整体刺激 DPOAE 分析。

Paul D Teal, Christopher A Shera, Carolina Abdala
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引用次数: 0

摘要

失真产物声发射(DPOAE)为听力诊断提供了巨大的潜力,但由于不同机制产生的成分相互作用而变得复杂。将这些成分从 DPOAE 测量中分离出来,可以对耳蜗这些不同机制的功能得出结论。然而,进行这种分离的信号处理方法并不完善。现有的方法基于对频率扫描刺激产生的 DPOAE 进行时间窗口处理。本文提出了一种同时估算失真(D)和反射(R)成分整个频谱的方法。这种方法有几个优点。首先,该方法无需在频率精度和信噪比之间做出妥协。其次,该方法可以包含刺激信号模型,这样刺激信号就不会对估算过程产生强烈干扰。第三,该方法可以有效利用被测量伪影破坏的数据。第四,该方法可以很容易地进行调整,以跟踪因化学或声学处理而变化的 DPOAE。所做的基本建模假设是:R 和 D 测量值的总和可以表示为与刺激信号的卷积之和;D 分量的频率表示比 R 分量更平滑;可以合理估计信号中的噪声电平。这些假设被合并成一个线性凸问题。在本文中,我们将所提出的方法与其他三种方法进行了比较。虽然它在每个频率上都不优于先前的方法,但确实有一些改进,特别是在减少 D 分量对 R 分量的污染方面。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Whole Stimulus DPOAE Analysis.

Distortion Product Otoacoustic Emissions (DPOAE) offer great potential for hearing diagnosis, but are complicated by the interaction of components generated by different mechanisms. Separation of these components from DPOAE measurements may allow conclusions to be drawn about the functionality of these separate mechanisms of a cochlear. However, the signal processing methods for performing this separation are imperfect. Existing methods are based on time windowing of DPOAE generated from frequency sweep stimuli. This paper presents a method in which the entire spectra of both distortion (D) and reflection (R) components are simultaneously estimated. This approach has several advantages. Firstly, the method removes the need for a compromise between frequency precision and signal to noise ratio. Secondly, the method can be made to include models of the stimulus signals, so that the stimulus does not strongly interfere with the estimation process. Thirdly, the method can be arranged to make efficient use of data that has been corrupted by measurement artefacts. Fourthly, the method can be easily adapted to track DPOAEs that are changing in response to chemical or acoustic treatments. The basic modelling assumptions made are that the sum of R and D measurements can be represented as the sum of convolutions with the stimulus signal, the frequency representation of the D component is more smooth than the R component, and that a reasonable estimate of the noise level in the signal is available. These assumptions are combined into a linear convex problem. In this paper we compare the proposed approach with three other methods. While it is not superior to the earlier methods at every frequency, it does offer some improvement, particularly with regards reducing the contamination of D by R.

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