【作者】 刘博；

【导师】 林海军；

【作者基本信息】 哈尔滨理工大学 ， 仪器科学与技术， 2017， 硕士

【摘要】 耳声发射信号源于耳蜗,测量不同频率的耳声发射信号可以了解耳蜗不同位置毛细胞的功能状况。ABR信号产生与听神经,是表现在头顶与乳突之间的脑电信号,通过分析ABR信号可以检测出听觉中枢功能的损伤情况。对耳声发射信号和ABR信号进行提取,并进行综合性的分析与处理,就可以对被测试者的听觉功能整体状况有一个详细的了解。对于耳声发射信号,本文决定采用非线性差分平均法与时域加窗法相结合的方法来提取。本文主要针对ABR信号幅值微弱、突变性强、噪声干扰复杂等特点,分析了常用微弱信号提取方法的不足,最后选择使用HHT方法来提取含噪的ABR信号。HHT方法是专门针对非线性非平稳信号处理所设计的一种算法,非常适合对ABR信号进行处理。但是传统的HHT方法存在着模态混淆的问题,所以我们对传统的HHT算法进行了改进,提出了EHHT信号处理方法。为了验证EHHT算法的效果,本文建立了一个含噪ABR信号模型,并对该模型分别使用HHT方法和EHHT方法进行了处理。为了判断算法的优劣程度,本文提出了一种新的参数MSEP。MSEP值越接近1,去噪提取效果越好。通过分析处理后的结果,本文验证了EHHT算法要优于HHT算法,而且MSEP值也接近理想数据,验证了算法的可行性。在确定了去噪提取算法之后,本文设计了听力综合检测仪的硬件系统,将整个硬件系统分为主控制单元、听觉激励单元、ABR信号检测单元和耳声发射信号检测单元来设计,并对每个单元进行分析。最后设计了听力检测仪的上位机软件,将硬件与上位机软件连接起来进行实验。通过ABR信号、TEOAEs信号和DPOAEs信号的实验结果,验证了整个系统的可行性。更多还原

【Abstract】 Otoacoustic emissions signal originate from the cochlea.If we measured different frequencies of otoacoustic emissions,we can understand the function of hair cells at different locations within the cochlea.ABR is generated from the auditory nerve.This signal is the EEG signal between the head and the mastoid.By analyzing the ABR signal,we can detect the damage of auditory center function.We extract the otoacoustic emissions signal and ABR signal.and then conduct a comprehensive analysis and processing of the two signals,we can have an overall understanding of the hearing function of the tested.In this paper,we use the combine of nonlinear difference averaging method and time window method to extract the acoustic emission signal.This paper mainly analyzes the weakness of weak signal extraction methods for ABR signal,such as weak amplitude,strong mutation and complex noise interference.Finally,we choose to use the HHT method to extract the noisy ABR signal.The HHT method is an algorithm designed for nonlinear non-stationary signal processing.This method is very suitable for ABR signal processing.But the traditional HHT method has the disadvantage of mode confusion,so we improved the traditional HHT algorithm and we propose a EHHT signal processing method.In order to verify the effect of the EHHT algorithm,a noisy ABR signal model is established in this paper,and the HHT model and EHHT method are used to deal with the model.In order to judge the accuracy of the algorithm,this paper presents a new parameter MSEP.The closer the MSEP value is to 1,the better the effect of denoising is.By analyzing the results of the two algorithms,the EHHT algorithm is proved to be superior to the HHT algorithm and the MSEP value is closer to the ideal data.The results verify the feasibility of the algorithm.After the denoising algorithm is designed,the hardware system is designed in this paper.The whole hardware system is divided into the main control unit,the auditory excitation unit,the ABR signal detection unit and the acoustic emission signal detection unit.In this paper,we make a detailed analysis of each unit.Finally,we designed the upper computer software of the hearing detector,and connected the hardware with the host computer software to carry on the experiment.The feasibility of the whole system is verified by the experimental results of ABR signal,TEOAEs signal and DPOAEs signal.更多还原