Effect of EEG pre-processing on Independent Component Analysis: reduction of cochlear implant artifact in Auditory Evoked Potentials - Trejo Alcantara, G.; Castañeda Villa, N. (Revista Mexicana de Ingenieria Biomedica, 2017)
Independent Component Analysis (ICA) is an algorithm used to remove artifacts from the EEG. However, there is little current literature about the impact of preprocessing stages of this signal on the performance of ICA. In this paper the effect of applying two different digital filters - lowpass and bandpass -, in a pre-processing step to ICA, was compared. This to remove the cochlear implant artifact from the Auditory Evoked Potentials. Recordings from 10 cochlear implant users were analyzed. In 5 of these records using the pre-lowpass filtering, the highest Signal Interference Ratio (SIR) was obtained; this index was used to assess the quality of ICA separation. The greatest effect of removing the cochlear implant artifact is noted in both T4 and T6 electrodes, which correspond to the area where the subjects have placed their implants (right temporal area).