Developing Brain Computer Interface Using Fuzzy Logic

The study of Human–Computer Interfaces (HCI) provides a challenge for future interaction research and development. Brain-Computer Interfaces (BCI) is a part or a subset of Human-Computer Interaction (HCI) that involves the communication between the user and the system via brain signals. The electroencephalography (EEG) have developed into one of the most important and widely used quantitative diagnostic tools in analysis of brain signals and patterns. Various soft computing techniques are being used to recognize and classifies different brain activation patterns associated with carefully selected mental tasks like Neural Network, Fuzzy Logic etc. Fuzzy Logic is a form of algebra employing a range of values from “true” to “false” that is used in decision-making with imprecise data, as in artificial intelligence systems. The aim of this paper is to give an idea of developing an application based Brain Computer Interface (BCI) using Fuzzy Logic.