臺灣博碩士論文加值系統

本篇論文使用了以稀疏正規型式 (sparse normal-form) 轉換將任何給定的狀態空間轉換為稀疏正規型式實現(realization)來達到高效率計算的目的，並藉由轉換後矩陣同時維持 normal-form 的特性而確保了系統在有限精準度實現下的強健性。此外，本論文使用了無限脈衝響應帶拒濾波器群 (filter bank) 來偵測心電圖當中的多重雜訊，並依據該濾波器群所設計出的演算法撰寫Matlab程式用以偵測多重頻段雜訊，並有效加以濾除。

In this Thesis, we use a sparse normal-form transformation matrix to transfer any original given realization to the sparse normal-form one. Such a realization is simulta-neously with high computational efficiency as well as strong robustness under finite precision implementations. In addition, we utilize the IIR filter bank and the developed algorithm to detect multiple noises in an ECG signal. Based on MATLAB program, the effectiveness of the algorithm is verified.

摘要 i
Abstract ii
目錄 iii
圖目錄 v
表目錄 vii
第一章緒論 1
1.1 研究背景 1
1.2 研究動機 4
1.3 研究目的 4
第二章 文獻探討 5
2.1 心電圖 5
2.1.1 歷史 5
2.1.2 原理 7
2.1.3 波形與間期 8
2.2 數位濾波器 10
2.2.1 濾波器原理 10
2.2.2 IIR數位濾波器 11
2.2.3 FIR數位濾波器 11
2.2.4 濾波器形式 12
第三章 研究方法 14
3.1 有限精準度濾波器已發展之相關成果 15
3.2 稀疏正規型式 (sparse normal-form) IIR數位濾波器設計 19
3.3 針對迷你ECG以IIR濾波器群(filter bank)為基礎的全新濾波器架構設計 23
第四章 數值範例探討 25
第五章 結論 44
參考文獻 45
附錄-程式碼 52
濾波器群參數 59


圖 1.1中華民國2012至2060年各年齡層人口比例推估圖(資料來源：經建會) 1
圖 2.1埃因托芬的心電圖描記裝置[29] 6
圖 2.2一秒時長的心電圖紙[29] 8
圖 2.3正常心電圖圖解[29] 9
圖 3.1採用SPARSE NORMAL-FORM實現的數位濾波器於16位元至8位元定點數的頻率響應及其極限環測試 22
圖 3.2針對迷你心電圖訊號雜訊處理的濾波器架構圖 23
圖 3.3經由圖 3.2計算後選出SNR較佳的候選者以CASCADE方式進行濾波 23
圖 4.1初始的心電圖訊號 26
圖 4.2加入雜訊後的心電圖訊號 28
圖 4.3 0.08~78.8HZ的帶通濾波器 29
圖 4.4 0~10HZ低通濾波器 30
圖 4.5心電圖的參考訊號 33
圖 4.6帶通濾波器群 35
圖 4.7局部放大後的帶拒濾波器群 35
圖 4.8選取後的濾波器 40
圖 4.9經過濾波後的心電圖訊號 42
圖 4.10放大後的初始心電訊號 43
圖 4.11放大後的經過濾波後的心電訊號 43

表 2.1心電圖主要的波形與間期[29] 9
表 4.1 0.08~78.8HZ帶通濾波器的參數 29
表 4.2 0~10HZ低通濾波器的參數 30
表 4.3參考訊號及濾波器群的SNR 37

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