Journal ArticleDOI
A novel compression algorithm for electrocardiogram signals based on the linear prediction of the wavelet coefficients
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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
A Real-Time ECG Data Compression and Transmission Algorithm for an e-Health Device
TL;DR: Because the proposed real-time data compression and transmission algorithm can compress and transmit data in real time, it can be served as an optimal biosignal data transmission method for limited bandwidth communication between e-health devices.
Journal ArticleDOI
u-Healthcare system: state-of-the-art review and challenges.
Farid Touati,Rohan Tabish +1 more
TL;DR: A comprehensive review of up-to-date requirements in hardware, communication, and computing for next-generation u-Health systems is presented and new technological trends and design challenges they have to cope with, while designing such systems are presented.
Journal ArticleDOI
An ECG Signals Compression Method and Its Validation Using NNs
C.M. Fira,Liviu Goras +1 more
TL;DR: This paper presents a new algorithm for electrocardiogram (ECG) signal compression based on local extreme extraction, adaptive hysteretic filtering and Lempel-Ziv-Welch (LZW) coding, which takes into account both the reconstruction errors and the compression ratio.
Journal ArticleDOI
Wavelet-based electrocardiogram signal compression methods and their performances: A prospective review
TL;DR: A prospective review of wavelet-based ECG compression methods and their performances based upon findings obtained from various experiments conducted using both clean and noisy ECG signals is presented.
Journal ArticleDOI
Heart sound classification using wavelet transform and incremental self-organizing map
Zümray Dokur,Tamer Ölmez +1 more
TL;DR: In order to increase the performance of heart sound classification, an incremental neural network is proposed in this study and it is observed that ISOM successfully classifies the HSs even in noisy environment.
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.
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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.