Data processing of stress ECGs using discrete cosine transform

The signal processing steps for the analysis of stress ECGs are aimed at im proving the signal to noise ratio (SNR) of recordings in addition to elimin ating artifacts due to respiration, movement of arms, etc. In this paper, w e bring forth two important applications of the discrete cosine transform ( DCT) for noise suppression and removal of baseline wander. The noise suppre ssion algorithm has been framed on the basis of a two step procedure involv ing singular value decomposition (SVD) smoothing operation in transform dom ain followed by that in time domain. The mean square error (MSE) resulting from the first step is shown to effectively follow the trend obtained by us ing an ideal Wiener filter using DCT. In the second step, the degree of clo seness to the minimum mean square error (MMSE) of the ideal Wiener filter i s improved by subjecting the filtered outputs to a second SVD smoothing ope ration in rime domain. Application of this scheme to noisy records has resu lted in near perfect reproduction of the original noise free ECG without si gnificant alterations in its morphological features. (C) 1998 Elsevier Scie nce Ltd. All rights reserved.