Journal ArticleDOI
A novel compression algorithm for electrocardiogram signals based on the linear prediction of the wavelet coefficients
TLDR
A new algorithm for electrocardiogram (ECG) compression based on the compression of the linearly predicted residuals of the wavelet coefficients of the signal, which reduces the bit rate while keeping the reconstructed signal distortion at a clinically acceptable level.About:Â
This article is published in Digital Signal Processing.The article was published on 2003-10-01. It has received 97 citations till now. The article focuses on the topics: Wavelet transform & Stationary wavelet transform.read more
Citations
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Proceedings ArticleDOI
ECG compression using multilevel thresholding of wavelet coefficients
TL;DR: A wavelet-based electrocardiogram (ECG) compression algorithm that reduces the bit rate of ECG and preserves its main clinically diagnostic features intact by minimizing reconstructed signal distortion.
Journal ArticleDOI
Analysis on ECG Data Compression Using Wavelet Transform Technique
TL;DR: Wavelet based compression algorithms for one-dimensional signals are presented along with the results of compression ECG data and compression using HAAR wavelet and local thresholding are found to be optimal in terms of compression ratio.
ECG compression using wavelet transform and three-level quantization
TL;DR: An efficient technique for compression of electrocardiogram (ECG) signals using the three level of quantization for thresholding and an embedded of zero-tree wavelet (EZW) method and Huffman algorithms is presented.
Proceedings ArticleDOI
An ECG Data Compression Method via Standard Deviation and ASCII Character Encoding
TL;DR: It is observed that this proposed algorithm can reduce the file size significantly and the data reconstruction algorithm has been developed using the reversed logic and it is seen that data is reconstructed preserving the significant ECG signal morphology.
Journal ArticleDOI
Computational efficient method for ECG signal compression based on modified SPIHT technique
TL;DR: An improved method for electrocardiogram (ECG) signal compression using Set Partitioning in Hierarchical Trees (SPIHT) algorithm that yields good compression with controlled quantity of signal degradation and requires computational time as compared to earlier published SPIHT algorithms.
References
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Journal ArticleDOI
Linear prediction: A tutorial review
TL;DR: This paper gives an exposition of linear prediction in the analysis of discrete signals as a linear combination of its past values and present and past values of a hypothetical input to a system whose output is the given signal.
Book
Digital Processing of Speech Signals
TL;DR: This paper presents a meta-modelling framework for digital Speech Processing for Man-Machine Communication by Voice that automates the very labor-intensive and therefore time-heavy and expensive process of encoding and decoding speech.
Journal ArticleDOI
Wavelets and filter banks: theory and design
Martin Vetterli,Cormac Herley +1 more
TL;DR: The perfect reconstruction condition is posed as a Bezout identity, and it is shown how it is possible to find all higher-degree complementary filters based on an analogy with the theory of Diophantine equations.
Journal ArticleDOI
ECG data compression techniques-a unified approach
TL;DR: The theoretical bases behind the direct ECG data compression schemes are presented and classified into three categories: tolerance-comparison compression, DPCM, and entropy coding methods and a framework for evaluation and comparison of ECG compression schemes is presented.
Journal ArticleDOI
Wavelet and wavelet packet compression of electrocardiograms
TL;DR: Pilot data from a blind evaluation of compressed ECG's by cardiologists suggest that the clinically useful information present in original ECG signals is preserved by 8:1 compression, and in most cases 16:1 compressed ECGs are clinically useful.