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首页> 外文期刊>Technology in society >Becoming a network beyond boundaries: Brain-Machine Interfaces (BMIs) as the actor-networks after the internet of things
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Becoming a network beyond boundaries: Brain-Machine Interfaces (BMIs) as the actor-networks after the internet of things

机译:成为超越界限的网络:物联网之后的行为者网络-脑机接口(BMI)

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摘要

For the last few decades, actor-network theory has been usually criticized for its focus on Machiavellian human actors controlling the overall networking between other actors or blamed for its dissipation of human agencies within the global status of a network. However, at the moment of its development, the freshness of actor-network theory was more relevant to its focus on the meaning of what the hyphen signifies; not so much just a simple connection between two independent variables, but an ontological event itself, from which certain entities juxtaposed together become involved by exchanging stable influences each other thus settled down as the actors participating in a network being associated as the summing up of these settled influences. The aim of this paper is to refresh this bygone freshness of ANT from the recent development of the Internet of Things (IoT); which vividly exemplifies how a network and its actors are generated from a manifold technologically augmented entities-such as smart appliances in a house, migratory animals with RFID tags, and ensembles of neurons signaling beyond one's brain through a bundle of microwires-each of which is physiologically or algorithmically adaptable to the environmental signals from other entities thus able to be settled down together into "new sensor/ processor/actuator affiliations." Brain-Machine Interface (BMI), developed by Nicolelis Lab at Duke University as a prototype of the future neuroprosthetics, shows a specific example of these networks of things; in which mutual adaptations of the technologically augmented entities-namely neurons and robot limbs-associate artificial sensory-motor circuits, programming its human/animal users' possible motor behaviors as well as their motor intentions.
机译:在过去的几十年中,行为者-网络理论通常被批评为聚焦于控制其他行为者之间的整体网络的马基雅维利人类行为者,或者因其在网络的全球地位下散布人类代理而受到指责。然而,在其发展之时,行动者网络理论的新鲜度与其对连字符含义的关注更为相关。与其说是两个独立变量之间的简单连接,还不如说是本体事件本身,并置在一起的某些实体通过彼此交换稳定的影响而并入其中,因此,随着参与网络的参与者被关联起来,这些实体就安顿下来了。解决的影响。本文的目的是从物联网(IoT)的最新发展中刷新ANT的这种过时的新鲜感。它生动地举例说明了如何从多种技术增强的实体中生成网络及其参与者,例如房屋中的智能设备,带有RFID标签的迁徙动物,以及通过一束微线在神经元之外发出信号的神经元集合,每个神经元都是在生理上或算法上适应于来自其他实体的环境信号,因此能够一起安顿到“新的传感器/处理器/执行器关联”中。杜克大学Nicolelis实验室开发的脑机接口(BMI)作为未来神经假体的原型,展示了这些物联网的具体示例。其中,技术增强实体(即神经元和机器人肢体)的相互适应关联了人工感觉运动电路,对人类/动物使用者可能的运动行为及其运动意图进行了编程。

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