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.
Cochlear implants consist of an implanted array of electrodes and passive electronics and an external processor designed to directly stimulate auditory nerve fibers to induce the sensation of hearing in those who have experienced hearing loss caused by problems in the inner ear. After surgical implantation, audiologists program the processor with settings intended to produce optimal hearing outcomes. The likelihood of optimal outcomes increases when audiologists are provided with tools that assist them in making objective decisions based on the patient’s own anatomy and surgical placement of the array. A visualization tool currently in use, called distance-versus-frequency (DVF)curves, can be used to estimate channel interactions between electrodes. Although the information presented is objective, an audiologist’s decisions are subject to their own estimations applied to this visualization. In this paper, we present a new visualization technique designed to remove the subjectivity of visually assessing channel interactions between electrodes. Preliminary results show plans generated using this method are more consistent and are rated as optimal more often than those generated using DVF curves.
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