Individualized Signal Processing Strategy :Phase II

该项目描述了一种使信号处理策略自动化和个性化的新方法 对于助听器(HA)，可以在背景噪声中提高语音清晰度， 用户对HAS的满意度和接受度，并减少负担得起的听力保健的障碍。这个 所提出的个性化信号处理策略(ISPS)是基于个体在 言语刺激的范畴知觉任务。这不同于传统的方法，基于 基于平均感知、性能和偏好数据构建的复杂增益模型。这个 能够自动、快速和远程确定您的ISP可以显著节省成本 以及为负担不起或缺乏听力保健的患者提供更多听力保健服务 轻松获得必要的专业知识。这些技术成就有可能从根本上 更改HA服务交付模式，但可以在现有业务模式和 与现在的练习者一起演唱。ISPS方法有效地取代了基于目标的HA拟合(例如 NAL-NL2)，具有基于语音的个性化参数调整。建议的工作如下 成功完成我们的试点项目，并建立在研究团队先前对小说的研究基础上 Cochlear，Ltd.最近收购的人工耳蜗(CI)装置的安装方法。 在试验研究中，我们成功地实施了ISPS并与商业HA软件集成 已证明的可行性，包括实地研究，在该研究中，执行支助方案方法的业绩结果 与传统的HA拟合方法一样好，而且只需要一小部分时间，尽管有ISPS 对病人的特征没有事先的了解，也没有听力图。成功成熟和 ISPS技术在第二阶段的商业化将解决 之前的RFA-DC-12-004，包括物理、基础架构和知识障碍(通过允许 远程或自适应)、经济障碍(通过降低总体成本)和文化障碍(通过 为倾向于逃避专业帮助的患者提供方便的医管局试衣)。这是第二阶段 项目将通过以下方式开发可操作的ISPS方法：(1)将ISPS与硬件/软件集成 行业伙伴的系统，(2)改进和加强ISPS方法，以提高效率和 安装听力仪器的有效性，(3)为在多个国家使用ISPS提供支持 市场，以及(4)通过不同服务提供的现场试验对技术进行评估 通过将符合ISPS的结果与使用传统规范实现的结果进行比较 在相同的对象中获得合适的结果。在成功演示这些目标之后，一个阶段 III项目将侧重于支持远程和自适应听力的技术过渡 乐器。

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.