本論文提出一個有效的心電圖資料壓縮方法，可應用於遠距醫療照護 (Telemedicine)中的心電圖管理系統，來節省儲存空間與降低資料傳輸時間。心電圖訊號壓縮演算法採用轉換編碼(Transform coding)的方式，屬有失真性壓縮 (Lossy Compression)，有別於過去文獻採用第二型離散餘弦轉換(DCT-II)，本論文嘗試以第四型離散餘弦轉換(DCT-IV)為核心，藉由DCT-IV係數的正負號關係與頻譜量化後的特性，以記錄差值的方式代表每筆資料，最後搭配霍夫曼編碼增加壓縮效率。所提出的壓縮演算法使用MIT-BIH 心律不整資料庫的48組心律不整資料作為測試訊號，平均壓縮比(CR)為5.26、失真率(PRD)為0.19，本論文也使用自製的心電讀取電路，量測實際的心電訊號，測試所提出的演算法，結果平均壓縮比(CR)為4.79，失真率(PRD)為0.22。
本論文在實作方面採用UBIKIT-6612嵌入式開發板，整合心電讀取電路，將系統軟硬體移植至Android平台上執行，受測者能夠透過觸控式面板來進行功能操作，並檢視心電圖與心律變異性(HRV)分析結果。

In this thesis, we present an idea that combine an effective electrocardiogram (ECG) data compression algorithm with the telemedicine in order to save storage space and reduce transmission time. Different from literatures, we take type IV discrete cosine transform (DCT-IV) as the kernel function which belongs to the lossy compression. Due to the sign bit of the DCT-IV coefficients have regular characteristic and the correlation of the DCT-IV spectrum values are closed to each other after quantization, we then use differential technique reducing the dynamic range and increasing the probability in some numeric. After the differential processing, Huffman coding is chosen to increase the compression rate. We also take MIT-BIH Arrhythmia Database as the input pattern which contains 48 two-lead recordings, the result show that compress ratio (CR) is 5.26 and the Percent Root mean square Difference (PRD) is 0.19. In addition, we measure the ECG signal from our ECG read-out circuit as the test pattern, the result show that CR is 4.79 and the PRD is 0.22.
Furthermore, we integrate ECG read-out circuit and implement algorithm on the embedded development board, porting on the Android platform. Users can operate the user interface (UI) to view ECG signal and heart rate variability (HRV) analysis.

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