title: EEG-based analysis of human driving performance in turning left and right using Hopfield neural network.
abstract: In this article a quantitative analysis was devised assessing driver's cognition responses by exploring the neurobiological information underlying electroencephalographic (EEG) brain signals in a left and right turning experiment on simulator environment. Driving brain signals have been collected by a 19-channel electroencephalogram recording system. The driving pathway has been selected with no obstacles, a set of indicators are used to inform the subjects when they had to turn left or right by means of keyboard left and right arrows. Subsequently in order to remove artifacts, preprocessing is performed on data to achieve high accuracy. Features of signals are extracted by using Fast Fourier Transform (FFT). Absolute power of FFT is used as a basic feature. Scalar Feature selection method is applied to reduce feature dimension. Thereafter dimension-reduced features are fed to Hopfield Neural Network (HNN) recognizing different brain potentials stimulated by turning to left and right. The performances of HNN are evaluated by considering five conditions; before feature extraction, after feature extraction, before reduction of features, after analyzing reduced features and finally subject-wise Hopfield performances respectively. An increase occurred in each level and continued until it has reached its highest 97.6% of accuracy on last condition.
authors.affiliation: Department of Mechatronics Engineering, Tabriz Branch, Islamic Azad University, Tabriz, Iran.
authors.forename: Mitra
authors.initials: M
authors.lastname: Taghizadeh-Sarabi
authors.affiliation: Department of Control Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.
authors.forename: Kavous Salehzadeh
authors.initials: KS
authors.lastname: Niksirat
authors.affiliation: Department of Control Engineering, Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran.
authors.forename: Sohrab
authors.initials: S
authors.lastname: Khanmohammadi
authors.affiliation: Department of Psychology, University of Tabriz, Tabriz, Iran.
authors.forename: Mohammadali
authors.initials: M
authors.lastname: Nazari
keywords: Driving; Fast Fourier Transforms (FFT); Feature extraction; Hopfield network