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 人工耳蜗假体被广泛接受为恢复听觉功能的最有效的临床干预措施 听力损失深远的人。尽管最先进的CI提供了高水平的语音 与大多数植入物接收者的理解和听觉沟通能力，仍然存在一个主要差距 在CI使用者的表现水平和正常的听力人之间，尤其是在现实生活中 环境。该性能的这种差距部分归因于声音编码和 电刺激策略，部分原因是探索潜在的新高级的能力有限 该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 这个缺点；但是，大多数都仅限于实验室研究。这主要是由于 无法获得便携式声音处理平台，可以1）实施计算密集型声音 处理方案和2）在实际的自然主义环境中长期对其进行评估。临床 处理器/平台要么强大，也可以灵活地满足研究的科学需求 社区。我们提出了一项多中心研究工作，以研究三个完整的声音处理 策略（目标1-3），将通过拟议的研究平台（AIM 4）实现。首先，我们 将开发和测试两个前端语音处理算法的两个新家族的有效性（AIM 1）， 两者都受到语音生产/感知生理的启发，旨在增强语音信号 来自竞争背景噪音。这些算法在现实生活中的潜在好处 将通过使用便携式研究平台进行带回家试验来评估。接下来，我们将调查 实时用户指定调整对频率分配和刺激率的潜在优势 对自然主义环境中语音感知和声音质量的调整（AIM 2）。在AIM 3中，我们将 研究语音处理策略的有效性，这些策略将同步的电刺激传递到 双边顺式。具体而言，我们旨在测试ITD歧视，声音定位和隔离的差异 具有和没有同步双侧刺激的噪声中的语音。这些研究将使用 平台的现有原型CCI-Mobile。作为下一步，我们建议开发下一代CCI- Mobile-2平台 - 灵活的开源，便携式声音处理平台，可以轻松 现实生活中的研究思想的实施以及对算法的长期评估 环境（目标4）。这个独一无二的研究平台将更加灵活，并且 计算功能强于现有临床处理器，将有助于与科学研究桥接 商业应用。 CCI-Mobile-2平台将免费与CI研究社区共享 使用开源模型的成本。这里列出的实验仅代表了电势的子集 拟议的研究平台的存在将取得突破性的进步。 进行现实生活中的长期语音评估的能力将为科学探索和 将导致语音处理/感知研究在人工耳蜗中进行的范式转变 植入场。目标1-3的进步将显示如何过渡科学和 使用CCI-Mobile-2（AIM 4）进行现场测试的算法进步（AIM 4），从而给出了操作示例 如何为其他研究实验室利用研究平台。