Functional Electrical Stimulation Capability Maps

Eric M. Schearer, D. Wolf
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引用次数: 1

Abstract

We introduce capability maps visualizing the abilities of the arm of a person with a cervical spinal cord injury activated by functional electrical stimulation (FES). We map the arm’s workspace at different wrist positions using a person-specific arm model based on force data gathered during interactions with a robot. We describe four maps: 1) a map of the maximum force the person can produce in one direction, 2) a map of wrist configurations that FES can hold against gravity and other passive forces, 3) a map of the maximum force the person can apply in all directions, and 4) a map of the directions the arm can move with FES. To demonstrate these maps we applied electrical stimulation to nine muscle groups of a person with high tetraplegia, measured the resulting force with a robot attached to the person’s wrist, created a Gaussian process regression model relating the forces to the wrist positions, and used this model to create the four capability maps. The results are 2D images displaying the arm’s force production and movement capabilities for a person with high tetraplegia as a function of wrist position. As these maps predict functional benefits of specific interventions, they can reduce risk in developing new interventions to restore function to people with whole-arm paralysis.
功能性电刺激能力图
我们介绍了通过功能性电刺激(FES)激活的颈脊髓损伤患者手臂能力可视化的能力图。我们使用基于与机器人交互过程中收集的力数据的个人特定手臂模型来绘制手臂在不同手腕位置的工作空间。我们描述了四个地图:1)一个人可以在一个方向上产生的最大力的地图,2)FES可以抵抗重力和其他被动力的手腕结构的地图,3)一个人可以在所有方向上施加的最大力的地图,以及4)一个手臂可以用FES移动的方向的地图。为了展示这些地图,我们对一个四肢瘫痪的人的九个肌肉群进行了电刺激,用一个附着在这个人手腕上的机器人测量了产生的力,创建了一个高斯过程回归模型,将力与手腕位置联系起来,并用这个模型创建了四个能力地图。结果是2D图像,显示了高度四肢瘫痪者的手臂的力量产生和运动能力,作为手腕位置的函数。由于这些地图预测了特定干预措施的功能益处,它们可以降低开发新的干预措施以恢复全臂瘫痪患者功能的风险。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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