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研究生:林延興
研究生(外文):Yen-Hsing, Lin
論文名稱:基於Lagrange多項式與HHT之光體積變化描記訊號心率估算技術
論文名稱(外文):A Lagrange Polynomial and Hilbert-Huang Transform-based Technology for Pulse Rate Estimation with Fingertip Photoplethymography
指導教授:高立人高立人引用關係陳仲萍陳仲萍引用關係
指導教授(外文):Lih-Jen, KauChung-Ping, Chen
口試委員:張正春房同經高立人陳仲萍
口試日期:2016-07-26
學位類別:碩士
校院名稱:國立臺北科技大學
系所名稱:電子工程系研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
畢業學年度:104
語文別:中文
中文關鍵詞:光體積變化描記圖、拉格朗日插值法、希爾伯特-黃轉換、經驗模態分解
外文關鍵詞:PhotoplethysmographyLagrange polynomialHilbert-Huang TransformEmpirical Mode Decomposition.
相關次數:
  • 被引用被引用:1
  • 點閱點閱:180
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本論文旨在探討如何在有雜訊影響下的光體積變化描記圖(Photoplethysmography, PPG)訊號,獲取可信的生理特徵。為了達成這個目的,論文中利用拉格朗日插值法實現一波峰落點預測器,用以預判同心搏生理特徵之PPG訊號波峰位置。當動作雜訊發生時,會以波峰落點預測器的預測值輔以希爾伯特-黃轉換(Hilbert-Huang Transform, HHT)的結果,補償預測器的預測值。
論文中交叉比對了提出演算法之估算心率及Capnobse資料庫提供之心電圖(Electrocardiography, ECG)訊號心率。其中14個含雜訊PPG訊號之皮爾森相關係數r為0.9962,係高相關性。36個可供比對之資料集的比對結果,方均根誤差均在3個BPM以內。以波峰偵測的面向來看,與文獻相比,兩者的陽性檢測率非常相近,只相差0.02個百分點,但就敏感度而論,本論文提出之演算法敏感度更高。就結果而言,提出之演算法,在較高敏感度的情況下,波峰偵測的結果,仍然有99.65%的陽性檢測率。透過拉格朗日插值法實現之波峰落點預測器,輔以希爾伯特-黃轉換為基礎提出之演算法,能有效的在含有動作雜訊的PPG訊號,找出可參考之波峰落點,進而估算出可信的心率。
This study explores a method to obtain reliable physical characteristics under the PPG signal interfered by noise. A peak locate predictor is implemented by Lagrange polynomial. The predictor predicts the possible peak location of PPG signal. Generally, the peak of PPG signal is considered to be as heartbeat appeared. When the motion artifact is detected, Hilbert-Huang Transform (HHT) is used for remedying the predict value.
The heart rate estimated by proposed algorithm is compared with the heart rate estimate from electrocardiography (ECG) which provided by Capnobase database. The result of comparison, the Pearson correlation coefficient of fourteen subjects which PPG signal is interfered by artifact is 0.9962, it is highly correlated. The root mean square of all thirty-six cases is in 3 BPM. On the other hand, the performance of peak detected compare with the literature, the difference of positive predictive value is 0.02% lower but proposed algorithm get higher sensitivity 99.9%. As a result, proposed algorithm still gets 99.65% positive predictive value. By using Lagrange polynomial implement a peak locate predictor and remedying the predict value by HHT, providing reliable estimated heart rate under PPG signal containing noise.
摘要 i
ABSTRACT iii
誌謝 v
目錄 vi
表目錄 viii
圖目錄 ix
第一章 緒論 1
1.1 引言 1
1.2 研究動機 2
1.3 文獻回顧 3
1.4 論文架構 6
第二章 研究背景及原理 7
2.1 Capnobase Database 簡介 7
2.2 心電圖簡介 9
2.3 光體積變化描記圖概述 12
2.3.1 光體積變化描記圖原理 12
2.3.2 光體積變化描記圖波形 15
2.3.3 動作雜訊干擾 17
第三章 系統架構與實驗方法 18
3.1 發現 18
3.2 分析 18
3.2.1 光體積變化描記圖的連續性 18
3.2.2 光體積變化描記圖的相似性 19
3.3 演算法流程與實現 21
3.3.1 演算法流程簡介 21
3.3.2經驗模態分解演算流程 22
3.3.3 本質分量與瞬時頻率 27
3.3.4 分析經驗模態分解結果 29
3.3.5 波峰偵測 32
3.3.6 波峰預測與預測補償 33
第四章 結果與討論 39
4.1 實驗環境設置 39
4.2 效能評估方式 40
4.3 實驗結果與比較 40
第五章 結論與未來展望 48
5.1 結論 48
5.2 未來展望 49
參考文獻 50
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