22 Guaranteeing Target Quality Denoising of Multichannel ECG Signals Using MSPCA

In this work, denoising of multichannel electrocardiogram (MECG) signals is proposed by applying multiscale principal component analysis (MSPCA). The desired quality of processed signals is achieved by selecting the principal components (PC) based on energy features in selected wavelet subband matrices. The number of PC selection, to achieve the target quality of denoised signals, is based on cumulative percentage of total variation of variances. The choice of multiscale matrices and selection of eigenvalues preserve the target energy in the processed signals. Input and output signal-to-noise ratio (SNR) is measured for quantitative performance. Signal distortion measures are evaluated using percentage root mean square difference (PRD) and wavelet energy based diagnostic distortion measure (WEDD). SNR improvement of 31.12 dB has been found with better denoising effect using database of CSE multilead measurement library.