An Ultra Low-Energy VLSI Approximate Discrete Haar Wavelet Transform for ECG Data Compression

Abstract

This work proposes a highly efficient compression scheme utilizing a VLSI-based Discrete Haar Wavelet Transform (DHWT) architecture. This scheme aims to facilitate improved transmission and storage, particularly in resource-constrained environments for electrocardiogram (ECG) signal processing. The work presents pruned, approximated, and truncated DHWT architectures (denoted as PDHWT, AxDHWT, and TDHWT, respectively) up to level 5, targeting ultra-high energy efficiency in ECG data compression. Among the developed solutions, the most energy-efficient and areaoptimized approach employs all three compression techniques simultaneously (pruning, approximation, and truncation). In this combined approach, the PDHWT technique achieves significant energy savings by eliminating redundant components. The AxDHWT approach enhances performance by removing the most computationally expensive elements. Finally, TDHWT reduces the number of input bits, leading to a lower-complexity architecture. This combined solution achieves a compression ratio of 0.03125 ( 132 ) and a percent root difference (PRD) less than 2.08. The VLSI architecture implementation leverages 65 nm CMOS technology with maximum frequency of 1.1 GHz. A key differentiator of this work is the remarkably low energy consumption of 0.6μW, which surpasses all existing ECG signal compression solutions reported in recent literature.