Design of a cross-pass filter to reduce the effects of noise and artifacts on the EEG signal

In recent years many researchers and scientists have been attracted to the field of signal processing and have done many studies in this field. Various applications of this topic have shown that the processing of vital signals such as electroencephalographic (EEG), cardiac (ECG) and other types can be used to control and monitor various diseases. What has always been one of the main topics of interest is the presence of noise and artifacts along with the main signal after recording it. Various methods such as noise reduction or the use of different filters have also been employed. But the maximum reduction in the effect of these noises is still significant. In this paper, using signal quantization techniques, signal transitions from time domain to frequency and vice versa and, of course, incremental and subtractive sampling techniques are used to reduce the effects of artifacts. This method works similar to a cross-pass filter. Because due to the frequency spectrum of the signal, it eliminates part of the signal carrying the noise. The simulation results show that it performs better than the previous methods.

Keywords:

Noise removal , Artifact removal , Cerebral signal processing , Electroencephalographic signal , EEG