SCH: INT: Collaborative Research: A Framework for Optimizing Hearing Aids In Situ Based on Patient Feedback, Auditory Context, and Audiologist Input

SCH:INT:协作研究:基于患者反馈、听觉环境和听力学家输入的现场优化助听器的框架

基本信息

  • 批准号:
    1838830
  • 负责人:
  • 金额:
    $ 70.2万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2019
  • 资助国家:
    美国
  • 起止时间:
    2019-01-01 至 2022-12-31
  • 项目状态:
    已结题

项目摘要

Twenty percent of Americans will be 65 years or older by 2030 out of which 35 - 50% will report having age-related hearing impairment that is treated primarily with hearing aids (HA). Regular use of HAs has been shown to improve communication and avoid the negative effects of hearing loss that include an increased risk of social isolation, depression, and inability to work, travel, or be physically active. Past research has shown that many people do not wear their HAs regularly, as they are unsatisfied with the performance in the real world. A fundamental limitation of existing methods for tuning HA is that they are not tailored to individual needs, which often leads to unsatisfactory performance. As part of this project, a team of computer scientists, engineers, and audiologists will develop new methods for tuning HAs that are based on the individual needs of a patient.The project is based on the approach that better HA configurations may be identified based on feedback from the patient that is collected in the moment and in situ. The project includes development of two systems for optimizing the configuration of HAs. The first system will improve the efficacy of the traditional tuning process by improving how feedback is obtained from patients, combined with auditory context information, and translated into HA configuration adjustments. The second system will automatically adapt the configuration of a HA based on patient feedback and auditory context information without requiring an audiologist to perform adjustments. The intellectual merit of this proposal includes the advances in machine learning necessary to model the performance of complex systems that have numerous parameters such as HAs and tuning their parameters based on feedback obtained from patients. Additionally, the project will advance the state-of-the-art in embedded systems by developing techniques to run HA optimization algorithms as part of a multi-tier system composed of HAs, mobile phones, and cloud services. It is anticipated that the proposed research will empower patients to become more involved in their hearing care, improve HA satisfaction, and enrich their social interactions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
到2030年,有20%的美国人将年满65岁或以上,其中35-50%将报告与年龄相关的听力障碍,主要接受助听器(HA)治疗。已证明定期使用可以改善沟通,并避免听力损失的负面影响,包括增加社会隔离,抑郁和无法工作,旅行或体育活跃的风险增加。过去的研究表明,许多人没有经常穿着,因为他们对现实世界的表现不满意。现有方法HA的基本局限性是,它们不是根据个人需求量身定制的,这通常会导致性能不令人满意。作为该项目的一部分,一组计算机科学家,工程师和听力学家将开发基于患者的个人需求的新方法。该项目是基于方法,即可以根据目前和原位收集的患者的反馈来确定更好的HA配置。该项目包括开发两个用于优化HAS配置的系统。第一个系统将通过改善从患者获得反馈,与听觉上下文信息相结合并转化为HA配置调整,从而提高传统调整过程的功效。第二个系统将根据患者的反馈和听觉上下文信息自动调整HA的配置,而无需听力学家进行调整。该提案的智力优点包括建模具有许多参数(例如HAS)并根据患者的反馈来调整其参数的复杂系统的性能所需的机器学习进步。此外,该项目将通过开发用于运行HA优化算法的技术来推动嵌入式系统中的最新技术,这是由HAS,移动电话和云服务组成的多层系统的一部分。预计拟议的研究将使患者有能力更多地参与听力,提高HA满意度并丰富他们的社交互动。该奖项反映了NSF的法定任务,并被认为是通过基金会的知识分子优点和更广泛影响的评估标准来评估的值得支持的。

项目成果

期刊论文数量(11)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Common Configurations of Real-Ear Aided Response Targets Prescribed by NAL-NL2 for Older Adults With Mild-to-Moderate Hearing Loss.
NAL-NL2 为轻度至中度听力损失的老年人规定的真耳辅助响应目标的常见配置。
  • DOI:
    10.1044/2020_aja-20-00025
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    1.8
  • 作者:
    Jensen,Justin;Vyas,Dhruv;Urbanski,Dana;Garudadri,Harinath;Chipara,Octav;Wu,Yu-Hsiang
  • 通讯作者:
    Wu,Yu-Hsiang
Auditory Environments and Hearing Aid Feature Activation Among Younger and Older Listeners in an Urban and Rural Area
  • DOI:
    10.1097/aud.0000000000001308
  • 发表时间:
    2023-05-01
  • 期刊:
  • 影响因子:
    3.7
  • 作者:
    Jorgensen, Erik;Xu, Jingjing;Wu, Yu-Hsiang
  • 通讯作者:
    Wu, Yu-Hsiang
Personalizing over-the-counter hearing aids using pairwise comparisons
使用成对比较个性化非处方助听器
  • DOI:
    10.1016/j.smhl.2021.100231
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Vyas, Dhruv;Brummet, Ryan;Anwar, Yumna;Jensen, Justin;Jorgensen, Erik;Wu, Yu-Hsiang;Chipara, Octav
  • 通讯作者:
    Chipara, Octav
Comparing population coverage between hearing aids using presets vs Bose CustomTune.
比较使用预设的助听器与 Bose CustomTune 的人口覆盖范围。
  • DOI:
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Sabin, Andrew;Jensen, Justin;Chipara, Octav;Wu, ‪Yu-Hsiang
  • 通讯作者:
    Wu, ‪Yu-Hsiang
Dataset for Personalizing Over-the-Counter Hearing Aids using Pairwise Comparisons
使用成对比较个性化非处方助听器的数据集
  • DOI:
    10.5281/zenodo.7535197
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    ochipara
  • 通讯作者:
    ochipara
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Octav Chipara其他文献

Octav Chipara的其他文献

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{{ truncateString('Octav Chipara', 18)}}的其他基金

SCH: Shallow and Deep Personalization for Hearing Aids
SCH:助听器的浅度和深度个性化
  • 批准号:
    2306331
  • 财政年份:
    2023
  • 资助金额:
    $ 70.2万
  • 项目类别:
    Standard Grant
CAREER: Software Adaptation and Synthesis Techniques for Internet of Things Systems
职业:物联网系统的软件适配和综合技术
  • 批准号:
    1750155
  • 财政年份:
    2018
  • 资助金额:
    $ 70.2万
  • 项目类别:
    Continuing Grant
NeTS: Small: Collaborative Research: Protocols and Analysis for Predictable Wireless Sensor Networks
NetS:小型:协作研究:可预测无线传感器网络的协议和分析
  • 批准号:
    1144664
  • 财政年份:
    2011
  • 资助金额:
    $ 70.2万
  • 项目类别:
    Standard Grant

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