Modeling of electrocardiogram signals using predefined signature and envelope vector sets
Yükleniyor...
Dosyalar
Tarih
2007
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Hindawi Publishing Corporation
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
A novel method is proposed to model ECG signals by means of "predefined signature and envelope vector sets (PSEVS)." On a frame basis, an ECG signal is reconstructed by multiplying three model parameters, namely, predefined signature vector (PSV)(R)," "predefined envelope vector (PEV)(K)," and frame-scaling coefficient (FSC). All the PSVs and PEVs are labeled and stored in their respective sets to describe the signal in the reconstruction process. In this case, an ECG signal frame is modeled by means of the members of these sets labeled with indices R and K and the frame-scaling coefficient, in the least mean square sense. The proposed method is assessed through the use of percentage root-mean-square difference (PRD) and visual inspection measures. Assessment results reveal that the proposed method provides significant data compression ratio (CR) with low-level PRD values while preserving diagnostic information. This fact significantly reduces the bandwidth of communication in telediagnosis operations. Copyright (c) 2007 Hakan Gurkan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Açıklama
Anahtar Kelimeler
ECG compression, Quantization, Codevectors, Algorithm, Electrocardiography, Data compression, Signal compression, Least squares approximations, Mathematical models, Mean square error, Parameter estimation, Signal reconstruction, Electrocardiogram signals, Envelope vector sets, Frame scaling coefficient (FSC), Model parameters, Signal analysis
Kaynak
EURASIP Journal on Advances in Signal Processing
WoS Q Değeri
Q3
Scopus Q Değeri
Q2
Cilt
2007
Sayı
Künye
Gürkan, H., Güz, Ü. & Yarman, B. S. B. (2007). Modeling of electrocardiogram signals using predefined signature and envelope vector sets. Eurasip Journal on Advances in Signal Processing, 2007, 1-12. doi:10.1155/2007/12071
