Journal ArticleDOI
ECG data compression techniques-a unified approach
Reads0
Chats0
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
More filters
Compresión de fonocardiogramas mediante las transformadas wavelet y wavelet packet
TL;DR: Este trabajo ha sido financiado parcialmente por la Fundación Seneca de la Region de Murcia y el Ministerio de Ciencia y Tecnologia, mediante la concesion de los676676proyectos PB/63/FS/02 and TIC2003-09400-C04-02,respectivamente.
Proceedings ArticleDOI
ECG Data Compression by Independent Component Analysis
TL;DR: Results showed that using ICA yields far smaller reconstruction errors when comparing the ICA results to the KLT results, so as to find a more efficient code.
Proceedings ArticleDOI
Efficient ECG Approximation Using Chebyshev Polynomials
Om Prakash Yadav,Shashwati Ray +1 more
TL;DR: An efficient model is designed to compress ECGs of MIT-BIR using majorization-minorization optimization technique and is found to be better than other existing approximation models.
Proceedings ArticleDOI
Signal compression by piecewise linear non-interpolating approximation
TL;DR: This paper generalizes the exact optimization scheme by removing the interpolation restriction when applying piecewise linear approximation, which guarantees a lower reconstruction error with respect to the number of extracted signal samples.
Book ChapterDOI
Compressing Data by Shortest Path Methods
TL;DR: Compressing the data in such a way that close reconstructions can be found, is a highly respected problem in signal processing.
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.