Title :
EEG multiresolution analysis using wavelet transform
Author :
Weidong, Zhou ; Yingyuan, Li
Author_Institution :
Dept. of Electron. Eng., Shandong Univ., Jinan, China
Abstract :
Wavelet transform (WT) is a new multiresolution time-frequency analysis method. WT possesses well localization feature both in time and frequency domains. It acts as a group of band-pass filters to decompose mixed signal into signals at different frequency bands. EEG, as a noninvasive testing method, plays a key role in the diagnosing diseases, and is useful for both physiological research and medical applications. Using the dyadic wavelet transform, the EEG signals are successfully decomposed to the alpha rhythm (8-13 Hz), beta rhythm (14-30 Hz), theta rhythm (4-7 Hz), and delta rhythm (0.3-3 Hz), and the EMG trembles in EEG are effectively removed while the useful information of EEG are well reserved so as to improve SNR. The experiment results are given in the end of the paper.
Keywords :
electroencephalography; medical signal processing; signal reconstruction; signal resolution; time-frequency analysis; wavelet transforms; EEG multiresolution analysis; EMG trembles; Mallat fast algorithm; alpha rhythm; band-pass filters; beta rhythm; complex valued function; delta rhythm; denoising; dyadic wavelet; improved SNR; multiresolution time-frequency analysis; theta rhythm; wavelet transform; Band pass filters; Electroencephalography; Frequency domain analysis; Medical tests; Multiresolution analysis; Rhythm; Signal resolution; Time frequency analysis; Wavelet analysis; Wavelet transforms;
Conference_Titel :
Engineering in Medicine and Biology Society, 2001. Proceedings of the 23rd Annual International Conference of the IEEE
Print_ISBN :
0-7803-7211-5
DOI :
10.1109/IEMBS.2001.1020584