High efficient ECG compression based on reversible round-off non-recursive 1-D discrete periodized wavelet transform

A Speed- and Power-Efficient SPIHT Design for Wearable Quality-On-Demand ECG Applications

In this paper, a speed and power-efficient set partitioning in hierarchical trees (SPIHT) design is introduced for one-dimensional (1-D) wavelet-based electrocardiography (ECG) compression systems with quality guarantee. To achieve real-time and low-power design objectives toward wearable quality-on-demand (QoD) ECG applications, we first propose a coding-time- and computation-efficient SPIHT algorithm using various types of coding status register files to overcome the disadvantages of low coding speeds and complicated hardware architectures characterizing prior SPIHT algorithms resulting from the necessity of dynamic computation and arrangement in the sorting and refinement processing phase. Second, a highly pipelined and power-efficient very large scale integration (VLSI) architecture is developed to implement a high-performance and low-power SPIHT design based on the proposed algorithm. The final simulation results demonstrate that our proposed algorithm can speed up the average coding time 1.52 to 2.74 times compared to prior work with an identical compression ratio for an 11-level $1024\times 1\,1-{\rm{D}}$ discrete wavelet transform at diverse target percentage root-mean-square differences (PRDT) on various MIT-BIH arrhythmia datasets. Applied to wearable wavelet-based QoD ECG applications, our proposed VLSI architecture attains a working frequency of 740 MHz and consumes an average of $\text{23}\ \mu {\text{W}}$ of power with Taiwan Semiconductor Manufacturing Company 90-nm CMOS technology, which shows the effectiveness of speed and power over the state-of-the-art designs.

A combined application of lossless and lossy compression in ECG processing and transmission via GSM-based SMS

This paper presents a software-based scheme for reliable and robust Electrocardiogram (ECG) data compression and its efficient transmission using Second Generation (2G) Global System for Mobile Communication (GSM) based Short Message Service (SMS). To achieve a firm lossless compression in high standard deviating QRS complex regions and an acceptable lossy compression in the rest of the signal, two different algorithms have been used. The combined compression module is such that it outputs only American Standard Code for Information Interchange (ASCII) characters and, hence, SMS service is found to be most suitable for transmitting the compressed signal. At the receiving end, the ECG signal is reconstructed using just the reverse algorithm. The module has been tested to all the 12 leads of different types of ECG signals (healthy and abnormal) collected from the PTB Diagnostic ECG Database. The compression algorithm achieves an average compression ratio of ∼22.51, without any major alteration of clinical morphology.

A linear quality control design for high efficient wavelet-based ECG data compression

In ECG data compression, maintaining reconstructed signal with desired quality is crucial for clinical application. In this paper, a linear quality control design based on the reversible round-off non-recursive discrete periodized wavelet transform (RRO-NRDPWT) is proposed for high efficient ECG data compression. With the advantages of error propagation resistance and octave coefficient normalization, RRO-NRDPWT enables the non-linear quantization control to obtain an approximately linear distortion by using a single control variable. Based on the linear programming, a linear quantization scale prediction model is presented for the quality control of reconstructed ECG signal. Following the use of the MIT-BIH arrhythmia database, the experimental results show that the proposed system, with lower computational complexity, can obtain much better quality control performance than that of other wavelet-based systems.