Hung King-Chu, Tsai Chin-Feng, Ku Cheng-Tung, Wang Huan-Sheng
Department of Computer and Communication Engineering, National Kaohsiung First University of Science and Technology, Kaohsiung 811, Taiwan.
Comput Methods Programs Biomed. 2009 May;94(2):109-17. doi: 10.1016/j.cmpb.2008.08.007. Epub 2008 Dec 13.
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.
在心电图(ECG)数据压缩中,保持具有所需质量的重建信号对于临床应用至关重要。本文提出了一种基于可逆舍入非递归离散周期小波变换(RRO-NRDPWT)的线性质量控制设计,用于高效的ECG数据压缩。RRO-NRDPWT具有抗误差传播和倍频系数归一化的优点,通过使用单个控制变量,能够实现非线性量化控制以获得近似线性的失真。基于线性规划,提出了一种用于重建ECG信号质量控制的线性量化尺度预测模型。使用麻省理工学院 - 贝斯以色列女执事医疗中心(MIT-BIH)心律失常数据库进行实验,结果表明,所提出的系统具有较低的计算复杂度,与其他基于小波的系统相比,能够获得更好的质量控制性能。