Optimizing Populations of SAI Tactile Mechanoreceptors to Enable Activities of Daily Living.

Isabelle I Rivest, Gregory J Gerling
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Abstract

At present, the dense network of peripheral afferents between finger and brain and the large size of engineered sensors preclude the recreation of biologically observed afferent populations. This work uses a validated computational model of cutaneous skin and tactile afferents to evaluate sparse populations in performing tasks required in activities of daily living. Using a model (3D finite element representation of fingertip skin, linear bi-phasic transduction function, and leaky-integrate-and-fire neuronal model), we systematically varied populations of tactile receptors in dimensions of density (100, 45, 20, and 10 sensors/cm(2)) and size (diameter 0.1, 0.2, 0.5, and 1.0 mm) to determine if a given modeled population can discriminate spheres and cylinders representative of objects used in activities of daily living. Using a scoring system which allows for direct comparisons between the populations, our results indicate that a population must have at least 20 sensors per cm(2) to maintain response resolution in these activities of daily living and that larger-sized sensors do not degrade response resolution.

优化SAI触觉机械感受器的数量,使日常生活活动成为可能。
目前,手指和大脑之间密集的外周传入神经网络和大尺寸的工程传感器阻碍了生物观察传入神经群的重建。这项工作使用一个经过验证的皮肤和触觉传入的计算模型来评估在日常生活活动中执行任务所需的稀疏种群。利用一个模型(指尖皮肤的三维有限元表示、线性双相转导函数和渗漏-整合-放电神经元模型),我们系统地改变了触觉感受器群体的密度(100、45、20和10个传感器/厘米(2))和尺寸(直径0.1、0.2、0.5和1.0毫米),以确定给定的模型群体是否能够区分日常生活中使用的代表物体的球体和圆柱体。使用一个评分系统,允许直接比较人群,我们的结果表明,一个人群必须有至少20个传感器每厘米(2),以保持在这些日常生活活动的响应分辨率,较大尺寸的传感器不会降低响应分辨率。
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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