Key points are not available for this paper at this time.
Hearing loss can significantly decrease the quality of life for individuals who do not receive adequate treatment, but fortunately, a variety of treatments exist depending on the nature of the loss. For individuals with severe-to-profound sensorineural hearing loss who have not achieved sufficient restoration of hearing with other treatments, the cochlear implant (CI) may be an option. The CI is a surgically-inserted neural prosthetic that converts sounds to electrical stimuli to directly stimulate auditory nerve fibers, bypassing the causes of dysfunction in the inner ear. While many recipients experience significant success with their implants, others receive little or no benefit. Multiple factors can affect hearing outcomes, including the quality of the program that controls the device. Prior research has endeavored to provide clinicians with objective information about a patient to assist them in identifying the optimal parameters for this program. Multiple comprehensive computational models that simulate electrical activity in the cochlea have been created for this task. However, these models are often not fully customizable or are highly customized to single sets of clinical measurements, requiring the model to be recomputed as these measurements change over time. Our overall goal is to create a new model of equal or better quality that is fully customizable and can adapt to changing clinical measurements without substantial recomputation. In this work, we present preliminary results of a methodology for one component of such a model, which uses non-patient-specific simulations of voltage spread in the cochlea to estimate patient-specific electric potentials.
Bratu et al. (Fri,) studied this question.