Genetic design of optimum linear and nonlinear QRS detectors.
This paper describes an approach to the design of optimum QRS detectors. We report on detectors including a linear or nonlinear polynomial filter, which enhances and rectifies the QRS complex, and a simple, adaptive maxima detector. The parameters of the filter and the detector, and the samples to be processed are selected by a genetic algorithm which minimizes the detection errors made on a set of reference ECG signals. Three different architectures and the experimental results achieved on the MIT-BIH Arrhythmia Database are described.
D000465:Algorithms; D001145:Arrhythmias, Cardiac / Q000175:diagnosis*; D016477:Artifacts; D015982:Bias; D004562:Electrocardiography; D006801:Humans; D016014:Linear Models; D016571:Neural Networks, Computer; D012815:Signal Processing, Computer-Assisted