ECG Data Compression Using ε-insensitive Quadratic Loss Function

Omer Karal

doi:10.19113/sdufbed.82260

ECG Data Compression Using ε-insensitive Quadratic Loss Function

Abstract

ElectroCardioGram (ECG) is a graphical representation of the electrical activity that occurred during the heartbeat. It plays a significant role in the diagnosis and analysis of heart diseases. ECG signals must be recorded continuously for the effective detection and diagnosis of heart diseases. However, such records as it produces large amounts of data at a level that makes it difficult storage and transmission can also be impaired due to the ambient noise. Thanks to the reasons mentioned above, an efficient ECG data compression algorithm is required even in a noisy environment. This study proposes ε-insensitive quadratic loss based Support Vector Regression (ε-quadratic SVR) technique for the compression of ECG signals. There is a well-known relationship between loss functions and noise distributions. The proposed ε-insensitive quadratic loss function provides the optimal solution against Gaussian noise. Computer simulation results show that the proposed loss function is an attractive candidate for ECG data compression in the presence of Gaussian noise.

Keywords

Data compression,Electrocardiogram; Modeling; Quadratic loss function; Support vector regression

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Details

Primary Language

Turkish

Subjects

-

Journal Section

-

Authors

Omer Karal

Publication Date

August 15, 2018

Submission Date

November 7, 2017

Acceptance Date

-

Published in Issue

Year 2018 Volume: 22 Number: 2

DOI

https://doi.org/10.19113/sdufbed.82260

IZ

https://izlik.org/JA74EJ94UX

Cite

RIS / Bibtex

APA

Karal, O. (2018). ECG Data Compression Using ε-insensitive Quadratic Loss Function. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 22(2), 380-387. https://doi.org/10.19113/sdufbed.82260

AMA

1.Karal O. ECG Data Compression Using ε-insensitive Quadratic Loss Function. J. Nat. Appl. Sci. 2018;22(2):380-387. doi:10.19113/sdufbed.82260

Chicago

Karal, Omer. 2018. “ECG Data Compression Using ε-Insensitive Quadratic Loss Function”. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi 22 (2): 380-87. https://doi.org/10.19113/sdufbed.82260.

EndNote

Karal O (August 1, 2018) ECG Data Compression Using ε-insensitive Quadratic Loss Function. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi 22 2 380–387.

IEEE

[1]O. Karal, “ECG Data Compression Using ε-insensitive Quadratic Loss Function”, J. Nat. Appl. Sci., vol. 22, no. 2, pp. 380–387, Aug. 2018, doi: 10.19113/sdufbed.82260.

ISNAD

Karal, Omer. “ECG Data Compression Using ε-Insensitive Quadratic Loss Function”. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi 22/2 (August 1, 2018): 380-387. https://doi.org/10.19113/sdufbed.82260.

JAMA

1.Karal O. ECG Data Compression Using ε-insensitive Quadratic Loss Function. J. Nat. Appl. Sci. 2018;22:380–387.

MLA

Karal, Omer. “ECG Data Compression Using ε-Insensitive Quadratic Loss Function”. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi, vol. 22, no. 2, Aug. 2018, pp. 380-7, doi:10.19113/sdufbed.82260.

Vancouver

1.Omer Karal. ECG Data Compression Using ε-insensitive Quadratic Loss Function. J. Nat. Appl. Sci. 2018 Aug. 1;22(2):380-7. doi:10.19113/sdufbed.82260

Cited By

ε-Insensitive Least Squares Support Vector Regression with Sequential Minimal Optimization

Computing Open

https://doi.org/10.1142/S2972370123500046