Detection of slow electrical conduction areas is crucial for providing an effective ablation therapy in ventricular tachycardia. To this aim local activations and their duration should be accurately identified. Currently mapping systems identify the precocity or lateness of a local activation with respect to a fixed reference without considering its duration. In this study we developed an automatic approach to compute local activation durations from electrograms (EGMs) and electrographic signals (ECGs). EGMs were acquired during both sinus rhythm and ventricular tachycardia with a commercial mapping catheter (Abbott Advisor HD Grid) in six patients. EGMs were band-pass filtered before processing and the analysis was based on the EGMs histogram and similarity techniques, only when a repeatable rhythm was detected in the ECGs the proposed approach was validated against 2846 activations manually annotated (GS) by an expert electrophysiologist. The mean error in the computation of the activation durations over each signal for each patient was -0.1±1.8ms (GS activation duration: 54.4±9.3ms). The developed algorithm is accurate, and the 3D dynamic maps showing slow electrical conduction areas may represent a useful tool to be integrated with activation and voltage maps to plan and assist therapeutic interventions in ventricular arrhythmias.