Alpha and Theta Wave Localisation using Hilbert-Huang Transform: Empirical Study of the Accuracy

This paper proposes to apply the Hilbert-Huang Transform (HHT) to locate alpha and theta waves in an Electroence phalogram (EEG), in order to estimate the vigilance level of an operator. The Hilbert-Huang Transform (HHT) is a recent technique for non-stationary signal processing. Using the Empirical...

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Bibliographic Details
Main Authors: Sharabaty, H., Martin, J., Jammes, B., Esteve, D.
Format: Conference Proceeding
Language:English
Subjects:
Electroencephalography
Feature extraction
Frequency
Jamming
Monitoring
Signal analysis
Signal processing
Signal processing algorithms
Signal resolution
Stress
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Summary:This paper proposes to apply the Hilbert-Huang Transform (HHT) to locate alpha and theta waves in an Electroence phalogram (EEG), in order to estimate the vigilance level of an operator. The Hilbert-Huang Transform (HHT) is a recent technique for non-stationary signal processing. Using the Empirical Mode Decomposition (EMD), the HHT allows decomposing a multi-modal signal into a sum of mono-contribution functions called Intrinsic Mode Functions (IMFs), then to compute the instantaneous frequency of each IMF by using Hilbert Transform (HT). We briefly review the basic principle of this method, then propose an empirical study of the accuracy of the Hilbert transform and a method to increase this accuracy when the amplitude of the analysed signal is small. The last section of this paper presents the results obtained with our algorithm.
DOI:10.1109/ICTTA.2006.1684538