Man-machine communications through brain-wave processing

Author

Keirn, Z.A. ; Aunon, J.I.

Author_Institution

Dept. of Electr. Eng., Colorado State Univ., Fort Collins, CO, USA

Volume

9

Issue

1

fYear

1990

fDate

3/1/1990 12:00:00 AM

Firstpage

55

Lastpage

57

Abstract

The possibility of monitoring voluntarily produced changes in the electroencephalogram (EEG) of a subject and translating these changes into a set of commands to be issued to an external device was investigated. Subjects performed five distinct tasks under both eyes-open and eyes-closed conditions. A feature set consisting of the asymmetry ratios and the power values for each lead at four frequency bands-delta (0-3 Hz) theta (4-7 Hz), alpha (8-13 Hz), and beta (14-20 Hz)-was used to characterize the EEG. The feature sets created from an estimate of the spectral density of the EEG for each task were used to test classification accuracy among the various tasks using a Bayes quadratic classifier. The results show that it is possible to distinguish, to a high degree of accuracy, among the various mental tasks studied, using only the EEG.<>

Keywords

Bayes methods; electroencephalography; man-machine systems; signal processing; spectral analysis; 0 to 20 Hz; Bayes quadratic classifier; asymmetry ratios; brain-wave processing; classification accuracy; electroencephalogram; eyes-closed conditions; eyes-open conditions; man machine communication; mental tasks; spectral density; voluntarily produced changes; Area measurement; Control systems; Electrodes; Electroencephalography; Eyes; Lead; Man machine systems; Monitoring; Process control;

fLanguage

English

Journal_Title

Engineering in Medicine and Biology Magazine, IEEE

Publisher

ieee

ISSN

0739-5175

Type

jour

DOI

10.1109/51.62907

Filename

62907