首页> 外文期刊>Neural Systems and Rehabilitation Engineering, IEEE Transactions on >A Brain–Machine Interface to Navigate a Mobile Robot in a Planar Workspace: Enabling Humans to Fly Simulated Aircraft With EEG
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A Brain–Machine Interface to Navigate a Mobile Robot in a Planar Workspace: Enabling Humans to Fly Simulated Aircraft With EEG

机译:在平面工作区中导航移动机器人的脑机界面:使人类能够通过脑电图飞行模拟飞机

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This paper presents an interface for navigating a mobile robot that moves at a fixed speed in a planar workspace, with noisy binary inputs that are obtained asynchronously at low bit-rates from a human user through an electroencephalograph (EEG). The approach is to construct an ordered symbolic language for smooth planar curves and to use these curves as desired paths for a mobile robot. The underlying problem is then to design a communication protocol by which the user can, with vanishing error probability, specify a string in this language using a sequence of inputs. Such a protocol, provided by tools from information theory, relies on a human user's ability to compare smooth curves, just like they can compare strings of text. We demonstrate our interface by performing experiments in which twenty subjects fly a simulated aircraft at a fixed speed and altitude with input only from EEG. Experimental results show that the majority of subjects are able to specify desired paths despite a wide range of errors made in decoding EEG signals.
机译:本文提出了一种用于导航在平面工作空间中以固定速度移动的移动机器人的界面,该接口具有嘈杂的二进制输入,该二进制输入是通过人类脑电图(EEG)以低比特率从人类用户异步获得的。该方法是为平滑的平面曲线构造有序的符号语言,并将这些曲线用作移动机器人的所需路径。然后,潜在的问题是设计一种通信协议,通过该协议,用户可以以消失的错误概率使用一系列输入来指定该语言的字符串。信息理论工具提供的这种协议依赖于人类用户比较平滑曲线的能力,就像他们可以比较文本字符串一样。我们通过进行实验来演示我们的界面,在该实验中,二十名受试者仅从脑电图输入,就以固定的速度和高度驾驶模拟飞机。实验结果表明,尽管在解码EEG信号时出现了各种各样的错误,但大多数受试者还是能够指定所需的路径。

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