ECG data compression by sub-band coding

Abstract

References 1 HAIGH, D., and EVERARD, J. (Eds.): 'GaAs technology and its impact on circuits and systems' (Peter Peregrinus Ltd. on behalf of IEE, 1989) 2 RAUSCHER, c. , and WILLING, H.: 'Simulation of nonlinear microwave FET performance using a quasi-static model', IEEE Trans., 1979, M'lT-27, pp. 836840 FILICORI, F., and MONACO, v. A.: 'Computer-aided design of nonlinear microwave circuits', Alta Frequenra, 1988, LVII, (7), pp. 355-378 4 CHIONE, G., FTLICORI, F., and NALDI, c. : 'Physical modeling of GaAs MESFETs in an integrated CAD environment: from device technology to microwave circuit performance',

ECG signal compression algorithm based on joint-multiresolution analysis (J-MRA)

“…There are so many different methods developed for ECG processing as well as ECG signal compression [2]. Techniques can be categorized into three types: direct techniques [1][2][3][4][5][6][7][8], parameter extraction [9][10][11] and transform and coding based techniques [12][13].In early stage of research, several methods such as turning point (TP) [4], amplitude zone time epoch coding (AZTEC) [5], coordinate reduction time encoding system (CORTES) [6], Fan and scan-along polygonal approximation (SAPA) algorithms [7], Peak-Picking (spline) with Entropy Encoding [8]and DPCM-linear Prediction, Interpolation and Entropy coding [9] . An ECG is a physiological signal of cardiac functionality due to ionic activity in the cardiac muscles of human heart.…”

“…In the past two decades, a substantial progress has been made in the field of data compression [11][12][13][14]. Here, transform based compression techniques are has become popular for ECG signals; especially wavelet transform based techniques [13,[15][16][17][18][19][20][21][22][23][24].…”

“…Here, transform based compression techniques are has become popular for ECG signals; especially wavelet transform based techniques [13,[15][16][17][18][19][20][21][22][23][24]. These techniques are categorising as 1D transformation based and 2D transformation based compression.…”

Dual tree DWT analysis based electrocardiogram signal compression using zero coding technique

“…There are so many different methods developed for ECG processing as well ECG signal compression [2]. This can be categorized into three main sections as follows: direct techniques [1][2][3][4][5][6][7][8], parameter extraction [9][10][11] and transform and coding based techniques [12][13][14][15][16][17][18][19][20][21][22][23]. In early stage of research, several methods such as turning point (TP) [4], amplitude zone time epoch coding (AZTEC) [5], coordinate reduction time encoding system (CORTES) [6], Fan and scan-along polygonal approximation (SAPA) algorithms [7], Peak-Picking (spline) with Entropy Encoding [8] and DPCM-linear Prediction, Interpolation and Entropy coding [9] were developed based on direct scheme in which compression is achieved by eliminating redundancy between different ECG samples in the time domain.…”

A novel method to represent ECG signals via predefined personalized signature and envelope functions

“…Usually, linear models are preferred for the sake of simplicity. In the existing literature, efforts have been made to represent the ECG signals in terms of the linear combination of somewhat orthogonal functions such as complex exponentials, trigonometric functions, wavelets or pre-selected, signature functions, which best describe the signal [1][2][3][4][5][6][7]. For example, in [5][6], over a finite time interval, limited number of ad-hoc sinusoidal waveforms with arbitrary frequencies is selected as signature functions.…”