Electromyogram signal enhancement in FMRI noise using spectral subtraction

This paper deals with noise removal in ElectroMyoGram (EMG) signals acquired in the hostile noisy environment of functional Magnetic Resonance Imaging (fMRI). The noise due to magnetic fields and radio frequencies corrupts significantly the EMG signal which render its extraction very difficult. The proposed approach operes in the frequency domain to estimate the noise spectrum to subtract it from noisy observation spectrum. The noise estimation is based on spectral minima tracking in each frequency bin without any distinction between muscle activity and muscle rest. But it looks for connected time-frequency regions of muscle activity presence to estimate a bias compensation factor. The method is tested with a simulated noisy observation in order to evaluate its performance using objective criteria. It is also validated for real noisy observations where no clean is available.