A genetic algorithm was successfully used to design optimum linear and nonlinear QRS detectors, minimizing detection errors on the MIT-BIH Arrhythmia Database.
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.
Poli et al. (Sun,) conducted a other in Arrhythmia / ECG signal processing. Genetic algorithm for QRS detector design was evaluated on Detection errors. A genetic algorithm was successfully used to design optimum linear and nonlinear QRS detectors, minimizing detection errors on the MIT-BIH Arrhythmia Database.