Journal ArticleDOI
ECG data compression techniques-a unified approach
TLDR
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.Abstract:
Electrocardiogram (ECG) compression techniques are compared, and a unified view of these techniques is established. ECG data compression schemes are presented in two major groups: direct data compression and transformation methods. The direct data compression techniques are ECG differential pulse code modulation (DPCM) and entropy coding, AZTEC, Turning-point, CORTES, Fan and SAPA algorithms, peak-picking, and cycle-to-cycle compression methods. The transformation methods include Fourier, Walsh, and Karhunen-Loeve transforms. 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. A framework for evaluation and comparison of ECG compression schemes is presented. >read more
Citations
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Journal ArticleDOI
A 2-D ECG compression algorithm based on wavelet transform and vector quantization
Xingyuan Wang,Juan Meng +1 more
TL;DR: The experimental results show that the proposed method is suitable for various morphologies of ECG data, and that it achieves higher compression ratio with the characteristic features well preserved.
Journal ArticleDOI
KLT-based quality controlled compression of single-lead ECG
TL;DR: An electrocardiogram (EGG) compression algorithm based on a combination of the Karhunen-Loeve transform and multirate sampling and a beat-by-beat quality controlled compression criterion is shown to be necessary to ensure clinically adequate reconstruction of each beat.
Proceedings ArticleDOI
ECG data compression with the Karhunen-Loeve transform
TL;DR: The authors analyze a Karhunen-Loeve transform technique for ECG data compression and finds the optimum number of coefficients and bits for coding the signal for the MIT-BIH Arrythmia database.
Journal ArticleDOI
Optimal wavelets for biomedical signal compression
Mogens Nielsen,Ernest Nlandu Kamavuako,Michael Midtgaard Andersen,Marie-Francoise Lucas,Dario Farina +4 more
TL;DR: A novel scheme of signal compression based on signal-dependent wavelets that can be applied to any signal type since the optimal wavelet is selected on a signal-by-signal basis is proposed.
References
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