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
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
Estimation of QRS Complex Power Spectra for Design of a QRS Filter
TL;DR: The power spectral analysis shows that the QRS complex could be separated from other interfering signals, and it is observed that a bandpass filter with a center frequency of 17 Hz and a Q of 5 yields the best signal-to-noise ratio.
Journal ArticleDOI
ECG compression using long-term prediction
G. Nave,Arnon D. Cohen +1 more
TL;DR: A new algorithm for ECG signal compression is introduced that can be considered a generalization of the recently published average beat subtraction method, and was found superior at any bit rate.
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ECG coding by wavelet-based linear prediction
A. G. Ramakrishnan,Saikat Saha +1 more
TL;DR: The significant feature of the proposed technique is that, while the error is nearly uniform throughout the cycle, the diagnostically crucial QRS region is kept free of maximal reconstruction error.
Journal ArticleDOI
Compression of ECG signals by optimized quantization of discrete cosine transform coefficients.
TL;DR: Experiments with ECG records used in other results from the literature revealed that the proposed method compares favorably with various classical and state-of-the-art ECG compressors.
Journal ArticleDOI
Mean-shape vector quantizer for ECG signal compression
TL;DR: A direct waveform mean-shape vector quantization (MSVQ) is proposed here as an alternative for electrocardiographic (ECG) signal compression, leading to high compression ratios (CRs) while maintaining a low level of waveform distortion and preserving the main clinically interesting features of the ECG signals.