Vigilance Estimation Based on EEG Signals

نویسندگان

  • Hong Yu
  • Li-Chen Shi
  • Bao-Liang Lu
چکیده

In some tasks that require sustained attention, vigilance levels of the operator might become very important. EEG has been proved very effective for measuring vigilance. However, many difficulties exist in this field such as how to label the EEG data, how to remove the noise from the EEG data and so on. In this paper, we introduce a very useful signal transform method, Common Spatial Pattern, to process the EEG data. Also we use unsupervised learning methods for analyzing the EEG data under two extreme cases, sleeping and awake, and discard other middle vigilance states. The results of our experiments are quite promising and give a direction for the vigilance labelling and feature selection in the future work.

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تاریخ انتشار 2007