ECG Signal Compression Using Discrete Wavelet Transform

Abo‐Zahhad, Mohammed

doi:10.5772/16019

Cited by 21 publications

(14 citation statements)

References 39 publications

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“…All transform based techniques are based on spectral and energy distribution analysis of the signal, which provide the detection of redundancy. The methods under this category are: Fast Fourier Transform (FFT), Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), Walsh Transformation (WT), and Karhunen-Loeve Transform (KLT) [8]- [9]. FFT is a discrete Fourier transform (DFT) algorithm which reduces the number of computations needed for a signal of length N samples from 2N 2 to 2N log 2 N. In literature [10], many methods have been proposed for compressing the ECG signal.…”

Section: Transformational Ecg Compression Techniquesmentioning

confidence: 99%

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Ecg Signal Compression Technique Based on DWT and Exploitation of Interbeats and Intrabeats Correlations

Abo‐Zahhad

Hussein

Mohamed

2015

JES. Journal of Engineering Sciences

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A hybrid ECG compression technique based on DWT and reducing the correlation between signal samples and beats has been presented in this paper. It starts by segmenting the ECG signal into blocks; each has 1024 samples. Then, DPCM approach is adopted by removing the redundancy between successive samples. This yields to residual signal with QRS-complex like waveform without the presence of P-, T-and U-waves. Then the first QRS-complex like wave is isolated and all the succeeding ones are subtracted from the preceding ones to remove the redundancy between signal beats. The next process depends on the application. For telediagnoses, the resulting residual signal is wavelet transformed while for telemonitoring both the first QRS-complex like wave and the residual signal are wavelet transformed. In both cases the resulting wavelet coefficients are thresholded based on energy packing efficiency and coded using modified run-length algorithm. The performance of the proposed algorithm has been tested on records extracted from MIT-BIH arrhythmia database. Simulation results illustrate the excellent quality of the reconstructed signal with percentage-root-mean square difference less than 1.5% and compression ratios greater than 20.

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Section: Transformational Ecg Compression Techniquesmentioning

confidence: 99%

“…These correlation properties play a big role in heart rate variability analysis and data compression. In the context of ECG signal compression, several algorithms have been proposed using correlation properties during the last few years, based on image processing and coding techniques [8]- [9].…”

Section: The Proposed Compression Schemementioning

confidence: 99%

Ecg Signal Compression Technique Based on DWT and Exploitation of Interbeats and Intrabeats Correlations

Abo‐Zahhad

Hussein

Mohamed

2015

JES. Journal of Engineering Sciences

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“…A wearable patch ECG monitor (PEM) records ECG signals using an embedded electronic circuit that is attached to a patient's chest with invisible electrodes and lead wires. The device can be considered a wearable health care system that is based on the use of knitted integrated sensors connected to electrodes using a conductive and piezoresistive yarn [12]. PEMs are typically highly energy-efficient and provide an analog readout application-specific integrated circuit (ASIC) for signal acquisition, amplification, and analog-to-digital conversion.…”

Section: Introductionmentioning

confidence: 99%

A Real Time and Lossless Encoding Scheme for Patch Electrocardiogram Monitors

Fang

2018

Applied Sciences

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Cardiovascular diseases are the leading cause of death worldwide. Due to advancements facilitating the integration of electric and adhesive technologies, long-term patch electrocardiogram (ECG) monitors (PEMs) are currently used to conduct daily continuous cardiac function assessments. This paper presents an ECG encoding scheme for joint lossless data compression and heartbeat detection to minimize the circuit footprint size and power consumption of a PEM. The proposed encoding scheme supports two operation modes: fixed-block mode and dynamic-block mode. Both modes compress ECG data losslessly, but only dynamic-block mode supports the heartbeat detection feature. The whole encoding scheme was implemented on a C-platform and tested with ECG data from MIT/BIH arrhythmia databases. A compression ratio of 2.1 could be achieved with a normal heartbeat. Dynamic-block mode provides heartbeat detection accuracy at a rate higher than 98%. Fixed-block mode was also implemented on the field-programmable gate array, and could be used as a chip for using analog-to-digital convertor-ready signals as an operation clock.

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“…The desired objective is to provide a high-quality reconstruction of electrocardiogram signals at low bit rates and acceptable distortion levels. Many algorithms for ECG data compression have been proposed in the last three decades [1] - [18] to achieve high compression ratios and good signal quality without affecting the diagnostic features in the reconstructed signal. The current technologies provide sufficient space to store or transmit data, so now it is no more a big problem.…”

Section: Introductionmentioning

confidence: 99%

“…The block diagram of the proposed approach is indicated in Figure ( 1). It shows that firstly the ECG signal is preprocessed and split into beats segments by detecting the QRScomplex.…”

Section: Introductionmentioning

confidence: 99%

A New ECG Compression Algorithm Based On Wavelet Foveation And Huffman Coding Techniques

Abo‐Zahhad

Ahmed

Zakaria

2013

JES. Journal of Engineering Sciences

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This paper introduces a new ECG signal compression algorithm based on modulating the ECG signal DWT coefficients with a proper mask constructed using the foveation principle. The constructed mask is a selective mask that gives a high resolution at a certain point (fovea) and falls down away from this point. The wavelet foveation of the ECG signal leads to decreasing the amount of information contained in the signal. So, the value of the foveated ECG signal Entropy will be decreased which by turn will increase the Compression Ratio (CR).The ECG signal after wavelet foveation is coded using Huffman codes; namely optimal selective Huffman coding, adaptive Huffman coding and modified adaptive Huffman coding. The performance of each coding technique is measured based on the CR, time cost and computational complexity.

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ECG Signal Compression Using Discrete Wavelet Transform

Cited by 21 publications

References 39 publications

Ecg Signal Compression Technique Based on DWT and Exploitation of Interbeats and Intrabeats Correlations

Ecg Signal Compression Technique Based on DWT and Exploitation of Interbeats and Intrabeats Correlations

A Real Time and Lossless Encoding Scheme for Patch Electrocardiogram Monitors

A New ECG Compression Algorithm Based On Wavelet Foveation And Huffman Coding Techniques

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