Stingel Jon P, Hicks Jennifer L, Uhlrich Scott D, Delp Scott L
Mechanical Engineering Department, Stanford University, Stanford, CA 94305.
Bioengineering Department, Stanford University, Stanford, CA 94305 USA.
IEEE Robot Autom Lett. 2023 Oct;8(10):6267-6274. doi: 10.1109/lra.2023.3303094. Epub 2023 Aug 7.
Connecting the legs with a spring attached to the shoelaces, called an exotendon, can reduce the energetic cost of running, but how the exotendon reduces the energetic burden of individual muscles remains unknown. We generated muscle-driven simulations of seven individuals running with and without the exotendon to discern whether savings occurred during the stance phase or the swing phase, and to identify which muscles contributed to energy savings. We computed differences in muscle-level energy consumption, muscle activations, and changes in muscle-fiber velocity and force between running with and without the exotendon. The seven of nine participants who reduced energy cost when running with the exotendon reduced their measured energy expenditure rate by 0.9 W/kg (8.3%). Simulations predicted a 1.4 W/kg (12.0%) reduction in the average rate of energy expenditure and correctly identified that the exotendon reduced rates of energy expenditure for all seven individuals. Simulations showed most of the savings occurred during stance (1.5 W/kg), though the rate of energy expenditure was also reduced during swing (0.3 W/kg). The energetic savings were distributed across the quadriceps, hip flexor, hip abductor, hamstring, hip adductor, and hip extensor muscle groups, whereas no changes were observed in the plantarflexor or dorsiflexor muscles. Energetic savings were facilitated by reductions in the rate of mechanical work performed by muscles and their estimated rate of heat production. By modeling muscle-level energetics, this simulation framework accurately captured measured changes in whole-body energetics when using an assistive device. This is a useful first step towards using simulation to accelerate device design by predicting how humans will interact with assistive devices that have yet to be built.
用一根系在鞋带上的弹簧连接双腿,即所谓的外肌腱,可以降低跑步的能量消耗,但外肌腱如何减轻单个肌肉的能量负担仍然未知。我们对七名个体在有和没有外肌腱的情况下跑步进行了肌肉驱动模拟,以辨别节省能量是发生在支撑阶段还是摆动阶段,并确定哪些肌肉有助于节省能量。我们计算了有和没有外肌腱跑步时肌肉水平的能量消耗、肌肉激活以及肌肉纤维速度和力量变化的差异。在使用外肌腱跑步时降低能量消耗的九名参与者中有七名,他们测得的能量消耗率降低了0.9W/kg(8.3%)。模拟预测平均能量消耗率降低1.4W/kg(12.0%),并正确识别出外肌腱降低了所有七名个体的能量消耗率。模拟显示,大部分能量节省发生在支撑阶段(1.5W/kg),不过摆动阶段的能量消耗率也有所降低(0.3W/kg)。能量节省分布在股四头肌、髋屈肌、髋外展肌、腘绳肌、髋内收肌和髋伸肌肌肉群中,而跖屈肌或背屈肌没有观察到变化。肌肉执行的机械功速率及其估计的产热速率降低有助于节省能量。通过对肌肉水平的能量学进行建模,这个模拟框架在使用辅助设备时准确地捕捉到了全身能量学的测量变化。这是朝着通过预测人类与尚未制造的辅助设备的相互作用来利用模拟加速设备设计迈出的有用的第一步。