近年來，心電圖已成為診斷心臟疾病的常見的方法。心電圖紀錄了人每次心跳時間內的電流變化，藉由偵測心電圖中不同的特徵(P 波、QRS複合波與 T 波)可以更快的了解目前身體狀況。小波轉換是在近年來常被利用在訊號分析上，在於小波轉換可以表示為多解析度分析，主要是小波轉換在時域和頻域都是局部的，而標準的傅立葉變換只在頻域上是局部的。小波轉換中常利用全域臨界值來處理訊號上被其外在雜訊所干擾的方法，因此我們利用離散小波轉換中的Symlet5與軟性臨界值來做進一步的分析。

在論文中，利用離散小波轉換來加以分析一個單導聯心電圖系統。起初，我們檢測每一次心跳中的峰值R，藉由找出的峰值R，我們設定的一窗口大小來找出峰值Q與S。接著利用峰值Q與S，我們在不同情況利用不同的方式如過零點方式、最大值與最小值來偵測QRS複合波的起始位置與終點位置。最後，我們利用小波轉換來重建訊號來得以去除高頻與低頻雜訊的干擾，藉由離散小波轉換分層重建訊號，在訊號所處於的頻域帶上，使用可適性的窗口大小分別來檢測P波與T波。而藉由我們找尋到的每一個特徵，我們可能推斷出一些症狀。心臟跳動的速率可以幫助檢測心血管異常問題，如心搏過緩(心跳速率每分鐘小於60下)或是心搏過速(心跳速率每分鐘大於100下)。PR時間長度為評估心房至心室的傳導速度，當間隔時過長也可能代表有房室阻斷的情況。而QTc時間長度為評估整個心室收縮所花費的時間。因此，藉由偵測出這些特徵所在的位置可以更進一步的了解我們心臟整體的狀態。

利用QT 資料庫中的所提供心臟科醫生所註解的波形位置與我們演算法中所找出的位置評比的結果皆有很高的靈敏度。在QRS複合波的檢測我們得到靈敏度皆超過99.94%，而在P波與T波的靈敏度中，分別也高達99.75%與99.7%的比例。

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