Journal of ICT Research and Applications
Vol. 15 No. 1 (2021)

Extraction of the Major Features of Brain Signals using Intelligent Networks

Shirin Salarian (Department of Computer Engineering, Islamic Azad University South Tehran Branch, Tehran, Iran)
Amir Shahab Shahabi (Department of Computer Engineering, Islamic Azad University South Tehran Branch, Tehran, Iran)



Article Info

Publish Date
05 Jul 2021

Abstract

The brain-computer interface is considered one of the main tools for implementing and designing smart medical software. The analysis of brain signal data, called EEG, is one of the main tasks of smart medical diagnostic systems. While EEG signals have many components, one of the most important brain activities pursued is the P300 component. Detection of this component can help detect abnormalities and visualize the movement of organs of the body. In this research, a new method for processing EEG signals is proposed with the aim of detecting the P300 component. Major features were extracted from the BCI Competition IV EEG data set in a number of steps, i.e. normalization with the purpose of noise reduction using a median filter, feature extraction using a recurrent neural network, and classification using Twin Support Vector Machine. Then, a series of evaluation criteria were used to validate the proposed approach and compare it with similar methods. The results showed that the proposed approach has high accuracy.

Copyrights © 2021






Journal Info

Abbrev

jictra

Publisher

Subject

Computer Science & IT

Description

Journal of ICT Research and Applications welcomes full research articles in the area of Information and Communication Technology from the following subject areas: Information Theory, Signal Processing, Electronics, Computer Network, Telecommunication, Wireless & Mobile Computing, Internet ...