Title :
A Novel ECG Data Compression Method Using Adaptive Fourier Decomposition With Security Guarantee in e-Health Applications
Author :
JiaLi Ma ; TanTan Zhang ; MingChui Dong
Author_Institution :
Electr. & Comput. Eng. Dept., Univ. of Macau, Macau, China
fDate :
5/1/2015 12:00:00 AM
Abstract :
This paper presents a novel electrocardiogram (ECG) compression method for e-health applications by adapting an adaptive Fourier decomposition (AFD) algorithm hybridized with a symbol substitution (SS) technique. The compression consists of two stages: first stage AFD executes efficient lossy compression with high fidelity; second stage SS performs lossless compression enhancement and built-in data encryption, which is pivotal for e-health. Validated with 48 ECG records from MIT-BIH arrhythmia benchmark database, the proposed method achieves averaged compression ratio (CR) of 17.6-44.5 and percentage root mean square difference (PRD) of 0.8-2.0% with a highly linear and robust PRD-CR relationship, pushing forward the compression performance to an unexploited region. As such, this paper provides an attractive candidate of ECG compression method for pervasive e-health applications.
Keywords :
Fourier analysis; data compression; electrocardiography; medical signal processing; security of data; AFD algorithm; ECG data compression; ECG records; MIT-BIH arrhythmia benchmark database; PRD-CR relationship; SS technique; adaptive Fourier decomposition; built-in data encryption; compression ratio; electrocardiogram compression method; fore-health applications; information security; lossless compression enhancement; percentage root mean square difference; symbol substitution technique; Benchmark testing; Electrocardiography; Encoding; Encryption; Informatics; Information security; Transforms; Adaptive Fourier decomposition (AFD); data encryption; e-health; electrocardiogram (ECG) compression; information security;
Journal_Title :
Biomedical and Health Informatics, IEEE Journal of
DOI :
10.1109/JBHI.2014.2357841
