Paper Info
Title
A new multilead ECG data compression method using Higher-Order Singular Value Decomposition
Abstract
In this paper, a new compression method based on Higher-Order Singular Value Decomposition (HOSVD) for multilead electrocardiogram (MECG) data is proposed. This method exploits intra-beat and inter-beat correlation present due to quasi-periodic nature of ECG, and inter-lead correlation present among different leads of MECG data as well. The MECG data is used to form a 3-array tensor after R-peak detection and period normalization. Then, DWT is applied to the 3-array tensor for better compression. The singular values corresponding to high frequency subbands are selected on basis of singular value ratio (SVR). The MECG data is taken from the PTB Diagnostic ECG database for evaluation of the proposed method. Simulations show that there are significant improvements in compression ratio (CR) compared to existing ECG compression methods available in the literature. Compression performance and quality of the compressed MECG data of our proposed method is assessed using CR and Percentage Root Mean Square Difference (PRD). For comparison purpose, HOSVD is directly applied to the 3-array tensor data without performing DWT.
Year
DOI
Venue
2014
10.1109/NCC.2014.6811355
NCC
Keywords
Field
DocType
data compression,electrocardiography,mean square error methods,medical signal processing,singular value decomposition,ecg compression methods,hosvd,mecg data,prd,ptb diagnostic ecg database,svr,compression ratio,frequency subbands,higher order singular value decomposition,inter beat correlation,intra beat correlation,multilead ecg data compression method,multilead electrocardiogram,percentage root mean square difference,3-array mecg,dwt,higher-order svd (hosvd),multilead electrocardiogram (mecg),singular value decomposition (svd)
Singular value decomposition,Normalization (statistics),Singular value,Tensor,Pattern recognition,Speech recognition,Compression ratio,Artificial intelligence,Root mean square,Higher-order singular value decomposition,Data compression,Mathematics
Conference
Citations 
PageRank 
References 
0
0.34
9
Authors
2
Name
Order
Citations
PageRank
Padhy, S.1163.29
S. Dandapat226128.51