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In this paper, an ECG signal compression technique is presented based on Slantlet transform with different thresholding functions. The presented compression method is exploited the uniform quantization (UQ) methods with different thresholding criteria on slantlet coefficients of ECG signal. This technique the returned the better reconstruction from compressed data as compare to wavelet and discrete...
Automated electrocardiogram (ECG) beat classification is an important component of heart monitoring systems used for raising an emergency call during sudden cardiac disorder of patients. An automatic ECG beat classifier is proposed to exploit the bandwidth features that are exclusively extracted from analytic intrinsic mode functions (IMFs). The proposed methodology employs artificial bee colony (ABC)...
In this paper, a compression technique for ECG signal using low-rank matrix approximation based on inter and intra beat correlation, is presented. Here, singular value decomposition (SVD) has been exploited to explore the low rank representation using truncation process that stores most significant data with few singular values. In this method, two dimensional (2-D) array of ECG signal is constructed...
An Electrocardiogram (ECG) signal compression technique is proposed using compressed sensing/sampling technique based on Block sparse Bayesian learning (BSBL) algorithm. Advantage of proposed method over the conventional stat-of-art techniques is energy efficient, highly compressive and minimum reconstruction error. Here, BSBL technique has utilized especially for compression of ECG signal to enhance...
In this paper, a linear predictive coding (LPC) based electrocardiogram (ECG) signal compression technique is examined and improved by exploiting different wavelet filters and thresholding functions. In this method, ECG signals are captured from MITBIH arrhythmia database and compression is achieved by propagating wavelet coefficients of ECG signal to linear predictive coder. Then different thresholding...
In this paper, a ECG compression system is presented based on two-dimensional discrete wavelet transform (2D DWT) and Huffman coding technique. In this method, two different approaches are utilized to construct a 2D array of 1D ECG signal using cut and align (CAB) technique, therefore ECG 2D array is decomposed with 2D DWT which results more number of insignificant coefficients. They are considered...
A simple efficient iterative technique for the design of non-uniform filter banks (NUFB) proposed by Soni et al is examined and improved by designing the prototype filters using constrained equiripple finite impulse response (FIR) technique. In this method, instead of optimizing the cut-off frequency, the passband edge frequency (ωP) is varied iteratively in order to adjust the filter coefficients...
An iterative method for the design of the non-uniform filter banks (NUFB) proposed by Soni et al is examined and improved by designing the prototype filters using the modified window such as Kaiser, Cosh and Exponential. These windows are modified by adding third parameter (ρ) which improves the spectral characteristic of the window in terms of smaller ripple ratio (RR), the wider main lobe width...
In this paper, we present a simple approach for implementing a pulse analyzer for devices with limited computational power, such as mobile and wearable computers. The main purpose of this system is to continuously monitor the ECG of a person and detect any possible heart abnormalities. The idea is to break the required computation in two parts. The learning and model building part that requires high...
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