CCI-Mobile: Signal Processing Advancements for Cochlear Implant Users in Naturalistic Environments

CCI-Mobile：自然环境中人工耳蜗用户的信号处理进步

• 批准号: 10390454
• 负责人: John H.L. Hansen
• 金额: $ 62.42万
• 依托单位: UNIVERSITY OF TEXAS DALLAS
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-05-03 至 2024-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10390454
• 关键词: Accent; Acoustics; Address; Adult; Algorithms; Android; Auditory; Bilateral; Binaural; Cellular Phone; Child; Chronic; Clinical; Cochlear Implants; Code; Communication; Communities; Complex; Comprehension; Cues; Devices; Discrimination; Drops; Effectiveness; Electric Stimulation; Electrodes; Electronics; Emotions; Environment; Evaluation; Family; Frequencies; Goals; Home; Human; Human Characteristics; Implant; Individual; Intervention; Knowledge; Laboratories; Laboratory Research; Life; Methods; Modeling; Music; Noise; Outcome; Patients; Perception; Performance; Physiology; Production; Research; Scheme; Signal Transduction; Sound Localization; Source; Specific qualifier value; Speech; Speech Development; Speech Intelligibility; Speech Perception; Speech Sound; Stress; Tablets; Testing; Time; Training; Work; base; commercial application; cost; deaf; denoising; effectiveness testing; experience; experimental study; field study; flexibility; frontier; improved; neural prosthesis; next generation; normal hearing; novel; novel strategies; open source; portability; prototype; research and development; segregation; signal processing; sound; speech in noise; speech processing; success

1) Project Summary/Abstract Cochlear prosthesis is widely accepted as the most effective clinical intervention to restore auditory function of individuals with profound hearing loss. Although state-of-the-art CIs provide a high level of speech comprehension and aural communication ability to a majority of implant recipients, there remains a major gap between performance levels of CI users and normal hearing individuals, especially in real-life noisy environments. This gap in performance in part can be attributed to limitations in both sound coding and electrical stimulation strategies, and partially due to the limited ability to explore potentially new advanced algorithms with current CI users in the field. Several methods have been proposed over the years to address this shortcoming; however, most have been restricted to laboratory research. This is primarily due to the unavailability of portable sound processing platforms that can 1) implement computationally-intensive sound processing schemes and 2) assess them chronically in real naturalistic environments. Clinical processors/platforms are neither powerful, nor flexible to meet the growing scientific needs of the research community. We propose a multi-center research effort to investigate three complementary sound processing strategies (Aims 1 – 3), which will be made possible through the proposed research platform (Aim 4). First, we will develop and test the effectiveness of two new families of front-end speech processing algorithms (Aim 1), both of which are inspired by speech production/perception physiology and aim to enhance the speech signal from competing background noise. The potential benefit of these algorithms in real-life acoustic environments will be assessed by conducting take-home trials using the portable research platform. Next, we will investigate the potential benefits of real-time user-specified adjustments to frequency allocation and stimulation rate adjustments on speech perception and sound quality in naturalistic environments (Aim 2). In Aim 3, we will investigate the effectiveness of speech processing strategies that deliver synchronized electrical stimulation to bilateral CIs. Specifically, we aim to test differences in ITD discrimination, sound localization, and segregation of speech in noise with and without synchronized bilateral stimulation. These studies will be done using the existing prototype of the platform, CCi-MOBILE. As a next step we propose to develop a next-generation CCi- MOBILE-2 platform - a flexible, open-source, portable sound processing platform that will allow easy implementation of research ideas as well as long-term assessments of algorithms in real-life acoustic environments (Aim 4). This one-of-a-kind research platform will be orders of magnitude more flexible and computationally powerful than existing clinical processors and will aid in bridging scientific research with commercial applications. The CCi-MOBILE-2 platform will be shared with the CI research community free of cost using an open source model. The experiments listed here represent a mere subset of the potential groundbreaking advancements that will be made possible by the existence of the proposed research platform. The ability to perform real-life chronic speech assessments will open new frontiers for scientific exploration and will result in a paradigm shift in how speech processing/perception research is carried out in the cochlear implant field. Advancements from Aims 1-3 will show clear examples of how to transition scientific and algorithmic advancements to field testing with the CCi-MOBILE-2 (Aim 4), thus giving operational examples on how to leverage the research platform for other research laboratories.

1)项目摘要/摘要 人工耳蜗术是目前公认的最有效的恢复听功能的临床干预手段。 听力严重受损的人。尽管最先进的配置项提供了高水平的语音 对大多数植入物接受者的理解和听力交流能力，仍有较大差距 CI使用者的表现水平与听力正常的人之间的差异，特别是在现实生活中的噪音 环境。这种性能上的差距部分可以归因于声音编码和 电刺激策略，部分原因是探索潜在新的先进技术的能力有限 算法与该领域的当前CI用户。多年来，已经提出了几种方法来解决 这一缺点；然而，大多数都局限于实验室研究。这主要是由于 无法使用可1)实现计算密集型声音的便携式声音处理平台 加工方案和2)在真实的自然环境中对它们进行长期评估。临床 处理器/平台既不强大，也不灵活，无法满足研究日益增长的科学需求 社区。我们提出了一个多中心的研究工作来研究三个互补的声音处理 战略(目标1-3)，这将通过拟议的研究平台(目标4)实现。首先，我们 将开发和测试两个新的前端语音处理算法家族的有效性(目标1)， 这两种方法都受到语音产生/感知生理学的启发，旨在增强语音信号 来自相互竞争的背景噪音。这些算法在实际声学环境中的潜在优势 将通过使用便携式研究平台进行带回家的试验进行评估。接下来，我们将调查 用户指定的实时调整频率分配和刺激率的潜在好处 自然环境中语音感知和音质的调整(目标2)。在《目标3》中，我们将 研究语音处理策略将同步电刺激传递给 双边顺位。具体地说，我们的目标是测试ITD歧视、声音本地化和隔离方面的差异 在有和没有同步双侧刺激的情况下在噪声中的语音。这些研究将使用 现有原型平台CCI-Mobile。作为下一步，我们建议开发下一代CCI- Mobile-2 Platform-一个灵活、开源、便携的声音处理平台，可轻松实现 在实际声学中实现研究思路以及算法的长期评估 环境(目标4)。这个独一无二的研究平台将在数量级上更加灵活和 在计算上比现有的临床处理器更强大，并将有助于将科学研究与 商业应用。CCI-MOBILE-2平台将与CI研究社区免费共享 使用开放源码模型的成本。这里列出的实验仅仅是潜力的一个子集 拟议的研究平台的存在将使突破性进展成为可能。 进行现实生活中慢性言语评估的能力将为科学探索和 将导致语音处理/知觉研究如何在耳蜗中进行的范式转变 植入场。目标1-3的进展将展示如何将科学和技术 CCI-MOBILE-2(目标4)现场测试的算法改进，从而给出了 如何利用其他研究实验室的研究平台。