Individualized Signal Processing Strategy :Phase II

个性化信号处理策略：第二阶段

• 批准号: 9347562
• 负责人: Lee Stanley Krause
• 金额: $ 75.89万
• 依托单位: SECURBORATION, INC.
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-04-18 至 2019-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9347562
• 关键词: Achievement; Address; Algorithms; Artificial Intelligence; Audiology; Audiometry; Auditory; Automation; Businesses; Categories; Characteristics; Cochlear Implants; Collaborations; Computer software; Cost Savings; Crossover Design; Data; Development; Devices; Economics; Effectiveness; Environment; Evaluation; Frequencies; Funding; Generic Drugs; Goals; Healthcare; Hearing; Hearing Aids; Individual; Instruction; Knowledge; Learning; Link; Manufacturer Name; Measures; Methods; Modeling; National Institute on Deafness and Other Communication Disorders; Noise; Outcome; Patient Care; Patients; Perception; Performance; Phase; Pilot Projects; Procedures; Process; Randomized; Rehabilitation therapy; Research; Research Infrastructure; Sensorineural Hearing Loss; Services; Speech; Speech Intelligibility; Speech Perception; Stimulus; Supervision; Technology; Testing; Time; Training; Translating; United States Department of Veterans Affairs; United States National Institutes of Health; Validation; Work; base; commercialization; cost; data modeling; experimental study; field study; graph theory; health care service; implantable device; improved; improved outcome; inclusion criteria; industry partner; instrument; knowledge base; meetings; novel; novel strategies; preference; satisfaction; signal processing; software systems; sound; success

This project describes a novel approach to automate and individualize the signal processing strategy for hearing aids (HA) that can result in improved speech intelligibility in background noise, greater user satisfaction and acceptance for HAs, and reduce barriers to affordable hearing health care. The proposed Individualized Signal Processing Strategy (ISPS) is based on individual performance on categorical perception tasks for speech stimuli. This differs from traditional methods based on sophisticated gain models built upon average perception, performance, and preference data. The ability to determine one’s ISPS automatically, rapidly and remotely can result in dramatic cost-savings and greater accessibility to hearing health care for patients who cannot afford it or for those who lack easy access to the necessary expertise. These technical achievements have the potential to radically change HA service delivery models yet can be implemented within existing business models and in concert with current practitioners. The ISPS method effectively replaces target-based HA fitting (e.g. NAL-NL2) with individualized speech-based parameter adjustment. The proposed work follows successful completion of our pilot project and builds upon the research team’s prior research on novel fitting methods for cochlear implant (CI) devices recently acquired by Cochlear, Ltd. Following the successful implementation of ISPS and integration with commercial HA software in the pilot study, we demonstrated feasibility including a field study in which performance outcomes for the ISPS method were as good as a conventional HA fitting method and only took a fraction of the time, despite ISPS having no prior knowledge of patient characteristics and no audiogram. Successful maturation and commercialization of the ISPS technology in Phase II will address several barriers identified in the previous RFA-DC-12-004 including physical, infrastructure, and knowledge barriers (by allowing remote or self-fitting HAs), economic barriers (by reducing overall costs), and cultural barriers (by providing easy access to HA fitting for patients who tend to avoid professional help). This Phase II project will develop an operational ISPS method by (1) integrating ISPS with hardware/software systems of our industry partners, (2) refine and enhance the ISPS method to improve efficiency and effectiveness of fitting hearing instruments, (3) build support for the use of ISPS in multiple marketplaces, and (4) evaluate the technology through field trials in different service delivery environments by comparing outcomes with ISPS fitting to those achieved with traditional prescriptive gain fitting within the same subjects. Following successful demonstration of these objectives, a Phase III project will focus on the transition of the technology to support remote and self-fitting of hearing instruments.

这个项目描述了一种新的方法来自动化和个性化的信号处理策略 对于能够在背景噪声中提高语音清晰度的助听器， 用户满意度和接受HA，并减少负担得起的听力保健的障碍。的 建议的个性化信号处理策略（ISPS）是基于个人的表现， 言语刺激的分类知觉任务。这不同于传统的方法， 基于平均感知、性能和偏好数据构建的复杂增益模型。的 自动、快速和远程确定ISPS的能力可以显著节省成本 以及为那些负担不起或缺乏听力保健的患者提供更多的听力保健服务。 容易获得必要的专业知识。这些技术成就有可能从根本上 改变HA服务交付模式，但可以在现有业务模式中实施， 与当前从业者的合作。ISPS方法有效地取代了基于目标的HA拟合（例如， NAL-NL 2），具有个性化的基于语音的参数调整。拟议的工作如下 成功完成我们的试点项目，并建立在研究团队的小说之前的研究 最近由Cobriar有限公司收购的人工耳蜗（CI）设备的装配方法。 在试验研究中，我们成功推行ISPS系统，并把系统与医管局的商用软件整合， 证明了可行性，包括现场研究，其中ISPS方法的性能结果 与传统的HA拟合方法一样好，并且只需要一小部分时间，尽管ISPS 对患者特征没有先验知识，也没有听力图。成功的成熟和 ISPS技术在第二阶段的商业化将解决在 先前的RFA-DC-12-004，包括物理、基础设施和知识障碍（通过允许 远程或自适应HA）、经济障碍（通过降低总成本）和文化障碍（通过 为倾向于避免专业帮助的患者提供方便的HA配件）。这项II期 该项目将通过以下方式开发一种可操作的ISPS方法：（1）将ISPS与硬件/软件相结合 我们的行业合作伙伴的系统，（2）完善和加强ISPS方法，以提高效率， （3）支持在多个国家使用ISPS， 市场，以及（4）通过在不同服务交付中的现场试验评估技术 通过比较ISPS的结果与传统规定性 在相同的主题中获得拟合。在成功实现这些目标后， III项目将侧重于支持远程和自适应听力的技术过渡 仪器.