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Speed adaptation in a powered transtibial prosthesis controlled with a neuromuscular model

机译:由神经肌肉模型控制的动力型胫骨假体的速度适应

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摘要

Control schemes for powered ankle–foot prostheses would benefit greatly from a means to make them inherently adaptive to different walking speeds. Towards this goal, one may attempt to emulate the intact human ankle, as it is capable of seamless adaptation. Human locomotion is governed by the interplay among legged dynamics, morphology and neural control including spinal reflexes. It has been suggested that reflexes contribute to the changes in ankle joint dynamics that correspond to walking at different speeds. Here, we use a data-driven muscle–tendon model that produces estimates of the activation, force, length and velocity of the major muscles spanning the ankle to derive local feedback loops that may be critical in the control of those muscles during walking. This purely reflexive approach ignores sources of non-reflexive neural drive and does not necessarily reflect the biological control scheme, yet can still closely reproduce the muscle dynamics estimated from biological data. The resulting neuromuscular model was applied to control a powered ankle–foot prosthesis and tested by an amputee walking at three speeds. The controller produced speed-adaptive behaviour; net ankle work increased with walking speed, highlighting the benefits of applying neuromuscular principles in the control of adaptive prosthetic limbs.
机译:电动脚踝假肢的控制方案将从使它们固有地适应不同步行速度的方法中受益匪浅。为了实现这一目标,人们可以尝试模仿完整的人类脚踝,因为它能够无缝适应。人的运动受腿部动力学,形态和神经控制(包括脊柱反射)之间的相互作用控制。已经提出,反射有助于踝关节动力学的变化,其对应于以不同速度行走。在这里,我们使用数据驱动的肌肉-肌腱模型,该模型生成横跨踝部的主要肌肉的激活,力,长度和速度的估计值,以得出局部反馈回路,这可能对步行过程中这些肌肉的控制至关重要。这种纯粹的自反性方法忽略了非自反性神经驱动的来源,并不一定反映生物控制方案,但仍可以紧密地再现根据生物数据估算的肌肉动力学。由此产生的神经肌肉模型被应用于控制脚踝踝关节动力假体,并由截肢者以三种速度行走进行测试。控制器产生了速度自适应行为;净脚踝工作随着步行速度的增加而增加,突出了将神经肌肉原理应用于适应性假肢控制的好处。

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