臺灣博碩士論文加值系統

本論文提出一個具有心跳檢測與疾病辨識功能的即時心電訊號處理器。此系統整合降頻濾波器以及心電訊號處理器，可即時對心電圖進行分析，並可長時間進行監控及記錄。本系統之降頻濾波器，降頻率為128，採用多級串接的方式實現節省功耗及硬體面積；本系統的辨識方法乃以小波轉換為基礎，在心跳檢測方面，訂定檢測區間，比較各區間內最大值，找出心跳出現時間；在疾病辨識方面，以醫師意見為基礎，產生相對應的病症參數，並經由醫師確認使用結果，如此可獲醫師信任，且藉由此系統協助醫師診斷，減輕醫師負擔。本系統之辨識方法經由MIT-BIH心律不整資料庫驗證，在預設參數下，心跳檢測以及疾病辨識的精準度皆可達到90%以上。
本系統已使用TSMC 0.18μm 製程實現。在操作電壓1.8V的情形下，此晶片功耗為0.77mW，降頻濾波器輸出有效位元數為12位元，在心跳檢測可達到90%以上的正確率；而疾病辨識方面，在不修飾疾病辨識樣本的前提下，可達到94%的正確率。

An ECG signal processor with real-time beat detection and beat classification is proposed. This system consists of a decimation filter and an ECG signal processor, which can analyze the incoming ECG in real time and provide a long term monitor and record. The decimation filter of the system with a decimation rate of 128 is implemented with multi-stages to optimize the power consumption and area. The algorithm of the system is based on the wavelet transform. In the beat detection part, the system first defines a detection region, and then compares the local maximum in each region to find the time of a heartbeat appearing. In the beat classification part, the system can refer to doctors’ options to generate the parameters of the classification, and doctors check if the symptoms meet their diagnoses, so that the system can win doctors’ confidence and reduce the loading in the clinical diagnoses. The algorithm of the system which is verified with data from MIT-BIH Arrhythmia Database can definitely achieve an accuracy of 90% or more.
The proposed system is implemented in TSMC 0.18 μm CMOS technology. The operation frequency is 1 MHz and the supply voltage is 1.8 V. And the total power consumption of proposed system is 0.77 mW. The resolution of the decimation filter is 12 bits. The accuracy of beat detection can achieve over 90%.In the beat classification part, the accuracy is 94% with non-tuning symptom pattern.

中文摘要 I
ABSTRACT II
目錄 III
圖目錄 V
表目錄 VIII
第一章 緒論 1
1.1 研究背景 1
1.2 相關研究與文獻 3
1.3 研究動機與目的 3
1.4 章節規劃 4
第二章 心電圖與MIT-BIH心律不整資料庫簡介 5
2.1 心電圖原理 5
2.2 MIT-BIH心律不整資料庫 7
2.1.2 病症分析 8
2.2.2 特殊波形分析 10
第三章 降頻濾波器介紹與設計 13
3.1 有限脈衝響應濾波器 13
3.2 無限脈衝響應濾波器 14
3.3 濾波器規格介紹 15
3.1.3 四級降頻濾波器設計 16
3.3.3 IIR濾波器係數設計 18
3.4 降頻濾波器實現 18
3.1.4 CIC濾波器實現 19
3.2.4 FIR濾波器實現 20
3.3.4 IIR濾波器實現 21
3.4.4 模擬結果 24
第四章 訊號處理器介紹與設計 26
4.1 小波轉換介紹 26
4.1.1 小波理論 26
4.1.2 離散小波轉換 27
4.1.3 Haar小波轉換 28
4.2 辨識波形演算法介紹 31
4.2.1 系統使用情境介紹 31
4.2.2 心跳檢測演算法介紹 33
4.2.3 辨識波形演算法介紹 36
4.3 心電訊號處理器實現 38
4.3.1 系統架構介紹 38
4.3.2 系統模擬結果 50
第五章 電路設計與實現 57
5.1 數位電路設計流程 57
5.2 FPGA驗證結果 58
5.1.2 Altera Cyclone IV開發板介紹 58
5.2.2 驗證結果 59
5.3 全晶片模擬及佈局 62
第六章 量測考量與結果 68
6.1 ADVANTEST V93000 PS1600介紹 68
6.2 量測結果 70
6.3 文獻比較 76
第七章 結論與未來展望 77
7.1 結論 77
7.2 未來展望 77
參考文獻 79

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