An Automatic Driver Assistant Based on Intention Detecting using EEG Signal

Reza Amini Gougeh, Tohid Yousefi Rezaii, Ali Farzamnia

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

Each year, vehicle safety is increasing. Recently brain signals were used to assist drivers. Attempting to do movement produces electrical signals in specific regions of the brain. We developed a system based on motor intention to assist drivers and prevent car accidents. The main objective of this work is improving reaction time to external hazards. The motor intention was recorded by 16 channels of a portable device called Open-BCI. Extracting features was done by common spatial patterns which is a well-known method in motor imagery based brain computer interface (BCI) systems. By using enhanced common spatial pattern (CSP) called strong uncorrelated transform complex common spatial pattern (SUTCCSP), features of preprocessed data were extracted. Regarding the nonlinear nature of electroencephalogram (EEG), support vector machine (SVM) with kernel trick classifier was used to classify features into 3 classes: left, right and brake. Due to using developed SVM, commands can be predicted 500 ms earlier with the system accuracy of 94.6% on average.

Original languageEnglish
Title of host publicationProceedings of the 11th National Technical Seminar on Unmanned System Technology 2019
Subtitle of host publicationNUSYS 2019
EditorsZainah Md Zain, Hamzah Ahmad, Dwi Pebrianti, Mahfuzah Mustafa, Nor Rul Hasma Abdullah, Rosdiyana Samad, Maziyah Mat Noh
PublisherSpringer Singapore
Pages617-627
Number of pages11
Volume666
Edition1st
ISBN (Electronic)9789811552816
ISBN (Print)9789811552809, 9789811552830
DOIs
Publication statusPublished - 8 Jul 2020
Externally publishedYes
Event11th National Technical Symposium on Unmanned System Technology - Kuantan, Malaysia
Duration: 2 Dec 20193 Dec 2019
Conference number: 11

Publication series

NameLecture Notes in Electrical Engineering
PublisherSpringer
Volume666
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference11th National Technical Symposium on Unmanned System Technology
Abbreviated titleNUSYS 2019
Country/TerritoryMalaysia
CityKuantan
Period2/12/193/12/19

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