小波变换模极大值重建检测瞬态诱发耳声发射  

Detection of transient evoked otoacoustic emissions using wavelet transform modulus maxima reconstruction

作　　者：叶万兴[1] 叶大田[1] 曹宇[1] 

机构地区：[1]清华大学生物医学工程系,北京100084

出　　处：《清华大学学报（自然科学版）》2003年第9期1218-1221,共4页Journal of Tsinghua University(Science and Technology)

基　　金：国家自然科学基金资助项目(39870212)

摘　　要：为提高检测效率,将基于小波变换的奇异性检测技术引入到瞬态诱发耳声发射(TEOAEs)检测中,提出了小波变换模极大值重建(WTMMR)检测TEOAEs的新方法。该方法采用多孔算法对A、B缓冲区数据分别进行二进离散小波变换,通过比较A、B间各尺度下小波变换模极大值的异同,确定其中的共同模极大值,采用共轭梯度法对它们进行重建,得到TEOAEs。69例TEOAEs实测结果表明:在累加次数较少时,由此法所获TEOAEs的总相关率明显高于传统相干平均方法。这意味着此法检测TEOAEs时比相干平均法更有效,可在TEOAEs少次提取中发挥重要的作用。Singularity detection technology using wavelet was used to detect transient evoked otoacoustic emissions (TEOAEs). The method was based on wavelet transform modulus maxima reconstruction (WTMMR). The test data in two independent buffers A and B were decomposed using the dyadic discrete time wavelet transform 'à trous' algorithm. The wavelet coefficients in each scale were compared to select the common wavelet transform modulus maxima of A and B to reconstruct the TEOAEs signal. The iterative reconstruction algorithm used the conjugate gradient method. TEOAEs tests with 69 ears showed that the overall TEOAEs correlation coefficient obtained using WTMMR was much better than that obtained by the traditional ensemble averaging (EA) method when few test sweeps were used. This result verifies that WTMMR is much more effective than EA in detecting TEOAEs so WTMMR will play an important role in singletrail estimation of TEOAEs.

关 键 词：瞬态诱发耳声发射 小波变换 模极大值 共轭梯度法 声信号重建 声信号检测 

分 类 号：TN911.23[电子电信—通信与信息系统] R764.04[电子电信—信息与通信工程]