  Magnetoencephalography (MEG) is an important noninvasive, nonhazardous
technology for functional brain mapping, measuring the magnetic fields due to
the intracellular neuronal current flow in the brain. However, most often, the
inherent level of noise in the MEG sensor data collection process is large
enough to obscure the signal(s) of interest. In this paper, a denoising
technique based on the wavelet transform and the multiresolution signal
decomposition technique along with thresholding is presented, substantiated by
application results. Thereafter, different frequency analysis are performed on
the denoised MEG signals to identify the major frequencies of the brain
oscillations present in the denoised signals. Time-frequency plots
(spectrograms) of the denoised signals are also provided.
