Using linear discriminant function to detect eyes closing activities through alpha wave

Author

Delisle-Rodriguez, Denis ; Castillo-Garcia, Javier F. ; Bastos-Filho, Teodiano ; Frizera-Neto, A. ; Lopez-Delis, Alberto

Author_Institution

Post-Grad. Program of Electr. Eng., Fed. Univ. of Espirito Santo, Vitoria, Brazil

fYear

2014

fDate

26-28 May 2014

Firstpage

1

Lastpage

4

Abstract

This work presents an alternative method to detect events correlated to eyes opening and closing, based on electroencephalography (EEG) measured from the occipital lobe. The goal is to propose a method based on linear discriminant function to classify segments of EEG signals that contain activities originated by eyes closing. A linear discriminant function presented by Fisher is employed to detect these activities on segments of 2s. This method showed a good values of sensitivity (SE ≥ 85 %) and specificity (SP ≥ 60 %). This approach can be used to control the switching of a brain computer interface (BCI).

Keywords

brain-computer interfaces; electroencephalography; eye; medical signal detection; medical signal processing; neurophysiology; signal classification; statistical analysis; visual evoked potentials; BCI switching control; EEG signal classification; EEG signal segmentation; alpha wave; brain computer interface; electroencephalography; eye closing activity detection; linear discriminant function; occipital lobe; time 2 s; Electroencephalography; Fractals; Sensitivity; Sensitivity and specificity; Switches; Testing; Training; BCI; EEG; alpha rythm; linear discriminant analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Biosignals and Biorobotics Conference (2014): Biosignals and Robotics for Better and Safer Living (BRC), 5th ISSNIP-IEEE

Conference_Location

Salvador

Print_ISBN

978-1-4799-5688-3

Type

conf

DOI

10.1109/BRC.2014.6880967

Filename

6880967