数字助听器中基于两步降噪的多通道频响补偿算法

目的 针对数字助听器中现有频响补偿算法在噪声环境下无法满足耳聋者言语可懂度和舒适度的问题,本文提出了基于两步降噪的多通道频响补偿算法。方法 该算法首先通过计算通用单通道语音增强的先验信噪比和系统增益,并利用前后语音帧间的相关性,结合自适应先验信噪比平滑因子对先验信噪比估计进行优化,实现两步降噪;然后采用gammatone滤波器对增强后的语音进行非均匀多子带分解,在每个子带中采用两次插值;最后依据耳聋者的听力曲线对每个频带进行频响补偿。结果实验表明,该算法能够有效地去除了噪声对频响补偿的影响,保护了共振峰结构,获得更多增益信息,补偿了患者缺失的语音能量,满足了听力损失者的听力需求。结论 基于两步降噪的多通道频响补偿算法有效提高了听障患者感知语音的可懂度和舒适度。     

基于Gammatone滤波器组分解的数字助听器频响补偿算法

目的针对现有数字助听器中的多通道频响补偿算法容易破坏语音信号的共振峰结构,致使频响补偿后语音信号的可懂度、清晰度和舒适度降低等问题,提出一种基于人耳听觉特性的多通道频响补偿算法。方法首先采用一种可以模拟人工耳蜗模型的Gammatone滤波器组,然后通过滤波处理把输入信号分为32个频带,并依据耳聋者的听力曲线对每个频带进行频响补偿。最后采用语音信号每个通道的声压级,以及从共振峰结构和主观测试对比该算法与基于Bark域的非均匀滤波器组分割频率的算法的优越性。结果通过该算法处理后的语音信号可以很好地满足不同听力损失者的听力要求。相对于比较算法,该算法语音信号的共振峰结构完整性更好,在不同的声压级下,该算法的语句可懂度提高10%以上。结论基于Gammatone滤波器组分解的数字助听器频响补偿算法优于对比算法,并且提高了听力损失者的语句可懂度和舒适度。     

多通道高信噪比神经信号放大器的设计与测试

我们设计和装配了一款高信噪比的神经信号放大器,该放大器在实验中能记录到稳定且高信噪比的神经脉冲信号.     

多通道高信噪比神经信号放大器的设计与测试

我们设计和装配了一款高信噪比的神经信号放大器,该放大器在实验中能记录到稳定且高信噪比的神经脉冲信号。     

复合自适应滤波器用于体感诱发电位信噪比的提高

本研究以可靠、快速提取体感诱发电位为目标,试图解决相干叠加方法既费时又不能反映体感诱发电位时变特征的缺点。运用以自适应噪声减法器和自适应增强器为基础构造的复合自适应滤波器提取体感诱发电位。仿真实验表明,运用复合自适应滤波器可实现从强噪声背景中快速提取体感诱发电位,能更快地识别体感诱发电位的潜伏期及幅值,并且系统性能稳定。     

自适应噪声减法器用于提高体感诱发电位信噪比

目的利用自适应方法实现从强噪声背景中快速提取体感诱发电位信号。方法采用最小均方误差算法对自适应噪声减法器进行设计，以15例接受脊柱外科手术的病人为对象，将600次刺激响应的SEP做叠加平均得到的信号作为标准的SEP模板，用脑电图（EEG）加白噪声来模拟临床中干扰SEP的噪声。通过仿真实验检验自适应噪声减法器提取SEP信号的性能。结果自适应噪声减法器可以将信噪比提高25dB左右：自适应噪声减法器提取出的SEP信号与SEP模板信号间潜伏期和峰峰幅值的百分比误差均分别小于1％和6％。结论运用白适应噪声减法器可以实现从强噪声背景中快速提取SEP，在提高检测信号信噪比的同时。更快地识别SEP的潜伏期及幅值。     

基于多通道自适应自回归模型脑-机接口系统特征的提取

背景：由于脑电图信号的非平稳特性,脑-机接口系统至今仍然没有走出实验室,制约脑-机接口实用的主要原因之一是由于被试生理或心理状态的干扰下,脑电特征信号动态变化,难以得到稳定可靠的分类特征。 目的：观察动态提取基于左手、右手和脚3种运动想象时的脑电信号分类特征,提高在线脑-机接口系统分类准确率和反应速度。 方法：共有3位自愿受试者参加了实验,按照屏幕上的提示分别想象左手、右手和脚3种运动,对采集到的脑电图信号,首先通过带通及拉普拉斯滤波,去除眼电等干扰;其次提取改进的多变量自适应自回归模型模型参数作为分类特征;最后与传统的自适应自回归模型和自回归模型方法进行了比较。 结果与结论：结果表明改进的多通道自适应自回归模型算法能够比较稳定的提取出对应左手、右手和脚的分类特征,有利于进一步改进在线脑-机接口数据分析算法的自适应能力,促进脑-机接口系统的实际应用。     

基于变分法的超声图像斑点噪声自适应滤波算法

各向异性扩散模型在去除超声图像斑点噪声时不能有效保护图像细节,针对上述问题本文提出基于变分法的自适应最小能量去噪模型.首先直接将由微分方程表示的各向异性扩散模型转化为最小能量变分模型;然后引入欧拉弹性能量模型,在去除噪声的同时有效地保护和增强图像细节.同时为了解决数值求解过程中出现的迭代次数与迭代步长的矛盾,本文还提出迭代停止准则和自适应变步长去噪算法.仿真和真实超声图像的实验结果表明基于变分法的超声图像斑点噪声自适应滤波算法在去噪的同时能够很好地保护细节信息,而且能有效地减少迭代次数.     

基于DLL的Labview环境多通道数据采集的实现方法

介绍了基于VC 6.0环境编写数据采集卡动态链接库(DLL)驱动程序的步骤,并给出在Lab view环境下调用DLL实现多通道数据采集的方法。最后通过对电子机柜横梁做激励试验,验证了数据采集系统的可行性。     

自适应超分辨率图像的重建算法

背景：超分辨率重建已经在视频、遥感等许多领域内的到广泛的研究与应用。 目的：介绍一种自适应超分辨率重建算法,以期从序列低分辨率图像中重建出高分辨率图像。 方法：采用常数λ=2/3作为正则化参数和自适应步长作为第一种方案。第二种方案充分考虑到低分辨率图像中的运动误差估计、点扩散函数以及加性高斯白噪声对重建算法的影响。实验构造出新的非线性自适应正则化函数,进而利用实验方法分析代价函数的凸性。通过数学理论,根据代价函数凸性实验得到自适应步长因子,从而改进了图像的空间分辨率和算法的收敛速度。 结果与结论：为验证此算法的有效性,采用光学图像进行实验。方案二图像峰值信噪比增高,其收敛速度为方案一的2倍以上;方案二的平均计算需要的时间为68.25 s。结果证实,自适应超分辨率图像重建算法对图像分辨率和迭代的收敛速度均改善显著,其稳定性较好。     

Effect of signal-to-noise ratio and spectral linewidth on metabolite quantification at 4 T

The accuracy and precision of measurements of metabolite concentrations from short echo-time spectra has previously been characterized at l.5 T as a function of signal-to-noise ratio (SNR) and peak linewidth. The purpose of this study was to characterize the systematic error in quantification of metabolite concentrations associated with linewidth and SNR for the major metabolites of interest in the short echo-time 1H-MR spectrum at 4 T. Simulated 4 T LASER localized spectra (TE = 46 ms) were generated with full width at half maximum (FWHM) over the range 4-14 Hz, and SNR over the range 5-500 by adding 100 Gaussian-distributed noise realizations at each combination of SNR and linewidth. Linewidth and SNR were treated as independent parameters, and therefore an increase in linewidth at a constant SNR resulted in increased metabolite areas. All spectra were fitted in the time domain using identical prior-knowledge and relative parameter starting values. Six metabolites (N-acetylaspartate, glutamate, creatine, myo-inositol, glycerophosphocholine, phosphocholine) were quantified with >90% accuracy and <10% standard deviation at SNR = 10 for linewidths ranging from 8 to 14 Hz FWHM. These simulations did not consider additional sources of variation, including eddy current artifacts, incomplete macromolecule baseline removal, and incomplete water suppression. Regardless, the results show that metabolite quantification from 4 T short echo-time 1H-MRS is sensitive to SNR and linewidth.     

DTI of human skeletal muscle: the effects of diffusion encoding parameters,signal‐to‐noise ratio and T2 on tensor indices and fiber tracts

In this study, we have performed simulations to address the effects of diffusion encoding parameters, signal‐to‐noise ratio (SNR) and T₂ on skeletal muscle diffusion tensor indices and fiber tracts. Where appropriate, simulations were corroborated and validated by in vivo diffusion tensor imaging (DTI) of human skeletal muscle. Specifically, we have addressed: (i) the accuracy and precision of the diffusion parameters and eigenvectors at different SNR levels; (ii) the effects of the diffusion gradient direction encoding scheme; (iii) the optimal b value for diffusion tensor estimation; (iv) the effects of changes in skeletal muscle T₂; and, finally, the influence of SNR on fiber tractography and derived (v) fiber lengths, (vi) pennation angles and (vii) fiber curvatures. We conclude that accurate DTI of skeletal muscle requires an SNR of at least 25, a b value of between 400 and 500 s/mm², and data acquired with at least 12 diffusion gradient directions homogeneously distributed on half a sphere. Furthermore, for DTI studies focusing on skeletal muscle injury or pathology, apparent changes in the diffusion parameters need to be interpreted with great care in view of the confounding effects of T₂, particularly for moderate to low SNR values. Copyright © 2013 John Wiley & Sons, Ltd.     

La théorie statistique de la décision: application à l''étude du rapport signal sur bruit en tomographie d''émission monophotoniqueStatistical decision theory: application to the study of signal to noise ratio in single photon emission tomography

The statistical decision theory (SDT) is applied in all direct imaging modalities. The detection stage can be quantified exactly from the ideal observer concept. The ideal observer depend on the noise power spectrum (NPS). An expression of NPS in single photon emission tomography (SPECT) of the uncertainty over the number of counts is derived in order to estimate the noise and the signal to noise ratio (SNR). The reconstruction algorithm is the method of back-projection of filtered projection. It is shown that derived expressions of noise and SNR compare well with expressions derived from classical approaches. So, we can affirm that the SDT can be considered in tomography (indirect imaging).