強健性心電信號壓縮演算法之研究

Abstract

因應高齡化社會的未來趨勢，遠距醫療與居家健康照護已經成為先進國家重點發展的新興服務產業。本論文旨在發展一高效能的心電信號壓縮演算法，以期長時間監測心臟機能的異常徵兆而防患於未然。演算法的設計需兼顧即時製作與強健性能，前者強調簡化運算得以快速實現，後者則要求訊源與量測雜訊能分離處理。第一項研究課題著重於理想傳輸環境下心電訊號壓縮演算法的設計。一維壓縮演算法是採用增益-形狀碼本結構的多層級向量量化機制，另一種是基於國際影像壓縮標準JPEG2000的二維壓縮演算法。第二項課題旨在探討能有效對抗環境雜訊干擾的信號除噪技術，其關鍵是參考希伯特-黃轉換理論而設計一兼顧時域及頻域非穩態特性的信號分析技術。針對MIT-BIH心電圖資料庫進行的系統模擬結果顯示，新的方法適用於行動心臟照護系統的未來應用。

The volume of ECG data produced by monitoring systems can be quite large, and data compression is needed for efficient transmission over mobile networks. We first propose a new method based on the multiple stage vector quantization in conjunction with gain-shape codebooks. The compression of ECG signals using JPEG2000 is also investigated. The good time-frequency localization properties of wavelets make them especially suitable for ECG compression applications. Also proposed is a method of ECG signal denoising based on Hilbert-Huang transform. This method uses empirical mode decomposition to decompose the signal into several intrinsic mode functions (IMFs) and then the noisy IMFs are removed by using soft-threshold method. Experiments using the MIT-BIH arrhythmia database illustrate that the proposed approach has improved the performance at a high compression ratio.