A wavelet-based progressive ECG compression using modified SPIHT

被引：4
|
作者：
Rajankar, Supriya O. [1 ]
Bhanushali, Raj K. [1 ]
Talbar, Sanjay N. [2 ]
机构：
[1] Sinhgad Coll Engn, Dept Elect & Telecommun Engn, Pune, Maharashtra, India
[2] Shri Guru Gobind Singhji Coll Engn & Technol, Dept Elect & Telecommun Engn, Nanded, Maharashtra, India
来源：
INTERNATIONAL JOURNAL OF BIOMEDICAL ENGINEERING AND TECHNOLOGY | 2016年 / 22卷 / 03期
关键词：
compression ratio; ECG; electrocardiogram; PRD; percentage root mean difference; RLE; run length encoding; mSPIHT; modified set partitioning in hierarchical trees;
D O I：
10.1504/IJBET.2016.079486
中图分类号：
R318 [生物医学工程];
学科分类号：
0831 ;
摘要：
An Electrocardiogram (ECG) signal contains much vital clinical information. These signals include information on cardiac imperfection. These signals recorded over an extended period result in large file size. Thus, compression is essential. This paper aims to implement compression of ECG signal using wavelet-based progressive coding such as set partitioning in hierarchical trees. Further improvement in the compression ratio is possible with modified run-length encoding. The experimentation performed with the MIT-BIH arrhythmia database shows compression ratio of 16:1 and average mean square difference percentage of 0.58 using bior4.4 wavelet. The coders achieve bit rate control and produce a bitstream that is progressive in quality. The user can trim the bitstream at any point and make the best quality restoration for reduced file size using required values of compression ratio.
引用
收藏
页码：216 / 232
页数：17
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