.png){kind=icon}
返回
A 2D electrocardiogram data compression method using a sample entropy-based complexity sorting approach
.png){kind=icon}
PRE
AI
DOI：10.1016/j.compeleceng.2016.10.012.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This paper proposes an effectual sample entropy (SampEn) based complexity sorting preprocessing technique for two dimensional electrocardiogram (ECG) data compression. The novelty of the approach lies in its ability to compress the quasi-periodic ECG signal by exploiting the intra and inter-beat correlations. The proposed method comprises the following steps: (1) QRS detection, (2) Length normalization, (3) Dc equalization, (4) SampEn based nonlinear complexity sorting and (5) Compression using JPEG2000 Codec. The performance has been evaluated over 48 records from the MIT-BIH arrhythmia database. The average quality score (QS) measurements at different residual errors were 42.25, 4.73, and 2.75 for percentage root mean square difference (PRD), PRD1024, and PRD Normalized respectively. The work also reports extensive experimentations on the compressor for various durations of the ECG records (5-30 min, with 5-min increment). The proposed algorithm demonstrates significantly better perforthance in comparison to the contemporary stateof-the-art works present in the literature. (C) 2016 Elsevier Ltd. All rights reserved.
Keyword:
Electrocardiogram
ECG
Pre-processing
Data compression
Sample entropy
SampEn
JPEG2000
Quality score
Complexity sorting
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
C
IF:
4.9
论文数:
6.7K
被引数:
1.3W
机构
引用论文
.png){kind=icon}
A Novel ECG Data Compression Method Using Adaptive Fourier Decomposition With Security Guarantee in e-Health Applications一种基于自适应傅里叶分解的ECG数据压缩方法，在电子健康应用中具有安全保证
PREAI
分享收藏
分享收藏
查看更多内容