Dissertation
Dissertation > Industrial Technology > Radio electronics, telecommunications technology > Communicate > Communication theory > Signal processing

TCQ based with a cut-off area of the ECG signal compression

Author JiangZuo
Tutor ChenJianHua
School Yunnan University
Course Biomedical Engineering
Keywords Discrete Wavelet Transform With the cut-off area TCQ Context model ECG signal compression
CLC TN911.7
Type Master's thesis
Year 2010
Downloads 21
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Heart disease is an important topic in clinical medicine , the ECG (electrocardiogram, ECG) has been an important basis for the diagnosis of heart disease . With the continuous development of modern medicine , the hospital on the growing number of ECG data storage , processing, transmission , put forward higher requirements. Therefore, efficient ECG compression has the very important practical significance . This paper presents an effective method for ECG signal compression . The method is divided into three main parts : the wavelet transform , quantization and coding . For the first part of the article describes the theory of the wavelet transform , and 5 layer suitable for ECG signal discrete wavelet transform is chosen for the characteristics of the ECG signal . Quantitative section , one with a cut - off area Trellis coded quantization (dead-zone trellis coded quantizer, DZTCQ) method , and applied to the quantification of the ECG signal compression . Trellis coded quantization (trellis coded quantizer, TCQ) is a convolution coding , signal space expansion signals between the Euclidean distance and codebook by quantitative methods . DZTCQ for ECG signal compression based on wavelet transform features, and improved on the basis of the TCQ get a higher quantization gain quantitative method . The article also determined by experiments of the important parameters in the the threshold quantization interval between DZTCQ in , so that the quantization effect is further improved . Quantized quantization coefficient contains too many symbolic and not conducive to the further compression coding part of this article will be broken down into four small character symbol stream , and four small character symbol stream model of Context , and then combined with the adaptive arithmetic coding its end encoding . ECG data of this experiment were from the MIT-BIH arrhythmia database , experiments show that the ECG signal compression method based on the tape cutoff area TCQ also saved at the same time to obtain a higher compression ratio , the better signal quality .

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