PMID: 11604149Oct 18, 2001Paper

Electroencephalogram analysis using fast wavelet transform

Computers in Biology and Medicine
Z ZhangZ Q Liu

Abstract

The continuous wavelet transform is a new approach to the problem of time-frequency analysis of signals such as electroencephalogram (EEG) and is a promising method for EEG analysis. However, it requires a convolution integral in the time domain, so the amount of computation is enormous. In this paper, we propose a fast wavelet transform (FWT) that the corrected basic fast algorithm (CBFA) and the fast wavelet transform for high accuracy (FWTH). As a result, our fast wavelet transform can achieve high computation speed and at the same time to improve the computational accuracy. The CBFA uses the mother wavelets whose frequencies are 2 octaves lower than the Nyquist frequency in the basic fast algorithm. The FWT for high accuracy is realized by using upsampling based on a L-Spline interpolation. The experimental results demonstrate advantages of our approach and show its effectiveness for EEG analysis.

References

Dec 1, 1994·Electroencephalography and Clinical Neurophysiology·S J SchiffS Sato

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Citations

Apr 26, 2005·Computer Methods and Programs in Biomedicine·Abdulhamit Subasi, Ergun Erçelebi
Jun 14, 2008·Computers in Biology and Medicine·K P IndiradeviK Radhakrishnan
Apr 9, 2008·IEEE Transactions on Bio-medical Engineering·Jie Cui, Willy Wong
Oct 7, 2004·Clinical Neurophysiology : Official Journal of the International Federation of Clinical Neurophysiology·R F ByringT Salmi
Oct 7, 2004·Clinical Neurophysiology : Official Journal of the International Federation of Clinical Neurophysiology·R F ByringT Salmi

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