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Compression of ECG Signal Based on Improving the Signal Sparsity Adopting QRS-Complex Estimation and Spatial Domain Transforms

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Last updated: 25 Dec 2024

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Abstract

In this paper, an ECG signal compression technique based on improving the signal sparsity adopting QRS-complex estimation and spatial domain transforms is proposed. Compressive Sensing (CS) framework is utilized for this purpose; where the difference between the rate of change of a signal and the rate of change of its information contents is utilized. The proposed method starts with estimating the QRS-complex through the detection of the maximum amplitudes and the start and end points of the signal components. The error signal calculated as the difference between the estimated QRS-complex samples and original ECG samples is transformed using either DWT, DCT or FFT. QRS-complex estimation results in sparser timedomain error signal and the sparsity is increased by adopting the spatial-domain transforms. The proposed technique is assessed by calculating PRD and CR. Numerical results indicate that DWT gives a higher CR and lower PRD. The effect of increasing the signal sparsity, signal length, wavelet filters and wavelet decomposition levels have been studied. Comparison with recently published results [1] adopted only QRS-estimation and DWT indicate that the utilization of CS with both QRS-estimation and DWT yields to improved acceptable retrieved signal quality and higher CR. Moreover, comparison with other four CS-based algorithms [2]-[5] and other traditional ECG compression algorithm [6] indicates the superior performance of the proposed algorithm.
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DOI

10.21608/mjeer.2016.64095

Authors

First Name

Mohammed

Last Name

Abo-Zahhad

MiddleName

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Affiliation

Electrical and Electronics Eng. Dept., Faculty of Eng., Assiut University, Egypt.

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Orcid

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First Name

Aziza

Last Name

Hussein

MiddleName

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Affiliation

Computer and Systems Dept., Faculty of Engineering, Minia University, Egypt.

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Orcid

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First Name

Abdelfatah

Last Name

Mohamed

MiddleName

-

Affiliation

Electrical and Electronics Eng. Dept., Faculty of Eng., Assiut University, Egypt.

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Volume

25

Article Issue

2

Related Issue

9501

Issue Date

2016-07-01

Receive Date

2015-12-23

Publish Date

2016-07-01

Page Start

179

Page End

190

Print ISSN

1687-1189

Online ISSN

2682-3535

Link

https://mjeer.journals.ekb.eg/article_64095.html

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https://mjeer.journals.ekb.eg/service?article_code=64095

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4

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Original Article

Type Code

1,088

Publication Type

Journal

Publication Title

Menoufia Journal of Electronic Engineering Research

Publication Link

https://mjeer.journals.ekb.eg/

MainTitle

Compression of ECG Signal Based on Improving the Signal Sparsity Adopting QRS-Complex Estimation and Spatial Domain Transforms

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Article

Created At

22 Jan 2023