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

Abstract

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.