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標題: | 時域及轉換域上針對不規則週期心電圖之壓縮演算法 Time-Domain and Transform-Domain Compression Algorithms for ECG Signals with Irregular Periods |
作者: | Hsiao-Hsuan Chou 周曉璇 |
指導教授: | 郭德盛(Te-Son Kuo) |
關鍵字: | 心電圖,壓縮,不規則,週期,排序, ECG,compression,irregular,period,sorting, |
出版年 : | 2006 |
學位: | 博士 |
摘要: | 現代的心電圖監視系統產生大量的資料,需要巨大記憶容量,為了有效率地處理、傳輸、及儲存這些資料,文獻上已有許多心電圖壓縮演算法被提出。然而大部份的演算法較適用於規律心電圖,但用在不規則週期心電圖中,壓縮率就沒有規律心電圖那麼好。本文在時域及轉換域各提出一種較佳壓縮法,可將不規則週期心電圖壓縮得比文獻上的其他同類型方法更好。
在時域壓縮方面,本文提出一種新穎且快速的非均勻取樣演算法,應用於心電圖的壓縮,比之前文獻上的其他時域壓縮演算法壓誤差更小。它計算複雜度低,可達到即時取樣的要求,而且,即使在不規則的心電圖中,仍能保持穩定的壓縮率及信號品質。本方法首度利用誤差方和 (SSD) 為測試公式,將此公式計算結果限制在某設定值以下,並應用於 MIT-BIH 心電圖資料庫,此資料庫以 11位元解析度及 360 Hz 取樣頻率來儲存心電圖資料。跟本方法一樣利用限制誤差取樣的演算法有 FAN,SAPA,MEA等。一般評估此類取樣演算法的指標有取樣壓縮率 (SCR) 及誤差方均根百分比 (PRD) ,我們的演算法比起上述方法,有更高的壓縮率,更低的誤差,且可保存更佳的心電圖臨床特性。 在轉換域壓縮方面,本文提出一完整程序一步步增加壓縮效能。首先利用心電圖中有心跳週期之內與之間的關連性,選擇一種 QRS 偵測演算法,將每一心跳QRS峰值鑑別出來,平移到平坦區域切分每個心跳。再依週期長短排序,使原雜亂無章的心跳片段變得有秩序。此週期排序步驟,是其他文獻未曾提出的創新,且對不規律心電圖壓縮,效能強大。接著用均值等化或週期等化處理成較平滑的二維矩陣。最後選用先進的靜態影像壓縮器JPEG2000來壓縮,得到良好的結果,即獲得較大壓縮率 (CR) ,較小誤差 (PRD) ,及較小的局部誤差 (MaxErr and StdErr)。此程序針對不規則週期心電圖的壓縮結果與之前文獻相比,突顯出很大的進步。與其他壓縮演算法的步驟合併使用,還能增進其在不規則週期心電圖的壓縮效能。 Because modern Electrocardiogram (ECG) monitoring devices generate vast amounts of data and require huge storage capacity, many ECG compression methods have been proposed to process, transmit, and store the data efficiently. Most of the related papers showed fair ECG compression performances for regular ECG cases. However, their compression performance dropped in irregular ECG waveforms. In fact, the abnormal ECG signals have more clinic significance. In this dissertation, we propose improved time-domain and transform-domain compression algorithms separately for ECG signals with irregular periods. For the time domain, a novel and rapid ECG signal compression algorithm with less error for non-uniform sampling is proposed. It meets the real-time requirements for clinical applications. Moreover, the compression performance is stable even for abnormal ECG signals. A criterion called the Sum Squared Difference (SSD) is first defined as an error test equation. The algorithm using SSD to calculate error tolerance is applied to the records in the MIT-BIH 11-bit resolution database that was based on a 360 Hz sampling rate. It belongs to the threshold-limited algorithm such as the popular Fan algorithm but outperforms the Scan-Along Polygonal Approximation (SAPA), the Fan, and the Maximum Enclosed Area (MEA) algorithms in Sample Compression Ratio (SCR) and the Percent Root mean squared Difference (PRD). In addition, it maintains more clinical features of the ECG signals. For the transform domain, this dissertation presents an effective and efficient algorithm for compressing ECG signals by exploiting their inter- and intra-beat correlations. To better reveal the correlation structure, the ECG signals are converted into a proper 2-D array. This involves a few steps including QRS detection and alignment, period sorting, and length equalization. Of all the steps, period sorting has been first proposed by us as a novel and powerful method to reduce period differences among heartbeats effectively. Then the state-of-the-art JPEG2000 is selected for its high efficiency and flexibility. In this way, the proposed algorithm is shown to outperform existing methods in the literature by simultaneously achieving high Compression Ratio (CR) and low PRD. Furthermore, because the proposed period sorting method rearranges the detected heartbeats into an orderly array that is easier to compress, this algorithm is insensitive to irregular ECG periods. This is a significant improvement over existing 2-D ECG compression methods. This algorithm can be combined with other algorithms or codecs to improve their efficiency. |
URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/34350 |
全文授權: | 有償授權 |
顯示於系所單位: | 電機工程學系 |
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