采用小波变换对自发耳声发射信号的检测研究

Continuous wavelet transform for the detection of spontaneous otoacoustic emissions

自发耳声发射信号的检测方法通常采用周期图法 ,为了推动自发耳声发射在临床生理和病理上的应用 ,需要有较高频率分辨率和准确率的稳健算法推向临床。论文在研究自发耳声发射信号的检测方法时 ,通过对连续小波变换的两种快速算法的比较 ,发现调频 Z变换方法比 Mellin变换方法在提高自发耳声发射信号的频率分辨率方面具有更大的优越性 ,提高了自发耳声发射信号谱峰识别的准确性和简易性。调频 Z变换方法对推动自发耳声发射在临床生理和病理上的应用有更大的潜力。

The detection of spontaneous otoacoustic emissions signal usually uses periodograms. To improve the clinical application in physiology and pathology of spontaneous otoacoustic emissions, a robust algorithm is needed with high frequency spectrum resolution and accuracy. This study of the detection methods for spontaneous otoacoustic emissions compares two fast algorithms for continuous wavelet transforms, the Chirped Z transform and the Mellin transform. The result shows that the Chirped Z transform is better than the Mellin transform for improving frequency spectrum resolution and for accurately picking the peak value. The Chirped Z transform has more potential for facilitating the use of the spontaneous otoacoustic emissions in clinical applications.