A HHT-based time frequency analysis scheme for clinical alcoholic EEG signals
MUSP'09 Proceedings of the 9th WSEAS international conference on Multimedia systems & signal processing
An effective method on reducing measurement noise based on Hilbert-Huang transform
CISST'10 Proceedings of the 4th WSEAS international conference on Circuits, systems, signal and telecommunications
Comparative study of noise reduction in ultrasonic inspection system
WSEAS Transactions on Circuits and Systems
A novel sleep apnea detection system in electroencephalogram using frequency variation
Expert Systems with Applications: An International Journal
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This paper proposes an algorithm for automatic location of alpha and theta waves in electroencephalogram. This algorithm is a part of developments that aim to process EEG and electroocculogram in order to estimate the drowsiness level of active subjects. Our algorithm is based on a method recently developed to analyse non-stationary signals: Hilbert Huang Transform (HHT). This transform proposes to decompose multi-modal signals into a sum of mono-contribution functions called Intrinsic Mode Functions, then to use the Hilbert Transform to compute the instantaneous frequency of each IMF. After a brief review of HHT principles, we propose a qualitative analysis of Hilbert transform accuracy and a method to decrease computation errors that appears when amplitude of the analysed signal is small. The last section of this paper presents the algorithm proposed to locate alpha and theta waves and preliminary results.