Title :
EEG De-Noising Based on Wavelet Transformation
Author_Institution :
Sch. of Electr., Shandong Univ. of Technol., Zibo, China
Abstract :
EEG is one of the mini-voltages. In order to improve the performance of EEG and increase the measure efficiency, we must eliminate the noise in EEG. Wavelet transformation is a kind of analytical tool in time-scale domain. It has the feature of multi-resolution analysis and the adaptation characteristic for signal. A noise rejection method with wavelet transformation was proposed here which is used to eliminate noises such as electrode disturbance, baseline movement, EMG noise and so on. At the same time, we use these methods mentioned above for emulation verify in clinical EEG de-noising. Experiments show that the wavelet transformation technology has good efficiency in EEG noise rejection.
Keywords :
electroencephalography; medical signal processing; signal denoising; wavelet transforms; EEG denoising; noise elimination; noise rejection method; wavelet transforms; Arithmetic; Electrodes; Electroencephalography; Electromyography; Emulation; Low pass filters; Noise reduction; Signal analysis; Wavelet analysis; Wavelet domain;
Conference_Titel :
Bioinformatics and Biomedical Engineering , 2009. ICBBE 2009. 3rd International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-2901-1
Electronic_ISBN :
978-1-4244-2902-8
DOI :
10.1109/ICBBE.2009.5162680