瞬态诱发耳声发射的时频分析

本文简要介绍了基于Ｗｉｇｎｅｒ Ｖｉｌｌｅ分布及其改进型的时频分析方法及其数字实现方法 ,然后 ,利用计算机计算了来自正常人耳的瞬态诱发耳声发射 (ＴｒａｎｓｉｅｎｔＥｖｏｄｅｄＯｔｏａｃｏｕｓｔｉｃＥ ｍｉｓｓｉｏｎｓ ,ＴＥＯＡＥｓ)的时频分布。根据试验和计算结果 ,分析了其时频分布的特点 ,并对不同的频率成分与潜伏期的关系进行了描述。0　引言耳声发射 (ＯｔｏａｃｏｕｓｔｉｃＥｍｉｓｓｉｏｎｓ ,ＯＡＥｓ)是一种产生于耳蜗 ,经听骨链及鼓膜传导释放入外耳道的音频能量信号 ,它以机械振动的形式起源于耳蜗 ,是由耳蜗耗…     

用STFT分析瞬态诱发耳声发射的时频特征

瞬态诱发耳声发射是一种时变的声信号,用传统的傅立叶变换无法完全表示其信息.本文介绍了用短时傅立叶变换分析瞬态诱发耳声发射方法,并给出了其时频分布的实验结果,分析了其各个频率成份出现的不同时刻及持续时间.本文还对瞬态诱发耳声发射中的伪迹出现的时间和频率作了分析,指出伪迹在时频域是和有用信号分离的,理论上可以通过时频滤波器去除.     

耳声发射的研究进展：耳声发射检测系统

耳声发射是一种产生于耳蜗经听骨链及鼓膜传导释放入外耳道的音频能量。它快速、无损、客观地反映了耳蜗外毛细胞的功能状态，在临床诊断和听力筛查方面具有广阔的前景。本文将对目前的ＯＡＥ检测系统作一概述。     

正常人耳瞬态诱发耳声发射的时—频分布初步分析

本文建立了瞬态诱发耳声发射时－频分布分析方法,在此基础上首次直观、清晰地展现了ＴＥＯＡＥ在正常人耳的个体差异及规律性,提出正常人耳ＴＥＯＡＥ频率变化的多种形态;通过对ＴＥＯＡＥ时－频关系、潜伏期等的研究,提出了探讨ＴＥＯＡＥ产生机理的新思路。     

耳声发射的研究进展——耳声发射检测系统

耳声发射（ＯＡＥ）是一种产生于耳蜗经听骨链及鼓膜传导释放入外耳道的音频能量。它快速、无损、客观地反映了耳蜗外毛细胞的功能状态，在临床诊断和听力筛查方面具有广阔的前景。可靠地提取、识别、分析ＯＡＥ信号是其应用于临床的前提。本文将对目前的ＯＡＥ检测系统作一概述。     

耳声发射及其信号处理问题

本文从信号处理角度对近年来国外耳科研研究的热点－耳声发射进行了综述，内容涉及耳声发射研究的历史发展，它的产生机理，临床意义及检测方法等，重点在于介绍它的信号特点及其信号处理中存在的主要问题。     

耳声发射的建模与小波分析

本文在介绍本 组前已提出的耳 声发射全耳模 型的基础上, 进一步 讨论了 瞬态诱 发耳 声发射 信号 的连续小波分析 。分析了变换算 法和基本小波 的选择,得出 其不同 频率成 分与潜 伏期 的关系 以及利 用小波变换进行 耳蜗病变部 分定 位的 可能 性。把 仿真 结果与 对临 床数 据的 类似 分析 进行 比较 ,其概貌与趋势 基本一致     

正常人耳瞬态诱发耳声发射的时－频分布初步分析

本文建立了瞬态诱发耳声发射（ Ｔｒａｎｓｉｅｎｔ Ｅｖｏｋｅｄ Ｏｔｏａｃｏｕｓｔｉｃ Ｅｍｉｓｓｉｏｎ， ＴＥＯＡＥ）时－频分布分析方法，在 此基础上首次直观、清晰地展现了ＴＥＯＡＥ在正常人耳的个体差异及规律性，提出正常人耳ＴＥＯＡＥ频率变化的多种形态；通过对 ＴＥＯＡＥ时－频关系、潜伏期等的研究，提出了探讨 ＴＥＯＡＥ产生机理的新思路。     

自发耳声发射的检测方法及其信号特征

本文综述了近年来内外关于自发耳声发射的基础及理论研究，其中包括自发耳声发射的检测方法，信号处理及信号特征等方面，自发耳发射的发现，对其础医学及神经生理的研究有重要的意义。     

272例早产儿耳声发射分析

目的探讨早产儿用耳声发射发现听力障碍的情况.方法对2001年7月～2003年5月间在我院出生的早产儿272例及同期分娩足月新生儿4801例采用耳声发射分析仪进行听力测试在分娩后3～5d测试一次,未通过者在出生42d再测试一次,再未通过者在出生90d进行复测,如三次均未通过则进行ABR检查,二次异常确诊为听力障碍.结果早产儿组出生3～5d异常率为46.69%,足月新生儿组为7.02%,P＜0.001,出生42天早产儿组异常率为6.25%,足月新生儿组为1.99%,P＜0.001,出生90天早产儿组异常率3.68%,足月新生儿组为1.02%,P＜0.001,ABR结果,早产儿组发病率为1.1%,足月新生儿组为0.19%,P＜0.05.讨论早产儿由于各器官发育不够成熟,耳蜗毛细胞也未完全发育,故早产儿听力障碍发生率明显高于足月新生儿组,要求作好产前检查,指导孕期卫生,尽量预防早产发生.同时应作好新生儿听力筛查,早期发现,早期干预,以减少聋哑的发生.     

模拟耳声发射信号的传统去噪方法

耳声发射是近年听觉生理、听觉临床、声学等领域的研究热点.本文尝试通过建立仿真耳声发射信号,再加上噪音信号,合成带噪音的模拟耳声发射信号,然后采用传统的方法进行去噪,分析去噪效果,得出传统消噪方法的误差范围.     

电刺激诱发豚鼠耳声发射及其畸变产物

为了了解活体耳蜗外毛细胞的电勇动性及其耳蜗的微机械作用，用声频范围内的正弦交流电对豚鼠耳蜗行蜗外电刺激，用麦克风记录豚鼠外耳道的声压级，用ＦＦＴ谱分析仪分析并记录电诱发耳声发射及其畸变产物。     

听觉脑干诱发电位及畸变产物耳声发射在婴幼儿？…

目的 对婴幼儿听力进行正确的定量定位评估。为婴幼儿早期听力语言康复治疗提供依据。方法 以听觉脑干诱发电位（ＡＢＲ）、畸变产物耳声发射（ＤＰＯＡＥ）,对疑听力障碍的１００例婴幼儿进行听力检测,记录Ⅴ波反应域,ＤＰＯＡＥ幅值、ＤＰ－ＮＦ幅值差。结果 以ＡＢＲ Ｖ波反应阈４０ｄＢ为正常判定标准。２００例中ＡＢＲ异常１３５耳（６７．５％）,ＤＰＯＡＥ以超过本底噪音１０ｄＢ为有效,与正常组比较,ＤＰＯＡＥ异     

中耳功能异常对畸变产物耳声发射测试的影响

目的 探讨中耳传音功能异常对畸变产物耳声发射（DPOAE）测试结果的影响程度并在临床应用中加以识别和剔除。方法 将年龄2月－11岁56例（107耳）小儿依听力损失类型分为感音性聋组 和传导性聋组,并设置正常听力对照组,应用GSI 60耳声发射仪分别观察其DPOAE的DP检出率、DP幅值、DP与NF幅值差及相同参数条件下DPOAE测试时间。结果 耳蜗功能严重受损和渗出性中耳炎所记录到的DPOAE各测量参数之间的差异无统计学意义（P＞0．05）。结论 中耳积液导致的中耳传音功能障碍对DPOAE测试结果的影响,与耳蜗功能严重损害时所记录到的DPOAE参数变化,在临床检测中难以区分。因此,临床上在应用DPOAE进行听力评估之前,首先要检测受检者的中耳功能,剔除其对DPOAE检测结果的影响,确保结果的可靠性。     

Otoacoustic emissions and improved pass/fail separation using wavelet analysis and time windowing

A new method is presented for the purpose of improving pass/fail separation during transient evoked otoacoustic emission (TEOAE) hearing screening. The method combines signal decomposition in scales using the discrete wavelet transform, non-linear denoising and scale-dependent time windowing. The cross-correlation coefficient between two subaveraged, processed TEOAE signals is used as a pass/fail criterion and assessed in relation to the pure-tone, mean hearing level. The performance is presented in terms of receiver operating characteristics for a database of 5214 individuals. The results show that the specificity improves from 68% to 83% at a sensitivity of 90% when compared with the conventional wave reproducibility parameter.     

听觉诱发电位信号的采集,处理与分析

本文结合听觉诱发电位信号特点,概要地叙述了听觉诱发电位数据的采集、叠加平均技术及信号的处理、分析。介绍了用PC-286微机实现上述功能的方法。结合我们临床工作实践,介绍了听性脑干反应、耳蜗电位的时域分析、相关函数分析以及频阈分析,如数字滤波、自回归模型参数谱估计以及AR模型参数逐步判别分析的计算机实时处理、分析的软、硬件实现方法及其临床意义。     

肺音信号的时变谱分析

肺音信号谱特性是肺音学研究的重要课题，本文利用ＦＦＴ谱分析技术，对正常肺音（肺泡呼吸音，气管音）与异常肺音（哮呜音，喘呜音）进行了时变谱研究，获得了上述各种肺音信号的谱特性，实验结果表明；时变谱分析是肺音分析的有效方法。     

Phase Spectral Analysis of EEG Signals

A new method of phase spectral analysis of EEG is proposed for the comparative analysis of phase spectra between normal EEG and epileptic EEG signals based on the wavelet decomposition technique. By using multiscale wavelet decomposition, the original EEGs are mapped to an orthogonal wavelet space, such that the variations of phase can be observed at multiscale. It is found that the phase (and phase difference) spectra of normal EEGs are distinct from that of epileptic EEGs. That is the variations of phase (and phase difference) of normal EEGs have a distinct periodic pattern with the electrical activity proceeds in the brain, but do not the epileptic EEGs. For epileptic EEGs, only at those transient points, the phase variations are obvious. In order to verify these results with the observational data, the phase variations of EEGs in principal component space are observed and found that, the features of phase spectra is in correspondence with that the wavelet space. These results make it possible to view the behavior of EEG rhythms as a dynamic spectrum.     

Spectral Analysis of the Visual Evoked Potential (VEP): Effects of Stimulus Luminance

Power spectral analysis was performed on the visual evoked potentials (VEPs) of subjects who had participated in an augmenting-reducing study. Six flash luminances were used (0.31, 0.65, 1.25, 2.5, 5.0, and 10.0 fL). EEG recordings were taken from C_z O₁, O₂, T₃, and T₄ scalp locations. Power in six frequency ranges was examined (0–2, 2–6, 6–10, 10–14, 14–18, and 18–22 Hz). Power in the lowest three frequency ranges increased linearly with stimulus luminance at all electrode sites. Power in the highest three ranges increased linearly with luminance at occipital sites only. Power was greater in the left hemisphere than in the right for 18–22 Hz activity recorded at occipital locations. The reverse asymmetry occurred for 6–14 Hz activity recorded at temporal locations. The results suggest that individual differences in stimulus control in EEG recordings taken from scalp locations overlying nonspecific cortex are due primarily to the contributions of higher frequency components of the VEP spectrum. A thalamo-cortical model of stimulus control is described.     

Power Spectral Analysis of Mammographic Parenchymal Patterns for Breast Cancer Risk Assessment

PURPOSE: The purpose of the study was to evaluate the usefulness of power law spectral analysis on mammographic parenchymal patterns in breast cancer risk assessment. MATERIALS AND METHODS: Mammograms from 172 subjects (30 women with the BRCA1/BRCA2 gene mutation and 142 low-risk women) were retrospectively collected and digitized. Because age is a very important risk factor, 60 low-risk women were randomly selected from the 142 low-risk subjects and were age matched to the 30 gene mutation carriers. Regions of interest were manually selected from the central breast region behind the nipple of these digitized mammograms and subsequently used in power spectral analysis. The power law spectrum of the form P(f) = B/f(beta) was evaluated for the mammographic patterns. The performance of exponent beta as a decision variable for differentiating between gene mutation carriers and low-risk women was assessed using receiver operating characteristic analysis for both the entire database and the age-matched subset. RESULTS: Power spectral analysis of mammograms demonstrated a statistically significant difference between the 30 BRCA1/BRCA2 gene mutation carriers and the 142 low risk women with an average beta values of 2.92 (+/-0.28) and 2.47(+/-0.20), respectively. An A (z) value of 0.90 was achieved in distinguishing between gene mutation carriers and low-risk women in the entire database, with an A (z) value of 0.89 being achieved on the age-matched subset. CONCLUSIONS: The BRCA1/BRCA2 gene mutation carriers and low-risk women have different mammographic parenchymal patterns. It is expected that women identified as high risk by computerized feature analyses might potentially be more aggressively screened for breast cancer.