Characterization of Cochlear Implant Artifact and Removal Based on Multi-Channel Wiener Filter in Unilateral Child Patients

Abstract

Cochlear implants (CI) allow deaf patients to improve language perception and improving their emotional valence assessment. Electroencephalographic (EEG) measures were employed so far to improve CI programming reliability and to evaluate listening effort in auditory tasks, which are particularly useful in conditions when subjective evaluations are scarcely appliable or reliable. Unfortunately, the presence of CI on the scalp introduces an electrical artifact coupled to EEG signals that masks physiological features recorded by electrodes close to the site of implant. Currently, methods for CI artifact removal have been developed for very specific EEG montages or protocols, while others require many scalp electrodes. In this study, we propose a method based on the Multi-channel Wiener filter (MWF) to overcome those shortcomings. Nine children with unilateral CI and nine age-matched normal hearing children (control) participated in the study. EEG data were acquired on a relatively low number of electrodes (n = 16) during resting condition and during an auditory task. The obtained results obtained allowed to characterize CI artifact on the affected electrode and to significantly reduce, if not remove it through MWF filtering. Moreover, the results indicate, by comparing the two sample populations, that the EEG data loss is minimal in CI users after filtering, and that data maintain EEG physiological characteristics.

Keywords: EEG; artifact reduction; cochlear implant; cochlear implant artifact; multi-channel Wiener filter (MWF).

Figure 1

Averaged PSD values for contralateral channel and the channel ipsilateral to CI before and after the application of the proposed method in the UCI group. It is easy to note the higher magnitude of PSD values for PSD_pre-MWF, indicating the presence of the CI artifact that covers the underlying EEG data.

Figure 2

(A) N channels of original EEG data, with the CI contaminated electrode highlighted in red. (B) M (N − 1) channels EEG data with AE channel (highlighted in red), composed in the first half by the CI contaminated electrode (T4 in the current example) and in the last half by its contralateral electrode (T3). The corresponding mask indicates with 1 where the CI is prominent and 0 where the CI artifact affects the EEG data less.

Figure 3

Wilcoxon test results for contralateral electrodes similarity before and after MWF application, showing that MWF application affects only the artifact component (UCI group) and the EEG signal loss is minimal (NH group). Results are shown for both rest and sound conditions. * denotes a significant difference with corrected p < 0.001.

Figure 4

Mann–Whitney test results for contralateral electrodes similarity before and after MWF application in NH and UCI groups, showing comparable relationship between contralateral electrodes after MWF application. Results are shown both for rest and sound conditions. * denotes a significant difference with corrected p < 0.01.

Figure 5

Mann–Whitney test results for the asymmetry score (AS) in NH and UCI groups, showing a significant increase in asymmetry in the UCI population. * denotes a significant difference with p < 0.01.

Figure 6

EEG data with T4 channel affected by CI artifact before and after MWF method application, using T3 as noise-free channel. The figure shows how MWF method correctly filters out the CI artifactual component while retaining EEG data.