There are a rapidly growing number of """"""""bimodal"""""""" patients, people who hear using a cochlear implant in one ear and a hearing aid in the other ear. These patients hear using two different forms of sound input: the cochlear implant delivers an electrical signal and the hearing aid delivers an acoustic signal. Current clinical practice usually entails the separate fitting of each device by a different audiologist, using methods that are normally employed for standalone devices. This paradigm is based more on historical circumstances than on evidence of its effectiveness. The goal of the proposed research is to develop data-based tools that will allow clinicians to maximize bimodal speech perception by better coordinating the fitting of the hearing aid and the cochlear implant, and the post-implantation follow-up.
Specific Aim 1 is to develop guidelines that will help clinicians select an appropriate hearing aid bandwidth for bimodal patients as a function of their residual hearing.
Specific Aim 2 is to develop a flowchart with recommendations concerning which frequency allocation table should be used in the cochlear implant of bimodal patients as a function of their residual hearing.
Specific Aim 3 is to develop guidelines for the post-implant follow up of bimodal patients, including recommendations for frequency of evaluation and conditions, tasks, and tests to be used. The set of clinical tools to be developed (lookup tables, flowcharts, and follow-up guidelines) will address a pressing clinical need and will allow clinicians to make data-driven decisions for the audiological management of bimodal patients.
This research will provide guidance to clinicians who manage the fitting and follow-up care of bimodal patients, those who use a cochlear implant in one ear and a hearing aid in the other ear. We will develop tools to help select the hearing aid and cochlear implant fittings that will provide the best bimodal speech recognition for each individual. In addition, protocols for long-term follow-up of bimodal patients will be generated.
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