胎兒的健康情形是每個懷孕婦女及產科醫師最關心的一件事,胎兒心電圖訊號(fetal Electrocardiogram,FECG)是量測胎兒健康情形的一個指標,使用非侵入式的母親體表電位量測方法,用來觀察胎兒心電圖訊號是最合適且簡便的方式。一般情況下,經由腹部電極由母親 腹部擷取的訊號,除了胎兒的訊號外,還包括母親本身的心電圖訊號,及一些外在因素所引起的雜訊。因此,如要獲取單純的胎兒心電圖,就必須先去除這些干擾及雜訊。有鑑於此,本論文利用特徵值分解演算法,在穩定的測量情況下,亦即母親及胎兒之心電圖訊號均是在穩定狀態下,逐一分離出母親心電圖與胎兒心電圖號。 本論文首先將從母體腹部量測到的心電圖訊號做訊號的前置處理,目的是為了濾除在測量胎兒心電圖時,因為母親的呼吸所造成的低頻飄移現象,以及母親心電圖中之T 波與雜訊等,對偵測胎兒心電圖會造成的影響。經此處裡後,可得到訊號特徵波的波形,接著再根據特徵值比例(Singular Value Ratio,SVR)頻譜,分析最佳週期長度以決定訊號的分割長度。分割後的訊號,利用短時距傅立葉轉換(ShortTime Fourier Transform,STFT)得到一個時頻圖矩陣,而後將時頻圖矩陣以特徵值分解法(Singular Value Decomposition,SVD)進行訊號的 解析。並將解析的主要資訊保留,可重建分別代表母親及胎兒心律的訊號區段。 本論文承現出的分析方法突破以往在偵測胎兒心電圖上的困難。但目前僅只獲得初步可行的實驗結果,希望未來藉由訊號擷取方式與實驗控制的改進,能夠更完善的建構一套完整的胎兒心電圖分析系統。
Health of fetal is the most important concern of pregnant women and gynecologist, and fetal ECG (F-ECG) is an index to determine the health of fetal. In general, using non-invent fetal electrocardiogram(FECG) monitoring system to observe fetal ECG is very convenient. However signals obtained from maternal abdomen are contaminated by maternal ECG (M-ECG), and interference from electric device. Therefore, if we want to obtain fetal ECG, we have to remove these non-demand signals. In order to remove the non-demand signals, our proposed method exploits this feature for selective separation of M-ECG and F-ECG components by formulating the problem in the singular value decomposition (SVD) framework. In this paper, in order to obtain QRS wavelets we used filter to remove the interference low-frequency trend component and reduce interference of M-ECG’s T wavelet. Then we used the Singular Value Ratio (SVR) spectrum, developed on the basis of the SVD, to detect the periodic components. SVR spectrum can provide an estimate of the period length of the most dominant periodic component present in any signal. Follow we according to the periodic length obtain a spectrogram matrix. Final we used Short Time Fourier Transform (STFT) and SVD to separate F-ECG.