Name
Abstract | ||
|---|---|---|
In this paper, multiscale principal component analysis (MSPCA) is proposed for multichannel electrocardiogram (MECG) data compression. In wavelet domain, principal components analysis (PCA) of multiscale multivariate matrices of multichannel signals helps reduce dimension and remove redundant information present in signals. The selection of principal components (PCs) is based on average fractional energy contribution of eigenvalue in a data matrix. Multichannel compression is implemented using uniform quantizer and entropy coding of PCA coefficients. The compressed signal quality is evaluated quantitatively using percentage root mean square difference (PRD), and wavelet energy-based diagnostic distortion (WEDD) measures. Using dataset from CSE multilead measurement library, multichannel compression ratio of 5.98:1 is found with PRD value 2.09% and the lowest WEDD value of 4.19%. Based on, gold standard subjective quality measure, the lowest mean opinion score error value of $\\hbox{5.56\\%}$ is found. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/TITB.2012.2195322 | IEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society |
Keywords | Field | DocType |
electrocardiography,average fractional energy contribution,multichannel electrocardiogram (mecg),percentage root mean square difference,multichannel electrocardiogram,multiscale pca,wavelet transforms,pca coefficients,data matrix eigenvalue,dimensional reduction,percentage root mean square difference (prd),mspca,wavelet energy based diagnostic distortion,prd,matrix algebra,data compression,medical signal processing,wedd,wavelet energy-based diagnostic distortion (wedd),redundant information removal,wavelet,compressed signal quality,wavelet domain,uniform quantizer,multichannel signals,mecg data compression,eigenvalues and eigenfunctions,principal component analysis,entropy coding,multiscale multivariate matrices,multiscale principal component analysis (mspca) | Entropy encoding,Pattern recognition,Mean opinion score,Artificial intelligence,Covariance matrix,Quantization (signal processing),Data compression,Principal component analysis,Mathematics,Wavelet,Wavelet transform | Journal |
Volume | Issue | ISSN |
16 | 4 | 1558-0032 |
Citations | PageRank | References |
18 | 1.14 | 12 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| L. N. Sharma | 1 | 118 | 10.04 |
| S. Dandapat | 2 | 261 | 28.51 |
| Anil Mahanta | 3 | 34 | 5.43 |