Journal ArticleDOI
ECG data compression techniques-a unified approach
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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
Compression of ECG signals using variable-length classifıed vector sets and wavelet transforms
TL;DR: An improved and more efficient algorithm for the compression of the electrocardiogram (ECG) signals is presented, which combines the processes of modeling ECG signal by variable-length classified signature and envelope vector sets (VL-CSEVS), and residual error coding via wavelet transform.
Journal ArticleDOI
Electrocardiogram Signal Compression Using Beta Wavelets
TL;DR: The simulation result included in this paper shows the clearly increased efficacy and performance in the field of biomedical signal processing.
Journal ArticleDOI
Wavelet transform and Huffman coding based electrocardiogram compression algorithm: Application to telecardiology
TL;DR: The proposed ECG compression algorithm is articulated on the use of wavelet transform, leading to low/high frequency components separation, high order statistics based thresholding, to denoise the ECG signal, and next a linear predictive coding filter is applied to the wavelet coefficients producing a lower variance signal.
Proceedings ArticleDOI
Compression of ECG signals based on optimum quantization of discrete cosine transform coefficients and Golomb-Rice coding
TL;DR: This paper proposes an ECG signal compressor based on optimum quantization of discrete cosine transform (DCT) coefficients and Golomb-Rice coding, and assesses the performance of the compressor at various distortion levels.
Proceedings ArticleDOI
A novel ECG data compression algorithm using best mother wavelet selection
TL;DR: The proposed algorithm provides a fast Daubechies mother wavelet selection approach based on minimum value of percent root-mean-square difference for minimum percentage root mean square difference in electrocardiogram data compression.
References
More filters
Journal ArticleDOI
A mathematical theory of communication
TL;DR: This final installment of the paper considers the case where the signals or the messages or both are continuously variable, in contrast with the discrete nature assumed until now.
Journal ArticleDOI
A Method for the Construction of Minimum-Redundancy Codes
TL;DR: A minimum-redundancy code is one constructed in such a way that the average number of coding digits per message is minimized.
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.
Journal ArticleDOI
Arithmetic coding for data compression
TL;DR: The state of the art in data compression is arithmetic coding, not the better-known Huffman method, which gives greater compression, is faster for adaptive models, and clearly separates the model from the channel encoding.
Proceedings ArticleDOI
Orthogonal transforms for digital signal processing
K. R. Rao,N. U. Ahmed +1 more
TL;DR: The utility and effectiveness of these transforms are evaluated in terms of some standard performance criteria such as computational complexity, variance distribution, mean-square error, correlated rms error, rate distortion, data compression, classification error, and digital hardware realization.