Abstract
A method for suppression of electromyogram (EMG) interference in electrocardiogram (ECG) recordings is presented. By assuming that the EMG is long-term non-stationary Gaussian noise, two successive decompositions were proposed, and the data transformed for Wiener filtering. Successive ECG cycles were rearranged and aligned by the R-wave, forming a matrix containing separated heart cycles in its rows. A short-window discrete cosine transform (DCT) was applied to the columns of the matrix for inter-cycle de-correlation. Next, Weiner filtering in a translation-invariant wavelet domain was performed on the DCT-transformed matrix rows for de-correlation of the data into each ECG cycle. The method resulted in an improvement in the signal-to-noise ratio of more than 10 db, a threefold reduction in mean relative amplitude errors and reduced ripple artifacts around the signal transients, thus preserving the waveform in diagnostically important signal segments.
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Nikolaev, N., Gotchev, A., Egiazarian, K. et al. Suppression of electromyogram interference on the electrocardiogram by transform domain denoising. Med. Biol. Eng. Comput. 39, 649–655 (2001). https://doi.org/10.1007/BF02345437
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DOI: https://doi.org/10.1007/BF02345437