Nonolinear Transforms In Qrs Detection Algorithms
A nonlinear transform is typically used in a QRS detection algorithm to estimate the signal energy. In this study five different nonlinear transforms on the derivative of the ECG signal are evaluated. These transforms include squaring, 2-point multiplication, 2-point multiplication with sign consistency, 3-point multiplication, and 3-point multiplication with sign consistency. The AHA ECG data base is used to test the algorithms. We have found that the 3-point multiplication enhances the QRS complex most, and the sign consistency constraint is useful in rejecting abrupt transitions such as the pacer spikes. old is used in the decision stage as previously described [3]. The adaptive threshold is used to increase the sensitivity of QRS detection as the elapsed time from the last QRS increases. Let 2, denote the 1st-order backward difference for the current ECG sample, and yn denote the output from the nonlinear transform. The five nonlinear transforms under investigation are, respectively, defined as follows: