A Quasi-probabilistic distribution model for EEG Signal classification by using 2-D signal representation

摘要

Background and Objective: Electroencephalography (EEG) is a method that measures and records the electrical activity of the human brain. These biomedical signals are currently being actively used in many research fields and have a wide range of potential uses in brain-computer interfaces (BCIs). The main aim of the present work is to improve the classification of EEG patterns for EEG-based BCI systems.