應用於無線身體感測網路之高效能心電圖壓縮器積體電路設計

VLSI Implementation of an Efficient ECG Encoder Design for Wireless Body Sensor Network

羅癸安(Guei-An Luo)

指導教授 ： 陳世綸

中原大學/工學院/電子工程研究所/碩士(2013年)

https://doi.org/10.6840/CYCU.2013.00136

摘要

在此論文中，提出兩種應用於無線身體感測網路之低成本且高效率的無失真心電圖壓縮電路架構。為了減少心電圖傳輸時之資料量，開發了應用於心電圖訊號壓縮之演算法；在這個演算法中，主要包含一個預測器和一個熵編碼器。這兩種無失真心電圖壓縮電路的預測器，主要採用模糊控制理論設計，藉由判斷心電圖之趨勢可適應性地選擇線性預測還是斜率預測。
第一個設計的熵編碼器採用霍夫曼編碼理論。為了改善壓縮率和減少霍夫曼編碼表的硬體成本，兩階段的霍夫曼技術用於實現熵編碼器。兩階段式霍夫曼熵編碼採用0.18μm製成合成，最高可以操作在100MHz。此兩階段式霍夫曼熵編碼搭配模糊控制預測器可以等效2.78K NAND邏輯閘數目且核心面積是34.411μm2。此設計壓縮率整個MIT-BIH心律失常數據資料庫之平均壓縮率為2.53。
第二個設計的熵編碼器採用一個兩階段式霍夫曼熵編碼技術以及一個哥倫布熵編碼技術，稱此為混合式熵編碼器。此混合式熵編碼器搭配配模糊控制預測器可以等效2.71K NAND邏輯閘數目且核心面積為33.929μm2，採用0.18μm製成合成。操作在100MHz下僅消耗了30μW。此設計壓縮率整個MIT-BIH心律失常數據資料庫之平均壓縮率為2.56。

關鍵字

無線身體感測網路 ； 心電圖 ； 超大型積體電路設計 ； 模糊定理

並列摘要

In this study, two VLSI architectures of low-cost and high-performance lossless ECG encoder are proposed for wireless body sensor network applications. To decrease the quantity of the transmission data, the novel lossless compression algorithms had been developed for ECG signal compression. These two both consisted of a predictor and an entropy encoder. The predictor in each design is based on a fuzzy decision technique, in which the prediction strategy can be adaptively selected from the linear and slope predictions according to the trends of the signals.
The first entropy encoder was based on a Huffman coding technique. To improve the performance of the compression rate and reduce hardware cost of the Huffman table, a two-stage Huffman technique was used to implement the entropy encoder. This work was synthesized by a 0.18-μm CMOS process and can be operated at 100 MHz processing rate. It contains 2.78 K gates with whole core area of 34,411 μm2. The data compression rate (CR) reaches an average value of 2.53 for MIT-BIH Arrhythmia Database.
The second entropy encoder was based on a two-stage Huffman technique and a Golomb-Rice coding, which is hybrid encode. This work contains only 2.71 K gate counts and its core area is 33,929 μm2 synthesized by a 0.18 μm CMOS process. This design can be operated at 100 MHz processing rate by consuming only 30 μW. It achieves an average compression rate of 2.56 for MIT-BIH Arrhythmia Database.

並列關鍵字

ECG ； Lossless ； Fuzzy ； and Wireless Body Sensor Network. ； VLSI

參考文獻

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