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Use of Patient-specific Models for Computer-assisted Cochlear Implant Programming
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Use of Patient-specific Models for Computer-assisted Cochlear Implant Programming. |
| 개인저자 | Cakir, Ahmet. |
| 단체저자명 | Vanderbilt University. Computer Science. |
| 발행사항 | [S.l.]: Vanderbilt University., 2019. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2019. |
| 형태사항 | 182 p. |
| 기본자료 저록 | Dissertations Abstracts International 81-06B. Dissertation Abstract International |
| ISBN | 9781088342763 |
| 학위논문주기 | Thesis (Ph.D.)--Vanderbilt University, 2019. |
| 일반주기 |
Source: Dissertations Abstracts International, Volume: 81-06, Section: B.
Advisor: Noble, Jack H. |
| 이용제한사항 | This item must not be sold to any third party vendors. |
| 요약 | Sensorineural hearing loss affects over 10% of the U.S. population and is most commonly caused by damage to the hair cells that transduce sound into action potentials in the afferent neurons of the auditory nerve fibers. Direct electrical stimulation of the spiral ganglion cell bodies using a surgically implanted neuroprosthetic device known as a cochlear implant (CI) bypasses damaged hair cells and effectively restores hearing sensation for individuals experiencing severe-to-profound hearing loss. Although these devices have been remarkably successful at restoring hearing, it is rare to achieve natural fidelity, and many patients experience poor outcomes. The selection of appropriately sized electrode array is one of the factors that limits outcomes. An ideal electrode covers the entire frequency spectrum of the cochlea without causing cochlear trauma. Another factor is the post-implantation programming process that audiologists clinically use because, while existing devices permit manipulation of many settings that could lead to better performance, there are no objective cues available to indicate what setting changes will lead to better performance. Thus, the adjustment process often converges to sub-optimal settings and may require dozens of programming sessions. In this dissertation, several approaches are proposed to estimate subject-specific cochlear length, which can be used to select appropriately sized electrode arrays, and neural activation patterns (NAPs) that contain information on which group of nerve fibers are activated by each intra-cochlear electrode. NAPs are predicted via physics-based computational models of electrically stimulated cochlea coupled with auditory nerve fiber activation models that are parameterized by neural health. These models can potentially guide CI programming as we have shown that NAPs can be used to determine channel interaction artefacts which negatively affect hearing outcomes. We have also clinically validated the in-vivo estimations of subject specific health of auditory nerve fiber populations in different regions of the inner ear as regions of dead or degenerated nerve fibers in the inner ear are common among individuals experiencing hearing loss and are a major contributor to the high variability in hearing outcomes with CIs. |
| 일반주제명 | Computer science. |
| 언어 | 영어 |
| 바로가기 | 
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