臺灣博碩士論文加值系統

傳統聽診器自1816年於醫學應用已使用至今，它是用來協助醫師診斷病患心肺音的工具之一。因為，傳統聽診器無法儲存受測者的訊號、醫師本身聽覺能力範圍限制、不便於攜帶、與無法長期監控功能等限制條件缺點。基於藍芽Android Smartphone系統，本研究除了改良有線傳統聽診器的缺點外，還結合三軸加速器與無線藍芽裝置。因此，我們建構一套遠距監控數位紀錄電子聽診器系統。更進一步，我們應用整合相關性、傅立葉轉換、與正規密度疊加分布等演算法開發一套法則用來提高所記錄的心音品質。三軸加速器所感測到的心音訊號借由藍芽手機傳送與儲存於伺服器中。然後，我們所設計系統是應用已建構完成的心音資料庫與透過相關疾病的統計分析完成心音診斷。因此，本系統可以提供專業醫師做心音診療判斷的精確參考。使用者也可以應用Android Smartphone進行自我心音診療判斷，發現心音異常時可以提早就醫。從我們實驗結果，本系統測量之數據與3M藍牙電子聽診器Littmann 3200型比較，兩者誤差約2.7%。因此，我們系統的可用性已達到相當的程度。

The traditional stethoscope on the medical applications since 1816 has been used so far, it is used to assist Doctors in the diagnosis of patients with heart and lung sounds tools. There are some limitations, without saving the patients signal function, Physicians themselves hearing range limits, not easy to carry, and without long-term monitoring function, in the traditional stethoscope. Based on the Bluetooth Android smartphone system, our design of a tele-monitoring system of digital stethoscope not only owns to improve the disadvantages of traditional wired stethoscope but also to combine 3D accelerator with wireless Bluetooth devices. Furthermore, we employ the correlated application, Fourier transform, and the normalization distribution of the density overlay algorithms to develop a set of rules for improving the recorded quality of heart sounds. The detected heart sound signals by the 3D accelerator can be sent by the Bluetooth-Smartphone and then stored in server. Then, our design system applies the well completed construction database of the completed phonocardiogram and its corresponding disease diagnosis with the statistical analysis to complete the diagnosis of heart sounds. Hence, our system can provide the accurate reference phonocardiogram for physician to diagnose. Users can also use the Android Smartphone for self-diagnosis of heart sound, when abnormal heart sounds can be found early medical treatment. From the experimental results, compared with Littmann 3200, the 3M Bluetooth Electronic Stethoscope model, the error between them is about 2.7%. Hence, the availability of our systems has reached a considerable degree.

摘要 i
Abstract ii
誌謝 iii
目錄 iv
表目錄 vi
圖目錄 vii
第一章 緒論 1
1.1 前言 1
第二章 相關背景知識介紹 4
2.1 文獻探討 4
2.2 心音概論 5
2.2.1 心臟結構 5
2.2.2 心音的產生 6
2.2.3 心音的組成 7
2.2.4 心臟雜音的產生 7
2.2.5 心音的頻率特點 8
2.2.6 心音圖概述 9
2.3 心臟雜音 10
2.3.1 主動脈瓣膜狹窄 10
2.3.2 二尖瓣膜狹窄 11
2.2 肺音概論 12
2.4.1 肺音訊號頻率 13
2.4.2 肺音分類 13
2.4.3 正常肺音 14
2.4.4 異常肺音 15
2.5 智慧型手機概論 16
2.5.1 Android架構 16
2.5.2 Android的執行環境 17
2.5.3 Dalvik虛擬機器 17
第三章 研究方法 19
3.1 系統架構 19
3.1.1 類比聽診器 19
3.1.2 三軸加速器 20
3.1.3 微控制器 21
3.1.4 行動裝置 22
3.2 心音有效區間擷取演算法 24
3.3 心音輔助診斷 28
3.4 語音辨識 31
3.4.1 語音辨識流程 31
3.4.2 產生模型 31
3.4.3 訓練模型 33
3.4.4 維特比演算法 33
3.5 系統實作 34
3.5.1 有線數位聽診器系統實作 34
3.5.2 無線數位聽診器系統實作 36
第四章 實驗 38
4.1 實驗一 38
4.2 實驗二 41
4.3 實驗三 43
4.4 實驗四 44
第五章 結論 45
5.1 結論 45
5.2 未來發展 45
參考文獻 46
附錄A 中英文對照表 50
附錄B作者簡介 53

表1-1國人十大死亡疾病 1
表2.1正常呼吸音的分類 15
表2.2異常肺音與可能肺部疾病之關連 15
表2.3異常肺音的特性概述 16
表3.1心跳數與心律之表現 28
表3.2各種心音之特徵與功率表現 30
表4.1本研究裝置與3M藍牙電子聽診器比較數據表 41
表4.2實驗二數據表 42
表4.3本研究裝置與3M藍牙電子聽診器比較心跳數據表 43
表4.4心音異常分析數據表診器比較心跳數據表 44

圖1.1傳統類比式聽診器架構 2
圖2.1人體心臟示意圖 6
圖2.2心臟雜音之波形圖 8
圖2.3心臟循環圖 8
圖2.4心音、心電與心臟壓力之比較圖 9
圖2.5主動脈瓣膜狹窄之心音圖 11
圖2.6二尖瓣膜狹窄之心音圖 12
圖2.7肺音運作原理 12
圖2.8肺音分類 14
圖2.9Android System Architecture Diagram 18
圖3.1精巧型數位紀錄電子聽診儀系統架構圖 19
圖3.2 Spirit的CK-A603CP單面類比聽診器 20
圖3.3Freescale MMA7260QT規格書 21
圖3.4MSP430F1611內部架構 22
圖3.5MSP430F1611實體模板 22
圖3.6Transformer Prime TF201重點功能 23
圖3.7Transformer Prime TF201實體圖 24
圖3.8心音訊號之振幅機率分布 24
圖3.9區間內心音位置與其振幅機率分佈之關係 27
圖3.10週期相關性與雜訊之關係 27
圖3.11心跳時序 28
圖3.12正常心音 29
圖3.13典型主動脈瓣膜狹窄 29
圖3.14典型二尖瓣膜狹窄 30
圖3.15語音辨識流程 31
圖3.16前置處理及求特徵值 32
圖3.17維特比演算法 34
圖3.18麥克風型的聽診器 35
圖3.19有線數位聽診器製作示意圖 35
圖3.20有線數位聽診器 35
圖3.21三軸加速器實體圖 36
圖3.22前置放大器 36
圖3.23低通濾波器 37
圖3.24無線數位聽診器 37
圖4.1本研究裝置與3M藍牙電子聽診器比較 39
圖4.2語音辨識結果 42

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