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Neuromimetic Event-Based Detection for Closed-Loop Tactile Feedback Control of Upper Limb Prostheses

机译:基于神经模拟事件的上肢假体闭环触觉反馈控制

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摘要

Upper limb amputees lack the valuable tactile sensing that helps provide context about the surrounding environment. Here we utilize tactile information to provide active touch feedback to a prosthetic hand. First, we developed fingertip tactile sensors for producing biomimetic spiking responses for monitoring contact, release, and slip of an object grasped by a prosthetic hand. We convert the sensor output into pulses, mimicking the rapid and slowly adapting spiking responses of receptor afferents found in the human body. Second, we designed and implemented two neuromimetic event-based algorithms, Compliant Grasping and Slip Prevention, on a prosthesis to create a local closed-loop tactile feedback control system (i.e. tactile information is sent to the prosthesis). Grasping experiments were designed to assess the benefit of this biologically inspired neuromimetic tactile feedback to a prosthesis. Results from able-bodied and amputee subjects show the average number of objects that broke or slipped during grasping decreased by over 50% and the average time to complete a grasping task decreased by at least 10% for most trials when comparing neuromimetic tactile feedback with no feedback on a prosthesis. Our neuromimetic method of closed-loop tactile sensing is a novel approach to improving the function of upper limb prostheses.
机译:上肢截肢者缺乏有价值的触觉,无法提供周围环境的信息。在这里,我们利用触觉信息为假手提供主动的触摸反馈。首先,我们开发了指尖触觉传感器,用于产生仿生尖峰响应,以监视由假手抓住的物体的接触,释放和滑动。我们将传感器的输出转换为脉冲,模仿在人体中发现的受体传入的快速和缓慢适应的尖峰响应。其次,我们在假体上设计和实现了两种基于神经模拟事件的算法,即顺应性抓握和防滑措施,以创建本地闭环触觉反馈控制系统(即将触觉信息发送到假体)。设计抓握实验以评估这种生物学启发的仿神经触觉反馈对假体的益处。身体强壮和被截肢者的结果表明,在大多数情况下,比较无神经模仿触觉反馈的情况下,在抓握过程中摔断或滑倒的物体的平均数量减少了50%以上,完成抓握任务的平均时间减少了至少10%。假体反馈。我们的神经模拟方法的闭环触觉是一种改善上肢假体功能的新颖方法。

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