A Highly Adaptive Lossless ECG Compression ASIC for Wireless Sensors Based on Hybrid Gomlomb Coding

Abstract

This work presents a low-complexity lossless electrocardiogram (ECG) compression ASIC for wireless sensors. Three linear predictors aiming for different signal characteristics are provided for prediction based on a history table that records of the optimum predictors for recent samples. And unlike traditional methods using a unified encoder, the prediction error is encoded by a hybrid Golomb encoder combining Exp-Golomb and Golomb-Rice and can adaptively configure the encoding scheme according to the predictor selection. The novel adaptive prediction and encoding scheme contributes to a compression rate of 2.77 for the MIT-BIH Arrhythmia database. Implemented in 40nm CMOS process, the design takes a small gate count of 1.82K with 37.6nW power consumption under 0.9V supply voltage.