论文标题
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Denoising Click-evoked Otoacoustic Emission Signals by Optimal Shrinkage
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论文摘要
在临床上使用点击诱发的耳声发射（CEOAE）作为推断耳蜗功能是否正常的客观方法。但是，由于CEOAES的声压水平通常比背景噪声低得多，因此通常需要数百次重复（即使不是数千个重复）才能以足够的精度估算信号。在本文中，我们建议在有限的测量时间内通过在两个不同的设置中提高CEOAE信号的信噪比（SNR）：基于协方差的OS（COS）和奇异值分解（SVD）的OS（SOS）。通过模拟和分析人类CEOAE数据，COS始终从基准方法（BM）中降低了噪声，并将SNR降低了1至2 dB，该方法基于计算中位数。在模拟中，SOS实现了2至3 dB的SNR增强，并且当BM获得的SNR低于0 dB时，可以在真实记录中增强SNR的能力。 OS的一个吸引人的属性是，它会产生信号矩阵的每个单独列的估计。该属性使得在人工耳蜗条件不是严格固定的情况下，可以在更长的时间内调查CEOAE动力学。
Click-evoked otoacoustic emissions (CEOAEs) are clinically used as an objective way to infer whether cochlear functions are normal. However, because the sound pressure level of CEOAEs is typically much lower than the background noise, it usually takes hundreds, if not thousands of repetitions to estimate the signal with sufficient accuracy. In this paper, we propose to improve the signal-to-noise ratio (SNR) of CEOAE signals within limited measurement time by optimal shrinkage (OS) in two different settings: the covariance-based OS (cOS) and the singular value decomposition (SVD)-based OS (sOS). By simulation and analyzing human CEOAE data, the cOS consistently reduced the noise and enhanced the SNR by 1 to 2 dB from a baseline method (BM) that is based on calculating the median. The sOS achieved an SNR enhancement of 2 to 3 dB in simulation, and demonstrated capability to enhance the SNR in real recordings when the SNR achieved by the BM was below 0 dB. An appealing property of OS is that it produces an estimate of every individual column of the signal matrix. This property makes it possible to investigate CEOAE dynamics across a longer period of time when the cochlear conditions are not strictly stationary.
