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Fuzzy bio-interface: Indicating logicality from living neuronal network and learning control of bio-robot

机译:模糊生物接口:从活神经网络指示逻辑性以及生物机器人的学习控制

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Recently, many attractive brain-computer interface and brain-machine interface have been proposed. The outer computer and machine are controlled by brain action potentials detected through a device such as near-infrared spectroscopy (NIRS) and electroencephalograph (EEG), and some discriminant model determines a control process. In this paper, we introduce a fuzzy bio-interface between a culture dish of rat hippocampal neurons and the khepera robot. We propose a model to analyze logic of signals and connectivity of electrodes in a culture dish, and show the bio-robot hybrid we developed. We believe that the framework of fuzzy system is essential for BCI and BMI, thus name this technology “fuzzy bio-interface”. We show the usefulness of a fuzzy bio-interface through some examples.
机译:近来,已经提出了许多有吸引力的脑机接口和脑机接口。外部计算机和机器由通过近红外光谱(NIRS)和脑电图仪(EEG)等设备检测到的大脑动作电位控制,某些判别模型确定了控制过程。在本文中,我们介绍了大鼠海马神经元培养皿和khepera机器人之间的模糊生物接口。我们提出了一个模型来分析培养皿中的信号逻辑和电极的连通性,并展示我们开发的生物机器人混合动力系统。我们认为模糊系统的框架对于BCI和BMI是必不可少的,因此将该技术命名为“模糊生物接口”。通过一些示例,我们展示了模糊生物界面的有用性。

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