Brain Computer Interfaces Employing Machine Learning Methods : A Systematic Review

Abstract

Research under the field of Brain Computer Interfaces is adapting various Machine Learning and Deep Learning techniques in recent times. With the advent of modern BCI, the data generated by various devices is now capable of detecting brain signals more accurately. This paper gives an overview of all the steps involved in the process of applying Machine Learning as well as Deep Learning methods from Data Acquisition to application of algorithms. It aims to study techniques currently employed to extract data, features from brain data, different algorithms employed to draw insights from the extracted features, and how it can be used in various BCI applications. By this study, I aim to put forward current Machine Learning and Deep Learning Trends in the field of BCI.