Data Compression for Wireless ECG Devices

Elena Merdjanovska, Elena Merdjanovska, Miha Mohorčič, Matjaž Depolli, Aleksandra Rashkovska, Tomaž Javornik

2022

Abstract

Wireless ECG devices are the latest novelty in the field of electrocardiography. ECG is commonly used in healthcare systems to observe cardiac activity, however wireless devices bring new challenges to the field of ECG monitoring. These challenges include limited battery capacity, as well as increased data storage requirements caused by daily uninterrupted ECG measurements. Both of these issues can be mitigated by introducing an efficient compression technique. This paper explores two direct data compression methods for ECG data: delta coding and Huffman coding, as well as their variations. We performed experiments both on measurements from a wireless ECG sensor – the Savvy ECG sensor, as well as on measurements from a standard public ECG database – the MIT-BIH Arrhythmia Database. We were able to select suitable parameters for delta coding for efficient compression of multiple ECG recordings from the Savvy ECG sensor, with a compression ratio of 1.6.

Paper Citation

in Harvard Style

Merdjanovska E., Mohorčič M., Depolli M., Rashkovska A. and Javornik T. (2022). Data Compression for Wireless ECG Devices. In Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2022) - Volume 4: BIOSIGNALS; ISBN 978-989-758-552-4, SciTePress, pages 15-21. DOI: 10.5220/0010818100003123

in Bibtex Style

@conference{biosignals22,
author={Elena Merdjanovska and Miha Mohorčič and Matjaž Depolli and Aleksandra Rashkovska and Tomaž Javornik},
title={Data Compression for Wireless ECG Devices},
booktitle={Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2022) - Volume 4: BIOSIGNALS},
year={2022},
pages={15-21},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010818100003123},
isbn={978-989-758-552-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2022) - Volume 4: BIOSIGNALS
TI - Data Compression for Wireless ECG Devices
SN - 978-989-758-552-4
AU - Merdjanovska E.
AU - Mohorčič M.
AU - Depolli M.
AU - Rashkovska A.
AU - Javornik T.
PY - 2022
SP - 15
EP - 21
DO - 10.5220/0010818100003123
PB - SciTePress