A novel method for extraction of neural response from single channel cochlear implant auditory evoked potentials. (February 2017) - Sinkiewicz, Daniel
Highlights: We developed a new tool to identify the CI artifact within the CI CAEP. We also proposed a novel method to extract CAEP components from a CI CAEP. Our study is also the first application of time–frequency analysis to successfully identify the artifact within the CI CAEP. The results are supported by a series of real data applications and a comparison with two other existing methods. Abstract: Cortical auditory evoked potentials (CAEP) are used to evaluate cochlear implant (CI) patient auditory pathways, but the CI device produces an electrical artifact, which obscures the relevant information in the neural response. Currently there are multiple methods, which attempt to recover the neural response from the contaminated CAEP, but there is no gold standard, which can quantitatively confirm the effectiveness of these methods. To address this crucial shortcoming, we develop a wavelet-based method to quantify the amount of artifact energy in the neural response. In addition, a novel technique for extracting the neural response from single channel CAEPs is proposed. The new method uses matching pursuit (MP) based feature extraction to represent the contaminated CAEP in a feature space, and support vector machines (SVM) to classify the components as normal hearing (NH) or artifact. The NH components are combined to recover the neural response without artifact energy, as verified using the evaluation tool. Although it needs some further evaluation, this approach is a promising method of electrical artifact removal from CAEPs.