在本論文中，提供一個偵測血液透析病患動靜脈廔管狹窄與否的演算法，統計分析病患資料得到一結論，血流信號的組成包括了一個1~2.5HZ之間的基頻訊號，以及一個頻寬隨血管的阻塞程度而定的載波。而本演算法中，檢測待測訊號是否與脈動有關，困難點在於與脈動有關的低頻成份(1~2.5)HZ以及與代表血流聲的高頻成份(300HZ以上)，其能量大小相差約100db。數位濾波器用來選取待測訊號的特定頻寬成份；根據音頻訊號強度設計門檻值可大致獲得與脈動有關的成分，但是使用樣板演算法可以進一步解決突波雜訊的問題。
我們的演算法判斷結果中，MissFire的機率在5 %以內，但是False Alarm的機率大約25%是需要以後再改進的部份。

In this thesis, we presented a new technique for detecting the arterial venous fistula stenosis for hemodialysis patients. Based on our analysis on patients’ data, we found that their blood flow generates a baseband signal which is between 1 to 2.5Hz over a carrier whose frequency range is highly correlated to the stenois level in the arterial venous fistula.
Although the carrier signal is extremely weak(less than -100dB), comparing to the baseband signal, based on our new findings, we developed an algorithm to detect the frequency range of this carrier and hence can be used in determine the condition of the arterial venous fistula.
Using our new technique, the results have been proved to within 5% of misfire rate. The false alarm rate is about 25%, unfortunately. This leaves room for future improvement, however.

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