一种用ICA去除瞬态诱发耳声发射伪迹的新方法

如何去除伪迹是瞬态诱发耳声发射检测中一个关键的问题。本研究提出了一种用ICA去除伪迹的新方法。首先用四组线性增长的刺激声在耳道内录音 ,得到的波形是瞬态诱发耳声发射和伪迹的混叠。因为伪迹和瞬态诱发耳声发射是统计独立的 ,而且伪迹随刺激声的变化线性增长 ,而瞬态诱发耳声发射随刺激声的变化非线性增长 ,逐渐趋于饱和 ,所以它们在混叠信号中具有不同的混叠系数。用ICA算法可以将各独立分量及混叠矩阵估计出来 ,伪迹是其中的一个独立分量。然后将伪迹的波形置零后再进行一次混叠 ,便达到了去除伪迹的目的。最后通过与传统的DNLR方法比较 ,证明这种方法是有效的     

小波变换在去除瞬态诱发耳声发射中刺激伪迹的应用

耳声发射是目前对外周听觉系统是否完好无损评价的客观指标。在瞬态刺激诱发耳声发射的初始部分通常混杂有刺激伪迹成分（主要指耳道对刺激声直接反射回声），它阻碍了具有短潜伏期的高频蜗响应，这就使得ＯＡＥｓ的测量在临床使用中受到了很多的限制。我们提出了一种基于离散小波变换预处理的去除伪迹方法，该方法不仅能够有效地去除刺激伪迹，而且能够有效的提高耳声发射的信噪比。     

瞬态诱发耳声发射信号的小波阈值去噪

目的瞬态诱发耳声发射信号是从人的外耳检测到的微弱的音频能量,在测试过程中常混入各种随机噪声,本文尝试对瞬态诱发耳声发射信号进行去噪,以提高信号的信噪比,为进一步的临床应用(如频谱分析)奠定基础.方法小波变换阈值法.选用了sym8小波,软阈值处理方法,阈值选取规则为Minimax法.结果去噪后相关系数加大,信噪比提高.信噪比平均提高约10%.结论小波变换阈值法对TEOAE信号去噪取得了较好的效果.     

瞬态诱发耳声发射(TEOAE)的建模与仿真

耳声发射是当前耳科学研究的热点。由于它的检测简便、客观、无损、迅速 ,因此一般认为它将与听觉诱发响应一起成为临床上听觉系统功能测试的两项互补的客观手段。本文借助听觉外周系统的同胚模型对瞬态诱发耳声发射进行了深入研究。通过对模型参数的辨识 ,我们不仅使得仿真的耳声发射信号具有与临床相近似的特征 ,而且进一步证实了耳声发射与耳蜗外毛细胞功能的关系     

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     

耳声发射测试系统传感装置的研制

耳声发射在现代听力学中已得到广泛关注。这是一种安全、简便的测试方法。文中介绍了耳声发射测试方法的发展现状，现在配合听觉诱发电位测试仪器所用的探头以及针对探头所存在的问题而采取的解决办法。我们现在研制的探头配合骨导短声刺激进行测试，通过一定技术处理在外耳道内部提取出微弱的耳声发射信号，与听觉诱发测试系统连接。作者讨论一些特定的技术处理，探头的设计以减少电磁干扰及伪迹信号，声阻抗元件的设置以保证鼓膜处于正常状态等。对正常人耳进行测试，并以耦合腔代替人耳进行对照，对其进行了时、频两域的分析。     

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…     

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.     

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。     

5—1 耳声发射的测量与分析

本文首先描述了一套在人的封闭耳道内记录耳声发射的装置的设计和制作。其中包括声学系统和电学系统以及存一台Z80单板微机上进行数字信号处理的计算机程序。声探头是真实记录的关键部件。诱发性耳声发射的记录主要依靠时域信号平均技术。在声信号测试过程中,存在着两类噪声。分析指出,在程序中采用限幅筛选的办法来去除含第二类噪声(非记录系统本底噪声)的样本,减小了随机过程的非平稳用素,可以有效提高信号处理质量,频域处理以FFT为基础。介绍了提高FFT效率的程序设计要点。用周期图迭加法可以获得自发性耳声发射的频谱估计。对于系统的定标,也作了说明。     

Biomedical signal processing (in four parts)

This is the second in a series of four tutorial papers on biomedical signal processing, and it concerns the relationships between commonly used frequency transforms. It begins with the Fourier series and Fourier transform for continuous time signals and extends these concepts for aperiodic discrete time data and then periodic discrete time data. The Laplace transform is discussed as an extension of the Fourier transform. The z-transform is introduced and the ideas behind the chirp-z transform are described. The equivalence between the time and frequency domains is described in terms of Parseval's theorem and the theory of convolution. The use of the FFT for fast convolution and fast correlation is described for both short recordings and long recordings that must be processed in sections.     

Computer aided analysis of phonocardiogram

In the present paper analysis of phonocardiogram (PCG) records are presented. The analysis has been carried out in both time and frequency domains with the aim of detecting certain correlations between the time and frequency domain representations of PCG. The analysis is limited to first and second heart sounds (S1 and S2) only. In the time domain analysis the moving window averaging technique is used to determine the occurrence of S1 and S2, which helps in determination of cardiac interval and absolute and relative time duration of individual S1 and S2, as well as absolute and relative duration between them. In the frequency domain, fast Fourier transform (FFT) of the complete PCG record, and short time Fourier transform (STFT) and wavelet transform of individual heart sounds have been carried out. The frequency domain analysis gives an idea about the dominant frequency components in individual records and frequency spectrum of individual heart sounds. A comparative observation on both the analyses gives some correlation between time domain and frequency domain representations of PCG.     

Computer aided analysis of phonocardiogram

In the present paper analysis of phonocardiogram (PCG) records are presented. The analysis has been carried out in both time and frequency domains with the aim of detecting certain correlations between the time and frequency domain representations of PCG. The analysis is limited to first and second heart sounds (S1 and S2) only. In the time domain analysis the moving window averaging technique is used to determine the occurrence of S1 and S2, which helps in determination of cardiac interval and absolute and relative time duration of individual S1 and S2, as well as absolute and relative duration between them. In the frequency domain, fast Fourier transform (FFT) of the complete PCG record, and short time Fourier transform (STFT) and wavelet transform of individual heart sounds have been carried out. The frequency domain analysis gives an idea about the dominant frequency components in individual records and frequency spectrum of individual heart sounds. A comparative observation on both the analyses gives some correlation between time domain and frequency domain representations of PCG.     

Suppression of respiratory motion artifacts in magnetic resonance imaging

Anatomical structures that are displaced periodically during respiration are repeated as ghosts in magnetic resonance (MR) images. These ghosts can be suppressed in many ways: the averaging of multiple sets of data, respiratory gating, deliberate positioning of ghosts, and respiratory ordering of phase encoding. Each method has a unique mechanism, which is described in detail. A theoretical investigation has been conducted into the effects that the methods have on the point spread function of a moving point. Data acquired in Fourier imaging are actually in the spatial frequency domain, so that respiratory motion can be regarded as a function of spatial frequency. The four methods above modify this functional dependence in different ways, allowing a unified comparison. Motion artifact suppression imposes additional constraints on image acquisition, which can prolong the imaging time. A technique has been developed that keeps the imaging time short by using the configuration of the subject to regulate the timing of image acquisition.     

小波分析理论在脑电分析中的应用

小波变换是一种把时间、频率（或尺度）两域结合起来的分析方法。它具有：（１）多分辨率；（２）相对带宽恒定；（３）适当地选择基本小波，可使小波在时、频两域都具有表征信号局部特征的能力的特点，被誉为“分析信号的显微镜”。本系统以Ｗｉｎｄｏｗｓ为操作系统平台，将小波变换用于脑电信号分析，实现病历管理，１００Ｈｚ脑电信号采样，１０分钟脑电数据存储等功能，是一个在Ｗｉｎｄｏｗｓ３．１下开发的脑电分析系统。从脑电信号小波变换后的波形可以看出，各尺度信号不仅反映信号的频率信息，同时也反映信号的时间信息，意即反映此时ＥＥＧ的状态。而传统的傅里叶分析只能获得信号的整体频谱，不能反映时域信息     

Short time spectrum discrimination between transient evoked otoacoustic emission and stimulus artifact

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A stimulated echo artifact from slice interference in magnetic resonance imaging

When multiple slices are imaged with a short time between slice acquisitions, a disturbing line artifact along the direction of frequency encoding is often seen across the center of the images. The artifact consists of alternating bright and dark pixel intensities. In this paper, we show that the artifact is due to slice interference, and is caused by stimulated echoes that are produced in the regions of overlap between slices. A theoretical analysis of the formation of these stimulated echoes leads to ways of reducing the artifact, which are verified experimentally. The artifact can be suppressed most conveniently by extending the duration of the read gradient beyond the sampling window.     

Ultrasonically-induced Lorentz force tomography

Electrical conductivity can be measured using the ultrasonically-induced Lorentz force. An ultrasonic wave is passed through tissue in the presence of a magnetic field. Moving charges in a magnetic field are subject to the Lorentz force, which acts as the source of current and potential. This paper shows that ultrasonically-induced Lorentz force imaging can be formulated in a way that makes it similar to tomography: an image can be reconstructed using waves propagating in various directions. More specifically, measuring the dipole strength for a particular direction and wavelength is equivalent to measuring the Fourier transform of the conductivity distribution at one point in frequency space. Measurements at a variety of wavelengths and directions are equivalent to mapping the Fourier transform of the conductivity distribution. The conductivity can then be found by an inverse Fourier transform.