DocumentCode :
2209819
Title :
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
Link To Document :
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