Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/13116
Title: Computation for EEG Brain Activity Identification
Authors: ZHENG HUI
Keywords: EEG SVM Feature Fatigue Sleep
Issue Date: 12-Feb-2008
Source: ZHENG HUI (2008-02-12). Computation for EEG Brain Activity Identification. ScholarBank@NUS Repository.
Abstract: This study was motivated by the fact that a large portion of industrial and traffic accidences are due to lack of alertness of human operators. The lack of alertness could be because of high level drowsiness or lack of attention. In this study we focus only on the first one, which is the lack of alertness is due to mental fatigue. Under high level mental fatigue, a human subject will be drowsy and respond slower or sometimes fall into sleep and not responding. Therefore, in this study we proposed a model to detect the onset of sleep on human subjects and another model for measuring the mental fatigue level of a human subject. Both models gives an accurate detection of targeted mental states.
URI: http://scholarbank.nus.edu.sg/handle/10635/13116
Appears in Collections:Master's Theses (Open)

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