Simulating ideal assistive devices to reduce the metabolic cost of walking with heavy loads

Wearable robotic devices can restore and enhance mobility. There is growing interest in designing devices that reduce the metabolic cost of walking; however, designers lack guidelines for which joints to assist and when to provide the assistance. To help address this problem, we used musculoskeletal simulation to predict how hypothetical devices affect muscle activity and metabolic cost when walking with heavy loads. We explored 7 massless devices, each providing unrestricted torque at one degree of freedom in one direction (hip abduction, hip flexion, hip extension, knee flexion, knee extension, ankle plantarflexion, or ankle dorsiflexion). We used the Computed Muscle Control algorithm in OpenSim to find device torque profiles that minimized the sum of squared muscle activations while tracking measured kinematics of loaded walking without assistance. We then examined the metabolic savings provided by each device, the corresponding device torque profiles, and the resulting changes in muscle activity. We found that the hip flexion, knee flexion, and hip abduction devices provided greater metabolic savings than the ankle plantarflexion device. The hip abduction device had the greatest ratio of metabolic savings to peak instantaneous positive device power, suggesting that frontal-plane hip assistance may be an efficient way to reduce metabolic cost. Overall, the device torque profiles generally differed from the corresponding net joint moment generated by muscles without assistance, and occasionally exceeded the net joint moment to reduce muscle activity at other degrees of freedom. Many devices affected the activity of muscles elsewhere in the limb; for example, the hip flexion device affected muscles that span the ankle joint. Our results may help experimentalists decide which joint motions to target when building devices and can provide intuition for how devices may interact with the musculoskeletal system. The simulations are freely available online, allowing others to reproduce and extend our work.

可穿戴机器人装置可恢复并提升运动能力。当前学界对设计可降低步行代谢能耗的装置的兴趣与日俱增，但设计者仍缺乏针对辅助关节选择与辅助时机的指导准则。为解决这一问题，本研究采用肌肉骨骼仿真（musculoskeletal simulation）技术，预测负重步行时假想装置对肌肉活动与代谢能耗的影响。本研究共探索了7种无质量装置，每种装置均可在单个自由度的单方向上提供无限制扭矩，分别对应髋外展（hip abduction）、髋屈曲（hip flexion）、髋伸展（hip extension）、膝屈曲（knee flexion）、膝伸展（knee extension）、踝跖屈（ankle plantarflexion）与踝背屈（ankle dorsiflexion）。本研究借助OpenSim中的肌肉控制计算（Computed Muscle Control）算法，求解在跟踪无辅助负重步行实测运动学数据的前提下，使肌肉激活平方和最小化的装置扭矩曲线。随后，本研究分析了每种装置带来的代谢能耗节约量、对应装置扭矩曲线，以及由此产生的肌肉活动变化。研究结果表明，髋屈曲、膝屈曲与髋外展装置的代谢能耗节约效果优于踝跖屈装置。髋外展装置的代谢能耗节约量与峰值瞬时正装置功率之比最高，这提示额状面髋关节辅助或许是降低步行代谢能耗的高效方案。整体而言，装置扭矩曲线通常与无辅助状态下肌肉产生的对应净关节力矩存在差异，且偶尔会超过净关节力矩，以降低其他自由度上的肌肉活动。诸多装置会影响肢体其他部位的肌肉活动，例如髋屈曲装置会对跨过踝关节的肌肉产生影响。本研究结果可为实验研究者在搭建装置时选择目标关节运动提供参考，并可帮助研究者直观理解装置与肌肉骨骼系统的交互机制。本研究所用的仿真程序已在线开源，可供其他研究者复现并拓展本研究工作。