Wavelet Transform Based Denoising in Transient Evoked OAE Measurement

小波轉換在耳聲反射信號的時頻域分析與雜訊消除之研究

吳漢章(Han-Chang Wu) ； 楊順聰(Shuenn-Tsong Young) ； 郭德盛(Te-Son Kuo)

《Journal of Medical and Biological Engineering》 22卷4期 (2002/12) Pp. 171-181

摘要

耳聲反射信號是在經過聲音信號的刺激後，經過耳蝸反射後在外耳道中所收集到的聲音信號。由於耳聲反射信號的特性與耳蝸如何轉換聲音為電信號的生理結構相似，耳聲反射已被利用在新生兒聽力篩選與高危險群勞工聽覺監控的應用中。傳統上臨床人員使用頻譜分析做為信號處理的基礎。
在本論文中，我們使用時頻域分析來解析耳聲反射信號。透過模擬信號的研究，小波轉換是在時頻域分析方法中，最適合應用在耳聲反射信號處理上。藉由小波轉換，我們可以有效偵測不同頻帶的耳聲反射信號的發生時間，作為判斷是否為有效信號，作為聽力篩選的基礎。
我們發展了一套以數位信號處理器為設計基礎的可攜式耳聲反射系統。我們也提出了以小波收縮方法來主動抑制所量測之耳聲反射信號中的環境噪音，取代傳統量測系統中所使用的平均法，可以有效縮短量測時間，並透過數位信號處理器強大的運算能力實現在量測系統中，增加可攜式耳聲反射儀的可用度。

關鍵字

耳聲反射信號 ； 小波轉換 ； 時頻域分析 ； 雜訊消除

並列摘要

The major purpose of this paper is to investigate the theories of various time-frequency analysis (TFA) and its capabilities in representing TEOAE signals. Owing to the tiny, noisy and nonstationary characteristics of TEOAE signals, conventional time- and frequency-domain based analysis are not adequate to extract all the information embedded within the original signals. TFAs can effectively decompose the original signals into time-frequency distributions (TFDs) that can provide both time and frequency resolutions. More precise medical diagnosis can thus be achieved. Because TFAs can represent signal features more efficiently, higher performance is accomplished in several biomedical applications, such as signal compressions, and pattern recognitions, by TFA-based signal processing methodologies. The mathematical backgrounds of several commonly used linear and quadratic TFAs are described. We used a simulated TEOAE signal to testify that the TFAs can efficiently decompose the original signal, and the results of various TFAs are compared and discussed. The specific feature of how different frequency components vary with time, which is similar to the Cochlear organ, can be successfully extracted by the wavelet transform. Because the acquired TEOAE signals are severely contaminated by environmental white noise, we designed a TFA-based active denoising methodology, called wavelet shrinkage, to suppress the embedded white noise during the measurement. The proposed method is more efficient than traditional statistically averaging method and is implemented in the DSP-based system.

並列關鍵字

TEOAE ； Wavelet Transform ； TFA ； Denoising