@inproceedings{2b63cb759b7c4de6a9f7e4f972d96f4a,
title = "ECG signal compression by predictive coding and Set Partitioning in Hierarchical Trees (SPIHT)",
abstract = "In this paper we present a method for multi-lead ECG signal compression using Predictive Coding combined with Set Partitioning In Hierarchical Trees (SPIHT). We utilize linear prediction between the beats to exploit the high correlation among those beats. This method can optimize the redundancy between adjacent samples and adjacent beats. Predictive coding is the next step after beat reordering step. The purpose of using predictive coding is to minimize amplitude variance of 2D ECG array so the compression error can be minimize. The experiments from selected records from MIT-BIH arrhythmia database shows that the proposed method is more efficient for ECG signal compression compared with original SPIHT and relatively have lower distortion with the same compression ratios compared to the other wavelet transformation techniques.",
keywords = "Compression, Electrocardiogram, Predictive Coding, SPIHT, wavelet transform",
author = "Grafika Jati and Aprinaldi and Isa, {Sani M.} and Wisnu Jatmiko",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; International Conference on Advanced Computer Science and Information Systems, ICACSIS 2015 ; Conference date: 10-10-2015 Through 11-10-2015",
year = "2016",
month = feb,
day = "19",
doi = "10.1109/ICACSIS.2015.7415191",
language = "English",
series = "ICACSIS 2015 - 2015 International Conference on Advanced Computer Science and Information Systems, Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "257--262",
booktitle = "ICACSIS 2015 - 2015 International Conference on Advanced Computer Science and Information Systems, Proceedings",
address = "United States",
}