@inproceedings{2cdc7449a7ef4e129fcd66a800238c03,
title = "Efficient Lossless Compression Scheme for Multi-channel ECG Signal",
abstract = "Electrocardiogram (ECG) is the recording of the heart electrical activity and used to diagnose heart disease nowadays. The diagnosis requires a large amount of time for acquiring enough multi-channel data normally. Thus storage and transmission of 12 lead ECG data will result in massive cost. In this work, we propose a multi-channel ECG lossless compression which uses the adaptive linear prediction for intra and inter channel decorrelation. The proposed technique is based on the adaptive Golomb-Rice codec for entropy coding with adaptive linear prediction. Thus the coefficient of linear prediction and Golomb-Rice codec will make self-adjustment during the process. Finally we evaluate the proposed algorithm with MIT-BIH Arrhythmia database for single-channel compression, and PTB database for multichannel compression.",
keywords = "Golomb-Rice codec, Lossless compression, linear prediction, multi-channel ECG signal, telemedicine",
author = "Tsai, {Tsung Han} and Tsai, {Fong Lin}",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 ; Conference date: 12-05-2019 Through 17-05-2019",
year = "2019",
month = may,
doi = "10.1109/ICASSP.2019.8683836",
language = "???core.languages.en_GB???",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1289--1292",
booktitle = "2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings",
}