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.

项目摘要/摘要： 获得的听力损失越来越普遍，尤其是随着老龄化人口的增长。 对于许多人来说，听力损失足够严重，可以保证人工耳蜗植入。而许多成年人 通过人工耳蜗（CIS）通过其设备很好地了解语音，因此无法解释的可变性很大 存在于语音识别结果以及语音识别改进的轨迹中（即 感知学习）植入后。不幸的是，由于这种无法解释的可变性，临床医生是 无法预测个人如何与CI一起表现，以解释某人的演讲差的原因 通过CI认可或设计适当的康复策略以帮助贫穷的人 表现。目前，只有一半的结果可变性可以通过传统的临床测量来解释。 最近的研究表明，CI用户反映的语音识别的个体差异 更基本的感觉（“自下而上”）和认知语言（“自上而下”）因素的变异性。这些因素 应该解释CI结果的其他差异，以及一个全面的集成模型编码 需要采取传统的临床措施以及自下而上和自上而下的因素。总体目标 拟议的项目是填补有关CI无法解释的可变性来源的知识的空白 语音识别结果和感知学习。 AIM 1将确定哪个预期的程度 自下而上的感觉函数和自上而下的认知语言过程的手术测量预测CI 语音识别结果。 AIM 2将调查额外的客观自下而上的程度 感官过程，尤其是它们与自上而下的因素的互动，解释句子识别。目的 3将调查在前两个期间发生的语音识别中感知学习的轨迹 CI使用年。该研究项目的发现将具有重要的理论和临床 通过全面描述自下而上和自上而下的贡献和互动来启示 与识别语音的可变性有关的因素，并帮助临床医生更好地预测 术前并在术后了解感知学习的结果和时间课程 植入后发生。