节运动学和动力学以及代谢成本。建立了多元回归模型，以从选定的测量变量组中预测净代谢成本。一个包括坡度和比目鱼肌和股外侧肌的整合肌电图信号的平方的线性回归模型解释了代谢成本的 96%的方差，表明这些大肌肉的激活模式对代谢成本具有很高的预测价值。一个仅包括站立阶段的峰值膝关节屈曲角度、峰值膝关节伸展力矩、峰值踝关节跖屈力矩和峰值髋关节屈曲力矩的回归模型解释了代谢成本的 89%的方差；这一发现表明，运动学和动力学本身可以预测倾斜行走时的代谢成本。这些模型从肌肉活动模式和步态特征预测代谢成本的能力为未来的工作指明了方向，这些工作旨在预测神经肌肉控制改变或使用辅助技术时步态改变时的代谢成本。
