A Finite Impulse Response (FIR) Filtering Technique for Enhancement of Electroencephalographic (EEG) Signal

摘要

Electroencephalographic (EEG) signal is electrical record generated by the brain. It is a vital signal as far as the monitoring, diagnosis and treatment of some health conditions that relate to the human brain are concerned. EEG artifact contaminants have the capability to distort he usefulness of this important bioelectrical signal. Such noises include power line interference, baseline wander, eye blink and eye movement (electro oculogram, EOG) as well as muscle artifacts also called electromyogram (EMG and electrocardiogram (ECG). These are identified as artifacts obtained alongside with EEG by the electrodes of the electroencephalograph which are placed on the scalp of the subject in the EEG procedures. This work focuses on the removal of 10mV 50Hz power line noise from EEG signal using Finite Impulse Response (FIR) filter which is based on a Nuttal window. This technique was simulated in MATLAB/Simulink environment for a real EEG signal that was contaminated with MATLAB generated 10mV 50Hz sine wave signal (power line artifact). The power line noise was seen to have been successfully cancelled out from the EEG with the use of the Nuttall window-based FIR filter modeled with filter order equal to 137 with a band stop filter format of lower sideband and upper sideband frequencies of 40Hz and 60Hz respectively. The filter gives a signal-to-noise ratio (SNR) equal to -2.49dB which is comparable to FIR filters modeled with Hamming, Kaiser, Hann, Gaussian and Bartlett windows.