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:
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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Journal ArticleDOI
Constrained ECG compression algorithm using the block-based discrete cosine transform
TL;DR: A novel method dedicated to ECG compression that uses the block-based discrete cosine transform and considers the percent root-mean-square difference (PRD) as a controlled quality criterion, and is classified as a valid concurrent to some recently published powerful methods.
Journal ArticleDOI
Electrocardiogram Compression Method Based on the Adaptive Wavelet Coefficients Quantization Combined to a Modified Two-Role Encoder
TL;DR: An effective method for electrocardiogram (ECG) compression is proposed, based on the pyramidal digital wavelet transform, which demonstrates clearly the method efficiency and the tradeoff rate-distortion is ensured successfully.
Journal ArticleDOI
Wavelet Packets Feasibility Study for the Design of an ECG Compressor
TL;DR: A thresholding-based method to encode ECG signals using wavelet packets that is versatile as far as neither QRS detection nor a priori signal information is required and can be applied to any ECG.
Journal ArticleDOI
ECG compression using uniform scalar dead-zone quantization and conditional entropy coding
TL;DR: Simulation results on several records from the MIT-BIH arrhythmia database show that the proposed coding algorithm outperforms some recently developed ECG compression algorithms.
Journal ArticleDOI
An ECG signal compression technique using ASCII character encoding
TL;DR: 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.
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.