Lossless ECG Signal Compression Using Non-linear Predictor and ASCII Character Encoding

Thivaagar Thamil Selvan; Kannan Ramakrishnan; Vijayakumar Vengadasalam; Rathimala Kannan

doi:10.2991/978-94-6463-094-7_41

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Lossless ECG Signal Compression Using Non-linear Predictor and ASCII Character Encoding

Authors

Thivaagar Thamil Selvan¹, Kannan Ramakrishnan¹^{, *}, Vijayakumar Vengadasalam¹, Rathimala Kannan²

¹Multimedia University, Cyberjaya, Malaysia

²Information Technology Department, Multimedia University, Cyberjaya, Malaysia

^*Corresponding author. Email: kannan.ramakrishnan@mmu.edu.my

Corresponding Author

Kannan Ramakrishnan

Available Online 27 December 2022.

DOI: 10.2991/978-94-6463-094-7_41 How to use a DOI?
Keywords: Biomedical; ECG signal; ASCII character; Lossless; Multilayer perceptron; Encoding; Decoding
Abstract: Electrocardiogram is a method of recording the heartbeat of a patient electronically. Storing or transmitting enormous amount of ECG signals to another device or via online is an unendurable process without compressing the signals. The purpose of this paper is to develop an efficient Electrocardiogram (ECG) compression technique using non-linear predictor and ASCII character encoding. The digitized ECG signal values are applied to Multi-layer Perceptron (MLP) neural network algorithm for non-liner prediction and the residues of the signal are passed through ASCII character encoding for further compression. It is shown that a compression ratio of 2.3726 can be achieved through this technique without any loss of information for MIT-BIH arrhythmia database records.
Copyright: © 2022 The Author(s)
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title: Proceedings of the International Conference on Computer, Information Technology and Intelligent Computing (CITIC 2022)
Series: Atlantis Highlights in Computer Sciences
Publication Date: 27 December 2022
ISBN: 978-94-6463-094-7
ISSN: 2589-4900
DOI: 10.2991/978-94-6463-094-7_41 How to use a DOI?
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

ris enw bib

TY  - CONF
AU  - Thivaagar Thamil Selvan
AU  - Kannan Ramakrishnan
AU  - Vijayakumar Vengadasalam
AU  - Rathimala Kannan
PY  - 2022
DA  - 2022/12/27
TI  - Lossless ECG Signal Compression Using Non-linear Predictor and ASCII Character Encoding
BT  - Proceedings of the International Conference on Computer, Information Technology and Intelligent Computing (CITIC 2022)
PB  - Atlantis Press
SP  - 513
EP  - 523
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-094-7_41
DO  - 10.2991/978-94-6463-094-7_41
ID  - Selvan2022
ER  -

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