Some important R-R interval based paroxysmal atrial fibrillation predictors

A trial fibrillation is the most common sustained cardiac arrhythmia. The result of series of machine learning experiments is detection of some promising paroxysmal atrial fibrillation predictors. Based on ratio of short and long R-R intervals there is a possibility to generate rules for PAF screening and predicting. For PAF screening the calculated ratio were 2.00 for successive R-R intervals. The problem of imminent PAF prediction is much more difficult and the concept of normalisation hail to be implemented. The optimal seems to be ratio between the shortest and the longest R-R interval, which was at least 1.75 times larger than ratio during the normalisation time for the same patient. Also it was detected that maximal distance of the longest and the shortest R-R intervals should be up to six R-R intervals.