The ventricular response during atrial fibrillation (AF) presents particular characteristics that may play a relevant role in the selection of the most appropriate treatment. Using different ECG signal processing techniques such as RR histogram analysis or histographic Poincaré plots (PPs) (so-called 3-D PPs), clusters of RR intervals due to preferential atrioventricular (AV) node conduction can be observed. However, these methods are limited by the need for visual inspection and subjective interpretation of analysis results. The objective of this paper is to develop a method to automatically detect and quantify preferential clusters of RR intervals. This novel method, the Poincaré surface profile (PSP), uses the information of histographic PPs to filter part of the AV node memory effects. PSP detected all RR populations present in RR interval histograms in 55 patients with persistent AF and also 67% additional RR populations. In addition, a reduction of beat-to-beat dependencies allowed a more accurate location of RR populations. This novel Poincaré-plot-based analysis also allows monitoring of short-term variations of preferential conductions. We illustrate the capability of this short-time monitoring technique to evaluate the effects of rate control drugs on each preferential conduction.