Signal Processing Of Transiently Evoked Otoacoustic Emissions

Otoacoustic Emissions (OAEs) diagnoses is one of the most important means in clinic hearing diagnoses. However, its detected validity is not so enough as all that needs to be further investigated. In this paper, according to the characteristic of OAEs and the deficiency of conventional processing method, a wavelet transform (WT) theory was presented to denoise to enhance detected validity and decrease detected time. Based on LabVIEW software, a Transiently Evoked Otoacoustic Emissions (TEOAEs) signal processing system with high expansibility has been built. Main results are shown as follows:1. The effectiveness of using WT to process non-stationary signals was confirmed by an example.2. A TEOAEs signal processing system has been built based on LabVIEW software. The system can process OAEs signal with conventional method and WT method, then calculates correlation ratio and Signal-to-Noise of the results.3. Correlation ratio, Signal-to- Noise and detected validity are enhanced and detectd time is decreased by changing three WT parameters: wavelet decompose level, wavelet basis and threshold choice method.4. The system has good augmentability, and the handling capacity and detected validity can be enhanced by integrateing signal processing module.5. The system is only a signal processing system, and it has not signal acquisition function. Further studies need to be done to build a practical signal detection system.