One Approach to using R for Bayesian Analysis of Brain Signals
Galina S. Panayotova1, Georgi P. Dimitrov2, Willian A. Dimitrov1, Pavel S. Petrov1, Pepa V. Petrova1, Paulina T. Tsvetkova2
1Department of Information Technologies, University of Library Studies and Information Technologies, Sofia, Bulgaria
2Department of Information Technologies, University of Library Studies and Information Technologies, “Institute of Robotics, Bulgarian Academy of Sciences, Sofia, Bulgaria
This study focuses on the classification of data obtained from Brain Computer Interface (BCI) using the Bayesian analysis. The aim of the paper is to study the classification of brain signals and the possibilities of reducing the number of channels. Experimental data is obtained by using Emotiv Epoc 14+. The programming language R was used for data processing. The data is classified using the Bayesian analysis in R.
Prof. Georgi Dimitrov is a PhD in modelling and Simulation process and Professor of Computer Science in the ULSIT. Dean of FIS. Prof. Dimitrov is the author of more 140 scientific publications, books and textbooks. Member of “Academic Community in Computer Systems and Information Technologies (ACCSIT)”. Prof. Dimitrov was involved in the Erasmus+ project Design Thinking for digital innovation, iBigWorld: Innovations for Big Data in a Real World as local coordinator, FAAI: The Future is in Applied Artificial Intelligence as local coordinator, etc. Member of editorial boards and technical committees of several prestigious conferences. He currently works in area on Big Data, Web Data Analyst, IoT, Artificial Intelligence, Virtual Reality, Augmented Reality, Cyber Security and etc.