Huan-Sheng Wang

Wavelet-Based ECG Data Compression System With Linear Quality Control Scheme

Maintaining reconstructed signals at a desired level of quality is crucial for lossy ECG data compression. Wavelet-based approaches using a recursive decomposition process are unsuitable for real-time ECG signal recoding and commonly obtain a nonlinear compression performance with distortion sensitive to quantization error. The sensitive response is caused without compromising the influences of word-length-growth (WLG) effect and unfavorable for the reconstruction quality control of ECG data compression. In this paper, the 1-D reversible round-off nonrecursive discrete periodic wavelet transform is applied to overcome the WLG magnification effect in terms of the mechanisms of error propagation resistance and significant normalization of octave coefficients. The two mechanisms enable the design of a multivariable quantization scheme that can obtain a compression performance with the approximate characteristics of linear distortion. The quantization scheme can be controlled with a single control variable. Based on the linear compression performance, a linear quantization scale prediction model is presented for guaranteeing reconstruction quality. 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 reconstruction quality control than other wavelet-based methods.

A Novel ECG Data Compression Method Based on Nonrecursive Discrete Periodized Wavelet Transform

In this paper, a novel electrocardiogram (ECG) data compression method with full wavelet coefficients is proposed. Full wavelet coefficients involve a mean value in the termination level and the wavelet coefficients of all octaves. This new approach is based on the reversible round-off nonrecursive one-dimensional (1-D) discrete periodized wavelet transform (1-D NRDPWT), which performs overall stages decomposition with minimum register word length and resists truncation error propagation. A nonlinear word length reduction algorithm with high compression ratio (CR) is also developed. This algorithm supplies high and low octave coefficients with small and large decimal quantization scales, respectively. This quantization process can be performed without an extra divider. The two performance parameters, CR and percentage root mean square difference (PRD), are evaluated using the MIT-BIH arrhythmia database. Compared with the SPIHT scheme, the PRD is improved by 14.95% for 4lesCRles12 and 17.6% for 14lesCRles20

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.

A high efficient non-recursive DPWT for extracting the transformed coefficients of coarser resolution levels

For the pattern recognition application, a high efficient 1-D non-recursive DPWT (NRDPWT) based on the segment accumulation algorithm (SAA) and the reversible round-off transformation theorem is presented. The SAA is developed to overcome the filter growth problem and facilitate the hardware implementation with the merit of requiring very small amount of multipliers and adders. The latency needed for the SAA-based 1-D NRDPWT is one system clock cycle for any resolution level. In addition, the reversible round-off NRDPWT is developed for solving the bit growth problem existing in the RPA

Non-recursive Discrete Periodized Wavelet Transform Using Segment Accumulation Algorithm and Reversible Round-Off Approach

Wavelet-based features with simplicity and high efficacy have been used in many pattern recognition (PR) applications. These features are usually generated from the wavelet coefficients of coarse levels (i.e., high octaves) in the discrete periodized wavelet transform (DPWT). In this paper, a new 1-D non-recursive DPWT (NRDPWT) is presented for real-time high octave decomposition. The new 1-D NRDPWT referred to as the 1-D RRO-NRDPWT can overcome the word-length-growth (WLG) effect based on two strategies, resisting error propagation and applying a reversible round-off linear transformation (RROLT) theorem. Finite precision performance analysis is also taken to study the word length suppression efficiency and the feature efficacy in breast lesion classification on ultrasonic images. For the realization of high octave decomposition, a segment accumulation algorithm (SAA) is also presented. The SAA is a new folding technique that can reduce multipliers and adders dramatically without the cost of increasing latency.

A fast quality-on-demand algorithm for wavelet-based electrocardiogram signal compression

In this paper, a fast quality-on-demand (QOD) algorithm for wavelet-based electrocardiogram (ECG) signal compression is proposed. The algorithm based on the 1-D reversible round-off non-recursive discrete periodized wavelet transform (1-D RRO-NRDPWT) and an approximately linear compression performance design to build a linear prediction model for quantization scale refinement. The convergence of quality control is verified to be always held. By using the MIT-BIH arrhythmia database, the experimental results show that the proposed method can effectively improved the computational complexity and convergence speed of quality control.

A High Efficient Quality Control Strategy for Wavelet-Based ECG Data Compression System

Maintaining retrieved signal with desired quality is crucial for ECG data compression. In this paper, a high efficient quality control strategy is proposed for wavelet-based ECG data compression. The strategy is based on a modified non-linear quantization scheme that can obtain a linear distortion behavior with respective to a control variable. The linear distortion characteristic supports the design of a linear control variable prediction algorithm. By using the MIT-BIH arrhythmia database, the experimental results show that the linear control variable prediction method can effectively improve the convergence speed than the previous literatures.

A single-variable non-linear quantization scheme for wavelet-based ECG data compression

In this paper, a non-linear quantization scheme with single control variable is proposed for wavelet-based ECG data compression. This scheme provides high and low octave coefficients with small and large decimal quantization scales, respectively. This method is based on the association of non-recursive 1-D discrete periodized wavelet transform (1-D NRDPWT) and a reversible round-off linear transformation (RROLT) theorem. The use of 1-D NRDPWT and RROLT is to resist error propagation effect and normalize the significance of octave coefficients, respectively. The two error control mechanisms can effectively reduce the searching area of quantization scales in an 11-D grid space. By using the MIT-BIH arrhythmia database, the experimental results show that this new approach can obtain a superior compression performance, particularly in high CR situations.

A Novel ECG Data Compression Based On Reversible Round-Off 1-D NRDPWT

In this paper, a novel ECG data compression method based on the reversible round-off non-recursive 1-D discrete periodized wavelet transform (1-D NRDPWT) is proposed. The reversible round-off 1-D NRDPWT can perform overall stages decomposition with minimum register word length and resist quantization error propagation. A non-linear word length reduction algorithm is developed to have high compression ratio (CR). This algorithm supplies high and low octaves coefficients with small and large decimal quantization scales, respectively. Using the MIT-BIH arrhythmia database, the experimental results show that this novel approach obtains much better compression performance than the SPIHT scheme, especially in high CR situation