Suppression of electromyogram interference on the electrocardiogram by transform domain denoising.
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, Wiener 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.
Nikolaev
N
N
Institute of Information Technologies, Bulgarian Academy of Sciences, Finland.
Gotchev
A
A
Egiazarian
K
K
Nikolov
Z
Z
D016477:Artifacts; D004562:Electrocardiography / Q000379:methods*; D004576:Electromyography; D006801:Humans; D012815:Signal Processing, Computer-Assisted