Classification of confusion level using EEG data and artificial neural networks

College

Gokongwei College of Engineering

Department/Unit

Electronics And Communications Engg

Document Type

Conference Proceeding

Source Title

2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management, HNICEM 2019

Publication Date

11-1-2019

Abstract

The purpose of this study is to create an artificial neural network (ANN) that can classify a person's level of confusion using Electroencephalography (EEG) data, more specifically, using the power spectrum of all the brain wave frequencies. This could help people in understanding the complicated mechanisms present in the brain, including the role that each specific brain wave signal plays in the formation of different cognitive activities in one's mind such as confusion and workload. This study is categorized as a cognitive-affective state research, inspired by its current possible application to different existing societal fields such as education and gaming industries. The processing platforms used to process and interpret the dataset used in this research are Microsoft Excel and MATLAB software, applying frequency-based analysis and standard averaging methods fit for EEG data classification and artificial neural network modeling. © 2019 IEEE.

html

Digitial Object Identifier (DOI)

10.1109/HNICEM48295.2019.9072766

Disciplines

Electrical and Computer Engineering

Keywords

Electroencephalography; Neural networks (Computer science); Cognition disorders—Diagnosis

Upload File

wf_yes

This document is currently not available here.

Share

COinS