以二維轉換以及連續近似值編碼進行失真到無失真的多導程心電圖壓縮

Lossy-to-Lossless Compression for Multichannel ECG Using Two Dimensional Transform and Successive Approximation Coding

吳倉志(Tsang-Chih Wu)

指導教授 ： 繆紹綱

中原大學/工學院/電子工程研究所/碩士(2005年)

https://doi.org/10.6840/cycu200500423

摘要

傳統的心電圖(Electrocardiography, ECG)共有十二個導程，包括心電訊號的額平面(frontal plane)六個導程的投影和在橫平面(horizontal plane)六個導程的投影。而在橫平面的六個導程(V1到V6)中，彼此的相關性相當的高。以往大都是對於單一導程ECG訊號提出各式各樣的失真與無失真的壓縮方法，而針對多導程直接處理的方法則相當的少。
對於多導程ECG訊號，以單一導程的編碼基礎去處理相當沒效率，因為此方法並沒好好運用到導程與導程間的相關性，因此我們提出一個新的方法，利用2D整數小波轉換(IWT)與集合分割階層樹狀法(SPIHT)，搭配連續近似值編碼(SAC)，以達到對多導程ECG訊號的壓縮。此2D轉換將可以利用到各導程間的相關性，經過轉換會產生小波係數方塊，此方塊的傳送與否更會經由方塊重要性辨識器去決定是否傳送。IWT確保真正的無失真壓縮，而SPIHT使我們可以有效率的運用於失真到無失真的壓縮。
本論文以CSE 多導程資料中的八個導程為實驗資料，實驗結果顯示，與單導程壓縮法做比較，本研究方法不管對於失真或無失真壓縮都優於單導程壓縮方法。在失真壓縮方面，當壓縮倍率在12.34時，以單導程方法所得的平均PRD為7.56%，以本研究所提方法則為3.21%，故明顯優於單導程壓縮法；在無失真壓縮方面，使用單導程方法由原本的6000 bits/s降為平均3007.8 bits/s，使用本研究所提方法則降為2876 bits/s。

關鍵字

多導程心電圖 ； 小波轉換 ； 心電圖壓縮 ； SPIHT

並列摘要

The traditional Electrocardiogram (ECG) has twelve leads, including six frontal plane leads and six horizontal plane leads, and the six frontal plane leads (from V1 to V6) correlate closely with each other. In the past, lossy and lossless compression methods are often proposed for single channel ECG signals, and compression methods that are directly applied to multichannel ECG signals are rarely seen.
For multichannel ECG signals, encoding ECG signals on a channel by channel basis is not efficient because the correlation across channels is not exploited. We propose a new ECG compression approach using a two-dimensional (2D) integer wavelet transform (IWT) and the set partitioning in hierarchical trees (SPIHT) along with successive approximation coding (SAC). The 2D-transform exploits both the in-channel and the inter-channel correlations. The transform results in wavelet coefficient blocks. Whether a block will be sent is determined by a block significance classifier. The IWT guarantees a true lossless compression, and the SPIHT allows efficient coding and progressive transition from lossy to lossless compression.
The ECG data of 8 leads in the CSE Database are tested. The experimental results show that the proposed approach performs better than its single-channel version in both lossy and lossless cases. For lossy compression, when compression ratio is 12.34, the average PRD is 7.56% using the single channel and 3.21% using the proposed approach. The performance of the proposed approach is significantly better than that of the single channel version. For lossless compression, the average compressed data rate per channel is reduced from 6000 bits/s to 3007.8 bits/s using the single channel approach and to 2876 bits/s using the proposed approach.

並列關鍵字

wavelet transform ； multichannel ECG ； ECG compression ； SPIHT

參考文獻

[1] S. Jalaleddine, C. Hutchens, R. Strattan, and W. Coberly, “ECG data compression techniques—A unified approach,” IEEE Trans. Biomed. Eng., vol. 37, no. 4, pp. 329-343, 1990.

[2] J. Cardenas-Barrera and J. Lorenzo-Ginori, “Mean-shape vector quantization for ECG signal compression,” IEEE Trans. Biomed. Eng., vol. 46, no. 1, pp. 62-70, 1999.

[3] S. G. Miaou, H. L. Yen, and C. L. Lin, “Wavelet-based ECG compression using dynamic vector quantization with tree codevectors in single codebook,” IEEE Trans. Biomed. Eng., vol. 49, no. 7, pp. 671-680, 2002.

[4] A. Koski, “Lossless ECG encoding,” Computer Methods and Programs in Biomedicine, vol. 52, pp. 23-33, 1997.

[5] C. D. Giurcăneanu, I. Tăbuş, and Ş. Mereuţă, “Using contexts and R-R estimation in lossless ECG compression,” Computer Methods and Programs in Biomedicine, vol. 67, pp.177-186, 2002.