Efficient fuzzy‐controlled and hybrid entropy coding strategy lossless ECG encoder VLSI design for wireless body sensor networks

Abstract

An efficient VLSI design of a lossless electrocardiogram (ECG) encoder is proposed for wireless body sensor networks. To save wireless transmission power, a novel lossless encoding algorithm had been created for ECG signal compression. The proposed algorithm consists of a novel adaptive predictor based on fuzzy decision control, and a novel hybrid entropy encoder including both a two-stage Huffman and a Golomb-Rice coding. The VLSI architecture contains only 2.71 K gate counts and its core area is 33 929 μm 2 synthesized by a 0.18 μm CMOS process. Moreover, 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 the MIT-BIH arrhythmia database. Compared with previous low-complexity and high-performance lossless ECG encoder studies, this design has a higher compression rate, lower power consumption and lower hardware cost than other VLSI designs.