Journal ArticleDOI
A wavelet transform-based ECG compression method guaranteeing desired signal quality
Jie Chen,Shuichi Itoh +1 more
TLDR
A new electrocardiogram compression method based on orthonormal wavelet transform and an adaptive quantization strategy, by which a predetermined percent root mean square difference (PRD) can be guaranteed with high compression ratio and low implementation complexity are presented.Abstract:
This paper presents a new electrocardiogram (ECG) compression method based on orthonormal wavelet transform and an adaptive quantization strategy, by which a predetermined percent root mean square difference (PRD) can be guaranteed with high compression ratio and low implementation complexity.read more
Citations
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Proceedings ArticleDOI
ECG denoising and compression by sparse 2D separable transform with overcomplete mixed dictionaries
TL;DR: An algorithm for ECG denoising and compression based on a sparse separable 2-dimensional transform for both complete and overcomplete dictionaries is studied and it is experimentally shown that the algorithm outperforms soft thresholding for about 4dB or more and also outperforms Extended Kalman Smoother filtering for about 2dB in higher input SNRs.
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.
Journal ArticleDOI
Consistent quality control in ECG compression by means of direct metrics.
TL;DR: This work proposes the use of the root mean square error (RMSE) for quality control because it provides a clearer and more stable idea about how much the retrieved ECG waveform separates from the original.
Journal ArticleDOI
Adaptive Sampling of the Electrocardiogram Based on Generalized Perceptual Features.
TL;DR: This paper proposes the application of generalized perceptual features to control the adaptive sampling of a digital ECG and shows good reproducibility of ECG diagnostic features, within the IEC 60601-2-25:2015 requirements, thanks to the occurrence of distortions in less relevant parts of the cardiac cycle.
Wavelet transform in ECG signal processing
TL;DR: The theory of wavelet transform is introduced and several promising applications in cardiology are shown, including data compression and digital signal processing and analysis.
References
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Orthonormal bases of compactly supported wavelets
TL;DR: This work construct orthonormal bases of compactly supported wavelets, with arbitrarily high regularity, by reviewing the concept of multiresolution analysis as well as several algorithms in vision decomposition and reconstruction.
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A Technique for High-Performance Data Compression
TL;DR: A new compression algorithm is introduced that is based on principles not found in existing commercial methods in that it dynamically adapts to the redundancy characteristics of the data being compressed, and serves to illustrate system problems inherent in using any compression scheme.
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Digital Coding of Waveforms: Principles and Applications to Speech and Video
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.