Predicting Speech Recognition in Adults Receiving Cochlear Implants

预测接受人工耳蜗植入的成年人的语音识别能力

• 批准号: 10294348
• 负责人: Aaron C Moberly
• 金额: $ 53.1万
• 依托单位: OHIO STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-01 至 2026-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10294348
• 关键词: Acquired Deafness; Action Potentials; Address; Adult; Age; Auditory Psychophysics; Clinical; Cochlear Implants; Cochlear implant procedure; Cognitive; Devices; Electrocochleographies; Electrodes; Face; Future; Goals; Growth; Image; Implanted Electrodes; Individual; Individual Differences; Knowledge; Linguistics; Measures; Modeling; Nerve; Operative Surgical Procedures; Outcome; Patients; Perceptual learning; Performance; Postoperative Period; Predictive Factor; Process; Protocols documentation; Rehabilitation therapy; Research; Research Project Grants; Scientist; Semantics; Sensorineural Hearing Loss; Sensory; Sensory Process; Severities; Short-Term Memory; Source; Speech; Surgeon; Time; United States; Verbal Learning; Visual; X-Ray Computed Tomography; aging population; clinical predictors; design; experience; hearing impairment; implantation; improved; lexical; lexical processing; phonology; processing speed; rehabilitation strategy; scaffold; semantic processing; skills; speech recognition; standard of care

Project Summary/Abstract: Acquired hearing loss is becoming increasingly common, especially with the growth of the aging population. For many individuals, hearing loss is severe enough to warrant cochlear implantation. While many adults with cochlear implants (CIs) understand speech well through their devices, enormous unexplained variability exists in speech recognition outcomes, as well as in the trajectory of speech recognition improvement (i.e., perceptual learning) after implantation. Unfortunately, because of this unexplained variability, clinicians are unable to predict how an individual will perform with a CI, to explain why someone has poor speech recognition with a CI, or to design appropriate rehabilitation strategies to help an individual with poor performance. Currently, only half of this outcome variability can be explained by traditional clinical measures. Recent studies have suggested that individual differences in speech recognition among CI users reflect variability in more basic sensory (“bottom-up”) and cognitive-linguistic (“top-down”) factors. These factors should explain additional variability in CI outcomes, and a comprehensive integrative model incorporating traditional clinical measures along with bottom-up and top-down factors is needed. The overall objective of the proposed project is to fill the gap in knowledge regarding the sources of unexplained variability in CI speech recognition outcomes and perceptual learning. Aim 1 will determine the degree to which pre- operative measures of bottom-up sensory functions and top-down cognitive-linguistic processes predict CI speech recognition outcomes. Aim 2 will investigate the degree to which additional objective bottom-up sensory processes, and especially their interactions with top-down factors, explain sentence recognition. Aim 3 will investigate the trajectories of perceptual learning in speech recognition that occur during the first two years of CI use. The findings from this research project will have important theoretical and clinical implications by comprehensively delineating the contributions and interactions of bottom-up and top-down factors as they relate to variability in recognition of speech, as well as helping clinicians to better predict pre-operatively and understand post-operatively the outcomes and time course of perceptual learning that occurs after implantation.

项目总结/文摘: