학술논문

Influence of the variables describing brain signals on the performance of the Naive Bayesian Classifier
Document Type
Conference
Source
2022 Progress in Applied Electrical Engineering (PAEE) Applied Electrical Engineering (PAEE), 2022 Progress in. :1-5 Jun, 2022
Subject
Components, Circuits, Devices and Systems
Engineered Materials, Dielectrics and Plasmas
Power, Energy and Industry Applications
Robotics and Control Systems
Electrical engineering
Feature extraction
Electroencephalography
Bayes methods
Task analysis
Functional near-infrared spectroscopy
signal processing
Bayesian Classifiers
patternrecognition
NIRS
EEG
Language
Abstract
In this paper various variables describing brain signals such as near-infrared spectroscopy (NIRS) and electroencephalography (EEG) on the Naive Bayesian Classifier were presented. Analysis of biomedical signals is a very challenging task – therefore the authors of this work decided to analyse two types of brain signals – EEG and NIRS, which have different features, character, nature and are differently prone to various artifacts occurrence. The applied classifiers can be applied for various features extraction and pattern comparisons, which is useful in diagnostic processes.