Independent component analysis for cochlear implant artifacts attenuation from electrically evoked auditory steady-state response measurements

Cochlear Implant Artifacts Removal in EEG-Based Objective Auditory Rehabilitation Assessment

Cochlear implant (CI) is a neural prosthesis that can restore hearing for patients with severe to profound hearing loss. Observed variability in auditory rehabilitation outcomes following cochlear implantation may be due to cerebral reorganization. Electroencephalography (EEG), favored for its CI compatibility and non-invasiveness, has become a staple in clinical objective assessments of cerebral plasticity post-implantation. However, the electrical activity of CI distorts neural responses, and EEG susceptibility to these artifacts presents significant challenges in obtaining reliable neural responses. Despite the use of various artifact removal techniques in previous studies, the automatic identification and reduction of CI artifacts while minimizing information loss or damage remains a pressing issue in objectively assessing advanced auditory functions in CI recipients. To address this problem, we propose an approach that combines machine learning algorithms-specifically, Support Vector Machines (SVM)-along with Independent Component Analysis (ICA) and Ensemble Empirical Mode Decomposition (EEMD) to automatically detect and minimize electrical artifacts in EEG data. The innovation of this research is the automatic detection of CI artifacts using the temporal properties of EEG signals. By applying EEMD and ICA, we can process and remove the identified CI artifacts from the affected EEG channels, yielding a refined signal. Comparative analysis in the temporal, frequency, and spatial domains suggests that the corrected EEG recordings of CI recipients closely align with those of peers with normal hearing, signifying the restoration of reliable neural responses across the entire scalp while eliminating CI artifacts.

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

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.

A full-head model to investigate intra and extracochlear electric fields in cochlear implant stimulation

Objective.Despite the widespread use and technical improvement of cochlear implant (CI) devices over past decades, further research into the bioelectric bases of CI stimulation is still needed. Various stimulation modes implemented by different CI manufacturers coexist, but their true clinical benefit remains unclear, probably due to the high inter-subject variability reported, which makes the prediction of CI outcomes and the optimal fitting of stimulation parameters challenging. A highly detailed full-head model that includes a cochlea and an electrode array is developed in this study to emulate intracochlear voltages and extracochlear current pathways through the head in CI stimulation.Approach.Simulations based on the finite element method were conducted under monopolar, bipolar, tripolar (TP), and partial TP modes, as well as for apical, medial, and basal electrodes. Variables simulated included: intracochlear voltages, electric field (EF) decay, electric potentials at the scalp and extracochlear currents through the head. To better understand CI side effects such as facial nerve stimulation, caused by spurious current leakage out from the cochlea, special emphasis is given to the analysis of the EF over the facial nerve.Main results.The model reasonably predicts EF magnitudes and trends previously reported in CI users. New relevant extracochlear current pathways through the head and brain tissues have been identified. Simulated results also show differences in the magnitude and distribution of the EF through different segments of the facial nerve upon different stimulation modes and electrodes, dependent on nerve and bone tissue conductivities.Significance.Full-head models prove useful tools to model intra and extracochlear EFs in CI stimulation. Our findings could prove useful in the design of future experimental studies to contrast FNS mechanisms upon stimulation of different electrodes and CI modes. The full-head model developed is freely available for the CI community for further research and use.

Artifact removal by template subtraction enables recordings of the frequency following response in cochlear-implant users

Electrically evoked frequency-following responses (eFFRs) provide insight in the phase-locking ability of brainstem of cochlear-implant (CI) users. eFFRs can potentially be used to gain insight in the individual differences in the biological limitation on temporal encoding of the electrically stimulated auditory pathway, which can be inherent to the electrical stimulation itself and/or the degenerative processes associated with hearing loss. One of the major challenge of measuring eFFRs in CI users is the process of isolating the stimulation artifact from the neural response, as both the response and the artifact overlap in time and have similar frequency characteristics. Here we introduce a new artifact removal method based on template subtraction that successfully removes the stimulation artifacts from the recordings when CI users are stimulated with pulse trains from 128 to 300 pulses per second in a monopolar configuration. Our results show that, although artifact removal was successful in all CI users, the phase-locking ability of the brainstem to the different pulse rates, as assessed with the eFFR differed substantially across participants. These results show that the eFFR can be measured, free from artifacts, in CI users and that they can be used to gain insight in individual differences in temporal processing of the electrically stimulated auditory pathway.

Detection of Electrically Evoked Auditory Steady-State Responses in Cochlear-Implant Recipients With a System Identification Based Method

OBJECTIVE

Electrically evoked auditory steady-state responses (EASSRs) can potentially be used as an objective measure to realize the automatic fitting of cochlear implants (CIs). They can be recorded using electroencephalography (EEG) and objectively detected at the modulation frequency of the stimulus. The main roadblock in using EASSRs is the presence of CI stimulation artifacts in the EEG recording. In this article, we present an improvement of a recently introduced system identification (SI) based artifact removal method. We evaluate its applicability for objective CI fitting on a larger dataset.

METHODS

The parameter estimation problem of the SI is solved using ordinary least squares (OLS), where an additional regularization term is added to the cost function. We compare EASSR latencies as determined by the commonly used linear interpolation artifact removal method and SI, to evaluate the artifact removal and EASSR detection quality on a dataset of 16 CI recipients and four different stimulation levels.

RESULTS

SI can fully remove stimulation artifacts and detect EASSRs, even for recordings from ipsilateral EEG channels, where all other artifact removal methods fail so far. Using OLS with regularization prevents false positive response detection.

CONCLUSION

Using SI, EASSRs can reliably be detected in EEG recordings, even for ipsilateral recording channels and recordings with lower stimulation levels. As the recordings are obtained with clinically relevant settings of the CI, they reveal the potential impact of SI on the objective fitting of CIs.

SIGNIFICANCE

We argue, that SI enables therefore a big step towards automated CI fitting with EASSRs.

Use of Functional Near-Infrared Spectroscopy to Predict and Measure Cochlear Implant Outcomes: A Scoping Review

Outcomes following cochlear implantation vary widely for both adults and children, and behavioral tests are currently relied upon to assess this. However, these behavioral tests rely on subjective judgements that can be unreliable, particularly for infants and young children. The addition of an objective test of outcome following cochlear implantation is therefore desirable. The aim of this scoping review was to comprehensively catalogue the evidence for the potential of functional near infrared spectroscopy (fNIRS) to be used as a tool to objectively predict and measure cochlear implant outcomes. A scoping review of the literature was conducted following the PRISMA extension for scoping review framework. Searches were conducted in the MEDLINE, EMBASE, PubMed, CINAHL, SCOPUS, and Web of Science electronic databases, with a hand search conducted in Google Scholar. Key terms relating to near infrared spectroscopy and cochlear implants were used to identify relevant publications. Eight records met the criteria for inclusion. Seven records reported on adult populations, with five records only including post-lingually deaf individuals and two including both pre- and post-lingually deaf individuals. Studies were either longitudinal or cross-sectional, and all studies compared fNIRS measurements with receptive speech outcomes. This review identified and collated key work in this field. The homogeneity of the populations studied so far identifies key gaps for future research, including the use of fNIRS in infants. By mapping the literature on this important topic, this review contributes knowledge towards the improvement of outcomes following cochlear implantation.

Free-Field Cortical Steady-State Evoked Potentials in Cochlear Implant Users

Auditory steady-state evoked potentials (SS-EPs) are phase-locked neural responses to periodic stimuli, believed to reflect specific neural generators. As an objective measure, steady-state responses have been used in different clinical settings, including measuring hearing thresholds of normal and hearing-impaired subjects. Recent studies are in favor of recording these responses as a part of the cochlear implant (CI) device-fitting procedure. Considering these potential benefits, the goals of the present study were to assess the feasibility of recording free-field SS-EPs in CI users and to compare their characteristics between CI users and controls. By taking advantage of a recently developed dual-frequency tagging method, we attempted to record subcortical and cortical SS-EPs from adult CI users and controls and measured reliable subcortical and cortical SS-EPs in the control group. Independent component analysis (ICA) was used to remove CI stimulation artifacts, yet subcortical responses of several CIs were heavily contaminated by these artifacts. Consequently, only cortical SS-EPs were compared between groups, which were found to be larger in the controls. The lower cortical SS-EPs' amplitude in CI users might indicate a reduction in neural synchrony evoked by the modulation rate of the auditory input across different neural assemblies in the auditory pathway. The brain topographies of cortical auditory SS-EPs, the time course of cortical responses, and the reconstructed cortical maps were highly similar between groups, confirming their neural origin and possibility to obtain such responses also in CI recipients. As for subcortical SS-EPs, our results highlight a need for sophisticated denoising algorithms to pinpoint and remove artifactual components from the biological response.

Electrophysiological assessment of temporal envelope processing in cochlear implant users

Cochlear-implant (CI) users rely on temporal envelope modulations (TEMs) to understand speech, and clinical outcomes depend on the accuracy with which these TEMs are encoded by the electrically-stimulated neural ensembles. Non-invasive EEG measures of this encoding could help clinicians identify and disable electrodes that evoke poor neural responses so as to improve CI outcomes. However, recording EEG during CI stimulation reveals huge stimulation artifacts that are up to orders of magnitude larger than the neural response. Here we used a custom-built EEG system having an exceptionally high sample rate to accurately measure the artefact, which we then removed using linear interpolation so as to reveal the neural response during continuous electrical stimulation. In ten adult CI users, we measured the 40-Hz electrically evoked auditory steady-state response (eASSR) and electrically evoked auditory change complex (eACC) to amplitude-modulated 900-pulses-per-second pulse trains, stimulated in monopolar mode (i.e. the clinical default), and at different modulation depths. We successfully measured artifact-free 40-Hz eASSRs and eACCs. Moreover, we found that the 40-Hz eASSR, in contrast to the eACC, showed substantial responses even at shallow modulation depths. We argue that the 40-Hz eASSR is a clinically feasible objective measure to assess TEM encoding in CI users.

Speech-ABRs in cochlear implant recipients: feasibility study

Objective: The aim of this study was to assess the feasibility of recording speech-ABRs from cochlear implant (CI) recipients, and to remove the artefact using a clinically applicable single-channel approach. Design: Speech-ABRs were recorded to a 40 ms [da] presented via loudspeaker using a two-channel electrode montage. Additionally, artefacts were recorded using an artificial-head incorporating a MED-EL CI with stimulation parameters as similar as possible to those of three MED-EL participants. A single-channel artefact removal technique was applied to all responses. Study sample: A total of 12 adult CI recipients (6 Cochlear Nucleus and 6 MED-EL CIs). Results: Responses differed according to the CI type, artefact removal resulted in responses containing speech-ARB characteristics in two MED-EL CI participants; however, it was not possible to verify whether these were true responses or were modulated by artefacts, and artefact removal was successful from the artificial-head recordings. Conclusions: This is the first study that attempted to record speech-ABRs from CI recipients. Results suggest that there is a potential for application of a single-channel approach to artefact removal. However, a more robust and adaptive approach to artefact removal that includes a method to verify true responses is needed.