Title :
Method of Removing Noise from EEG Signals Based on HHT Method
Author :
Zhang, Lihong ; Wu, Dingyun ; Zhi, Lianhe
Author_Institution :
Dept. of Phys. & Eng., Zhoukou Normal Univ., Zhoukou, China
Abstract :
Many noises are interfused into EEG signals when they are measuring. In order to remove the noises effectively, a novel method based on Hilbert Huang Transform, is shown in the thesis. The theories of empirical mode decomposition and instantaneous frequency solution which are two parts of Hilbert-Huang Transformation are discussed in the thesis. Empirical mode decomposion is used to EEG which can be decomposed into a limited number of intrinsic mode functions. Different threshold are used to treat intrinsic mode functions to achieve de-noising. Results: Hilbert-Huang Transformation is demonstrated to be effective in removing the general EEG noise. Compared with the traditional wavelet transform, Hilbert-Huang Transform for EEG de-noising has some advantages. Conclusion: Using HHT method for EEG signals denoising effective and doable.
Keywords :
Hilbert transforms; electroencephalography; signal denoising; wavelet transforms; EEG signals; HHT method; Hilbert Huang Transform; empirical mode decomposition; intrinsic mode functions; signals denoising; wavelet transform; Cerebral cortex; Electroencephalography; Filters; Frequency; Neoplasms; Noise reduction; Scalp; Signal analysis; Signal processing; Wavelet analysis;
Conference_Titel :
Information Science and Engineering (ICISE), 2009 1st International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-4909-5
DOI :
10.1109/ICISE.2009.739