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探讨对自发耳声发射信号进行较高频率分辨率和准确率的稳健检测算法以使其应用于临床。方法采用改进的周期图法、AR模型及小波变换方法 ,研究自发耳声发射信号的检测算法。结果改进的周期图法和小波变换方法比目前临床所采用的检测算法在准确检测谱峰峰值及其位置、高分辨率提取信号频谱特征等方面 ,具有更大的优越性。结论改进的周期图法和小波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巨大的潜力。
To discuss the robust detection algorithm of high frequency resolution and accuracy of spontaneous otoacoustic emission signals for clinical application. Methods The improved periodic graph method, AR model and wavelet transform method were used to study the detection algorithm of spontaneous otoacoustic emission signals. Results The improved periodic graph method and wavelet transform method have more advantages than the current clinical detection algorithms in accurately detecting the peak and peak position of the spectrum and the spectral characteristics of the high-resolution extracted signal. Conclusion The improved periodic graph method and wavelet transform method have great potential to promote the application of spontaneous otoacoustic emissions in clinical physiology and pathology.