Multivariate approach to QRS detection
We have developed a QRS detection algorithm based on a multivariate model, in which three independent, normalized measures -- amplitude, first difference, and spatial frequency -- are combined in a weighted sum to generate an indicator variable that is then compared to a detection threshold. To increase sensitivity, we first applied and FIR, band-pass filter consisting of a cascaded series of running medians and means. The techniques appears to be exceedingly robust, correctly detecting even aberrant QRS complexes in noise-corrupted ECGs.
Bond, AB; Greco, EC; Bowser, R; Kadri, NN; Sketch, MH
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