基於經驗模態分解法與零相位延遲濾波器之心電圖雜訊濾除法則

Abstract

心電圖(ECG)是用來記錄病患在時間軸上，心臟的電壓變化。然而，在取得心電訊號時，訊號常會被以下三種雜訊破壞：基準線飄移、市電干擾與肌肉波干擾。為了讓醫療人員能確切的診斷出心臟疾病，因此必須將這些雜訊的影響給降低。 近數十年來，各種濾除雜訊的方法不斷地被學者們所提出。而本研究基於經驗模態分解法(Empirical mode decomposition, EMD)與零相位延遲濾波器(Zero-phase filter)，提出兩種新的方法濾除這些雜訊。第一種濾波方式，以EMD濾波器濾除基準線飄移；接著將介於兩個QRS複合波之間的訊號，透過低通的零相位延遲濾波器濾除高頻雜訊。第二種濾波方式，根據Weng提出的方法，在處理基準線飄移的部份，改以低通的零相位延遲濾波器對原始訊號濾波，並紀錄基準線飄移的成分；當原始訊號減去基準線飄移的成分後，再經由結合杜克窗口的EMD濾波器濾除高頻雜訊。 本研究提出的方法，其效能透過測試訊號來評估。測試訊號是由生理訊號產生器(PS-2110)先產生出心電訊號，再加入人為的虛擬雜訊。此外，本研究也使用MIT/BIH心律不整資料庫中的訊號來展示本研究方法的效能。實驗結果證實，本研究所提出的方法可有效的將各種心電雜訊濾除。

Electrocardiogram (ECG) is the recording of the heart’s electrical potential versus time. These signals are often corrupted by three types of noise including baseline wander (BW) noise, power line interference and electromyographic (EMG) interference during the signal acquisition stage. These noise need to be attenuated in order to obtain a clean ECG signal for accurate diagnosis of heart condition. In the past decades, several methods have been proposed for the removal of the noise. In this dissertation, two new methods based on empirical mode decomposition (EMD) and zero-phase filter were proposed to remove the aforementioned artifacts. For the first proposed filtering algorithm, the baseline wandering interference is removed by EMD filter and then the power line interference between two consecutive QRS complex is removed by a low pass zero-phase butterworth filter. The second proposed filtering algorithm based on Weng’s algorithm estimates the baseline wandering noise by passing the original signal through a low pass zero-phase filter. The estimating baseline wandering noise is subtracted from the original signal and then the high frequency interference is removed from the signal by using the EMD filter with a Turkey window. The performance of the proposed algorithms is evaluated on the data sets which are generated from a physical ECG signal generator (PS-2110) with an artificial noise. Moreover, MITBIH database are also used to demonstrate the efficiency of the proposed filtering algorithms. Experimental results indicate that the interferences of ECG can be removed effectively by the proposed algorithms.