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研究生: 詹益生
Yi-Sheng Chan
論文名稱: 基於攝影機的非接觸式心率量測方法之研究
A Study of Camera Based Non-Contact Heart Rate Measurement
指導教授: 林淵翔
Yuan-Hsiang Lin
口試委員: 周迺寬
none
陳維美
none
林敬舜
none
學位類別: 碩士
Master
系所名稱: 電資學院 - 電子工程系
Department of Electronic and Computer Engineering
論文出版年: 2014
畢業學年度: 102
語文別: 中文
論文頁數: 69
中文關鍵詞: 基於攝影機非接觸式生理訊號量測盲源分離適應性濾波移動雜訊心率量測
外文關鍵詞: Camera Based, Non-Contact Vital Sign Measurement, Blind Source Separation, Adaptive Filter, Motion Artifact, Heart Rate Measurement
相關次數: 點閱:317下載:8
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  • 本論文開發出一套以攝影機為基礎的非接觸式心率量測裝置。並設計實驗針對裝置量測精準度、量測範圍、適應性濾波器成效等進行探討。而在裝置精準度驗證的部分,針對趴姿態與坐姿態時的量測數值進行驗證,發現在趴姿態時裝置精準度為98.74%,而坐姿態時則為98.61%。在裝置量測範圍的實驗當中也發現,感測範圍為36bpm~300bpm。而在適應性濾波器成效探討的部分也發現,可以讓使用者在有較多動態雜訊產生的情形之下亦能還原出生理訊號,有助於訊號雜訊比的提升。


    The thesis developed a camera based non-contact heart rate measurement device. Besides, there is a accuracy and sensoring range verification of our proposed system, and also investigation of the adaptive filter performance for blind source separation. On the device accuracy verifying section, we verified the accuracy on two postures including lying posture and sitting posture, and measured heart rate from these two posture of each subject. And the device accuracy report of lying posture and sitting posture are 98.74% and 98.61% separately. On the other hand, the device sensoring range verifying section, it shows that sensoring range is between 36 bpm to 300 bpm. Furthermore, the adaptive filter has good performance at reducing motion artifact.

    摘要 I Abstract II 誌謝 III 目錄 IV 圖目錄 VI 表目錄 VII 第一章 緒論 1 1.1 動機與目的 1 1.2 文獻探討 4 1.3 相關論文比較 6 1.4 論文架構 7 第二章 研究背景 8 2.1 背景 8 2.2 PPG定義 11 2.3 傳統PPG訊號量測 11 2.4 傳統PPG量測方式 13 2.5 非接觸式PPG量測原理 14 2.6 非接觸式PPG量測方式 14 2.7 移動雜訊 15 2.8 光源雜訊 15 2.9 PPG相關生理參數應用 16 2.10 訊號來源為頸動脈衝導致頭部震動變化 17 2.11 Microsoft Visual Studio C# 應用程式開發環境 18 2.12 Microsoft Life Cam Studio Q2F-00017 19 2.13 OPEN CV 20 2.14 可能遇到的問題 20 第三章 研究方法 21 3.1 介紹 21 3.2 系統架構 22 3.3 心率訊號取得 23 3.4 訊號處理 25 3.4.1 訊號放大 26 3.4.2 雜訊來源 27 3.4.3 濾波器設計 27 3.4.4 有限脈衝響應濾波器(FIR) 28 3.4.5 無限脈衝響應濾波器(IIR) 31 3.4.6 訊號處理各階段輸出成果 34 3.5 適應性濾波器 35 3.6 演算法 40 3.6.1 波峰偵測 41 3.6.2 動態閥值調整 43 3.6.3 波峰範圍預測 44 3.6.4 心率換算方法 45 3.6.5 波峰偵測成果 45 第四章 實驗與結果討論 46 4.1 裝置精準度驗證 46 4.1.1 實驗方法 46 4.1.2 實驗結果 47 4.2 生理訊號源成因探討 48 4.2.1 實驗方法 48 4.2.2 實驗結果 50 4.2.3 結果討論 53 4.3 光源對訊號造成的影響 54 4.3.1 實驗方法 54 4.3.2 實驗結果 56 4.3.3 結果討論 58 4.4 心率量測範圍驗證 59 4.4.1 實驗方法 59 4.4.2 實驗結果 59 4.5 盲源分離成效探討 60 4.5.1 實驗方法 60 4.5.2 實驗結果 60 第五章 結論與未來展望 62 參考文獻 63 附錄一 裝置精準度驗證數據 68 附錄二 心率量測範圍驗證數據 69

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