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

1)项目总结/摘要 人工耳蜗被广泛认为是恢复听力的最有效的临床干预措施， 严重听力损失的人。尽管最先进的CI提供了高水平的语音， 理解和听觉沟通能力，以大多数植入接受者，仍然有一个重大的差距， CI用户和正常听力个体的性能水平之间的差异，特别是在现实生活中的嘈杂环境中， 环境.性能上的这种差距部分地可以归因于声音编码和语音编码两者的限制。 电刺激策略，部分是由于有限的能力，以探索潜在的新的先进的 算法与当前CI用户在该领域。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 无法获得能够1）实现计算密集型声音的便携式声音处理平台 处理方案和2）在真实的自然环境中长期评估它们。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，调查三个互补的声音处理 这些战略（目标1 - 3）将通过拟议的研究平台（目标4）得以实现。一是 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 从竞争的背景噪音。这些算法在实际声学环境中的潜在益处 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 对频率分配和刺激速率进行实时用户指定调整的潜在益处 调节自然环境中的语音感知和音质（目标2）。在目标3中，我们 研究提供同步电刺激的语音处理策略的有效性， 双侧CI。具体来说，我们的目标是测试在ITD歧视，声音定位和隔离的差异 在有和没有同步双侧刺激的情况下，这些研究将使用 该平台的现有原型CCi-MOBILE。作为下一步，我们建议开发下一代CCi- 移动的-2平台-一个灵活的、开源的、便携式的声音处理平台， 研究思路的实施以及对现实生活中声学算法的长期评估 环境（目标4）。这个独一无二的研究平台将更加灵活， 计算能力强于现有的临床处理器，将有助于将科学研究与 商业应用。CCi-MOBILE-2平台将免费与CI研究社区共享， 使用开源模式的成本。这里列出的实验仅仅是潜在的一个子集。 这些突破性的进步将通过拟议的研究平台的存在而成为可能。 进行现实生活中的慢性言语评估的能力将为科学探索开辟新的前沿， 将导致如何在耳蜗中进行语音处理/感知研究的范式转变 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，从而给出了以下方面的操作示例 如何为其他研究实验室利用研究平台。

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.