Journal ArticleDOI
A novel compression algorithm for electrocardiogram signals based on the linear prediction of the wavelet coefficients
Reads0
Chats0
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
More filters
Journal Article
ECG Compression Using Subband Thresholding of the Wavelet Coefficients
Sharafat Hossain,Nowshad Amin +1 more
TL;DR: Experiments on selected records from the MIT-BIH arrhythmia database reveal that the proposed method is significantly more efficient in compression than some existing wavelet based ECG compression method.
Proceedings ArticleDOI
An ECG data compression method via R-Peak detection and ASCII Character Encoding
TL;DR: A software based effective ECG data compression algorithm is proposed and the data reconstruction algorithm has also been developed using the reversed logic and it is seen that data is reconstructed preserving the significant ECG signal morphology.
Wavelet-based ECG Compression using Dynamic
Gyu-Hyeok Jeong,In-Sung Lee +1 more
TL;DR: An improved wavelet compression algorithm for electrocardiogram (ECG) signals which is combined with the lifting wavelet transform (WT) and the dynamic multi-stage vector quantization (MS-VQ) and preliminary results indicate that the proposed method excels over previous techniques for high fidelity compression.
Journal ArticleDOI
Effective compression and classification of ECG arrhythmia by singular value decomposition
TL;DR: In this paper, a simple but efficient method utilizing singular value decomposition (SVD) to decompose ECG signals, then applied the decompressed data to a convolutional neural network (CNN) and supporting vector machine (SVM) for classification.
Journal ArticleDOI
ECG signal compression using the optimised wavelet filter banks
Anil Kumar,K. Ranjeet +1 more
TL;DR: In this article, an optimised wavelet filter bank based methodology is presented for compression of Electrocardiogram (ECG) signal using simple linear optimisation, the methodology employs new wavelet filtering bank whose coefficients are derived with different window techniques such as Kaiser and Blackman windows, which gives better compression ratio and also yields good fidelity parameters as compared to other wavelet filters.
References
More filters
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.