脑-机器人交互的心理状态、脑电图表现和心理模拟数字电路

S. Bozinovski, Adrijan Božinovski
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引用次数: 19

摘要

本文重点研究了心理状态和动作的脑电图表现,利用脑电图表现模拟控制和通信结构,以及它们在脑-机器人交互中的应用。本文介绍了一种心理模拟解复用器,它是一种利用心理动作将单个脑电信号信道解复用为多个数字命令的装置。该装置适用于通过一个EEG通道控制多个对象。实验证明了这一概念,并给出了一个包含障碍物的轨迹,该轨迹应由具有两个自由度的机械臂通过,由人类大脑的精神状态控制,使用单个脑电图通道。这项工作是在人机交互(HRI)的框架下提出的,特别是在脑-机器人交互(BRI)的框架下。这项工作是先前开发心理模拟数字设备的工作的延续,例如心理动作开关和心理状态触发器。
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Mental States, EEG Manifestations, and Mentally Emulated Digital Circuits for Brain-Robot Interaction
This paper focuses on electroencephalogram (EEG) manifestations of mental states and actions, emulation of control and communication structures using EEG manifestations, and their application in brain-robot interactions. The paper introduces a mentally emulated demultiplexer, a device which uses mental actions to demultiplex a single EEG channel into multiple digital commands. The presented device is applicable in controlling several objects through a single EEG channel. The experimental proof of the concept is given by an obstacle-containing trajectory which should be negotiated by a robotic arm with two degrees of freedom, controlled by mental states of a human brain using a single EEG channel. The work is presented in the framework of Human-Robot interaction (HRI), specifically in the framework of brain-robot interaction (BRI). This work is a continuation of a previous work on developing mentally emulated digital devices, such as a mental action switch, and a mental states flip-flop.
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来源期刊
IEEE Transactions on Autonomous Mental Development
IEEE Transactions on Autonomous Mental Development COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-ROBOTICS
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期刊最新文献
Types, Locations, and Scales from Cluttered Natural Video and Actions Guest Editorial Multimodal Modeling and Analysis Informed by Brain Imaging—Part 1 Discriminating Bipolar Disorder From Major Depression Based on SVM-FoBa: Efficient Feature Selection With Multimodal Brain Imaging Data A Robust Gradient-Based Algorithm to Correct Bias Fields of Brain MR Images Editorial Announcing the Title Change of the IEEE Transactions on Autonomous Mental Development in 2016
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