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基于生理数据输入的小腿轨迹误差框架的实验论证。

Experimental Demonstration of the Lower Leg Trajectory Error Framework Using Physiological Data as Inputs.

机构信息

GEAR Laboratory, Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139.

Jesse Brown VA Medical Center, Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, IL 60208.

出版信息

J Biomech Eng. 2021 Mar 1;143(3). doi: 10.1115/1.4048643.

Abstract

While many studies have attempted to characterize the mechanical behavior of passive prosthetic feet to understand their influence on amputee gait, the relationship between mechanical design and biomechanical performance has not yet been fully articulated from a fundamental physics perspective. A novel framework, called lower leg trajectory error (LLTE) framework, presents a means of quantitatively optimizing the constitutive model of prosthetic feet to match a reference kinematic and kinetic dataset. This framework can be used to predict the required stiffness and geometry of a prosthesis to yield a desired biomechanical response. A passive prototype foot with adjustable ankle stiffness was tested by a unilateral transtibial amputee to evaluate this framework. The foot condition with LLTE-optimal ankle stiffness enabled the user to replicate the physiological target dataset within 16% root-mean-square (RMS) error. Specifically, the measured kinematic variables matched the target kinematics within 4% RMS error. Testing a range of ankle stiffness conditions from 1.5 to 24.4 N·m/deg with the same user indicated that conditions with lower LLTE values deviated the least from the target kinematic data. Across all conditions, the framework predicted the horizontal/vertical position, and angular orientation of the lower leg during midstance within 1.0 cm, 0.3 cm, and 1.5 deg, respectively. This initial testing suggests that prosthetic feet designed with low LLTE values could offer benefits to users. The LLTE framework is agnostic to specific foot designs and kinematic/kinetic user targets, and could be used to design and customize prosthetic feet.

摘要

虽然许多研究试图描述被动假肢脚的机械行为以了解其对截肢者步态的影响,但从基础物理学的角度来看,机械设计和生物力学性能之间的关系尚未得到充分阐明。一个新的框架,称为小腿轨迹误差 (LLTE) 框架,提供了一种定量优化假肢脚本构模型以匹配参考运动学和动力学数据集的方法。该框架可用于预测假肢所需的刚度和几何形状,以产生所需的生物力学响应。通过单侧胫骨截肢者测试了一种具有可调踝刚度的被动原型脚,以评估该框架。具有 LLTE 优化踝刚度的脚条件使使用者能够在 16%均方根 (RMS) 误差内复制生理目标数据集。具体来说,测量的运动学变量与目标运动学的 RMS 误差在 4%以内匹配。使用相同的使用者测试从 1.5 到 24.4 N·m/deg 的一系列踝刚度条件表明,具有较低 LLTE 值的条件与目标运动学数据的偏差最小。在所有条件下,该框架预测了在中间站立期间小腿的水平/垂直位置和角向位置,误差分别在 1.0 cm、0.3 cm 和 1.5 度以内。初步测试表明,设计具有低 LLTE 值的假肢脚可以为使用者带来益处。LLTE 框架与特定的脚型设计和运动学/动力学用户目标无关,可用于设计和定制假肢脚。

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