RESUMO
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.
