DocumentCode :
2090684
Title :
Study on Real-time Detection of Alertness Based on EEG
Author :
Bi, Luzheng ; Zhang, Ran ; Chen, Zhilong
Author_Institution :
Beijing Inst. of Technol., Beijing
fYear :
2007
fDate :
23-27 May 2007
Firstpage :
1490
Lastpage :
1493
Abstract :
Human alertness varies in tasks requiring sustained attention. This can lead to severe consequences in occupations like car traffic operation, air traffic control and nuclear power plant monitoring and so on. EEG that is the electrical activity of brain can reflect the state of alertness. In this paper, the present work aims at real-time estimation of alertness from EEG signals. We made subjects perform a test of variables of attention (TOVA) and recorded their response time that was selected as a metric to quantify the subject´s performance. Synchronously, we acquired the EEG signals of the subjects during the whole test. We studied the correlation between EEG power spectrum and response time, and used the power spectrum to construct the models of estimation alertness for single subjects by means of support vector machines method. The experimental results show the possibility of using EEG signals to real-time estimation alertness. We conclude that the method is helpful for the construct of the practical real-time detection system to alertness.
Keywords :
cognition; electroencephalography; neurophysiology; regression analysis; support vector machines; EEG power spectrum; EEG signals; brain electrical activity; real-time alertness detection; support vector machines regression model; Air traffic control; Brain modeling; Delay; Electroencephalography; Humans; Monitoring; Performance evaluation; Power generation; Power system modeling; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Complex Medical Engineering, 2007. CME 2007. IEEE/ICME International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-1077-4
Electronic_ISBN :
978-1-4244-1078-1
Type :
conf
DOI :
10.1109/ICCME.2007.4381994
Filename :
4381994
Link To Document :
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