Performance monitoring from the EEG power spectrum with a radial basis function neural network

Author

Kirk, Brian P. ; LaCourse, John R.

Author_Institution

Biomed. Eng. Lab., New Hampshire Univ., Durham, NH, USA

fYear

1997

fDate

21-22 May 1997

Firstpage

19

Lastpage

20

Abstract

Length of vigilance is a major obstacle in jobs associated with low levels of arousal. To provide the highest levels of safety, the level of attention, particularly visual awareness, has to be monitored. A system has been designed, offline, as a precedent to a real-time awareness predictor. The electroencephalograph (EEG) is used as the major predictive data with a radial basis function network classifying the attention level

Keywords

computerised monitoring; electroencephalography; feedforward neural nets; human resource management; medical signal processing; pattern classification; personnel; spectral analysis; EEG power spectrum; attention level classification; electroencephalograph; jobs; low arousal levels; major predictive data; performance monitoring; radial basis function neural network; real-time awareness predictor; safety; vigilance; visual awareness; Automatic control; Biomedical engineering; Biomedical monitoring; Control systems; Electroencephalography; Electrooculography; Error analysis; Kirk field collapse effect; Radial basis function networks; Signal resolution;

fLanguage

English

Publisher

ieee

Conference_Titel

Bioengineering Conference, 1997., Proceedings of the IEEE 1997 23rd Northeast

Conference_Location

Durham, NH

Print_ISBN

0-7803-3848-0

Type

conf

DOI

10.1109/NEBC.1997.594938

Filename

594938