Denoising MEG sensor data using wavelets

Author

Sreenathan, G. ; Sadanandan, G.K.

Author_Institution

Dept. of Electron. & Commun., Toc H Inst. of Sci. & Technol., Ernakulam, India

fYear

2013

fDate

4-6 June 2013

Firstpage

1

Lastpage

5

Abstract

Magnetoencephalography (MEG) is a noninvasive technology for analyzing cerebral neuronal activity. The noise level in the MEG data is large enough to affect the desired signal. This paper describes a denoising technique based on Wavelet Transform (WT). It compares denoising MEG data with different wavelet techniques like Discrete Wavelet Transform (DWT), Wavelet Packet Transform (WPT) and Stationary Wavelet Transform (SWT). Here WT is implemented using Multiresolution Analysis (MRA). Spectrogram of original MEG data and its denoised version are also compared.

Keywords

magnetoencephalography; medical signal processing; signal denoising; wavelet transforms; MEG sensor data; cerebral neuronal activity; magnetoencephalography; multiresolution analysis; signal denoising technique; wavelet transform; Discrete wavelet transforms; Multiresolution analysis; Noise measurement; Noise reduction; Wavelet packets; Discrete Wavelet Transform; Magnetoencephalography; Spectrogram; Stationary Wavelet Transform; Wavelet Packet Transform;

fLanguage

English

Publisher

ieee

Conference_Titel

Emerging Research Areas and 2013 International Conference on Microelectronics, Communications and Renewable Energy (AICERA/ICMiCR), 2013 Annual International Conference on

Conference_Location

Kanjirapally

Print_ISBN

978-1-4673-5150-8

Type

conf

DOI

10.1109/AICERA-ICMiCR.2013.6575998

Filename

6575998