be used to determine the circuit’s location. This means that the electrograms can be measured at a lower resolution as no one measurement is critical to the success of the locating algorithm. Sample electrograms from the CMP model can be seen in Fig. \[fig:comparisonECG\]. These are generated as outlined in appendix \[sec:ap1\].

For the purpose of recording training data to build the machine learning models, a 9 electrode probe used, arranged in a $3 \times 3$ array. This represents the multi-contact mapping catheters used for ablation. The $3 \times 3$ probes are distributed uniformly in a $9 \times 9$ cell grid of the CMP tissue as seen in Fig. \[fig:elecgrid\]. The distance between each probe and its nearest neighbors is 3 cells as this gives a resolution comparable to clinically used ablation mapping catheters. We define the probe to be on the re-entrant circuit if any part of the re-entrant circuit is within the multiprobe’s $9 \times 9$ cell region.

A first look at the electrograms shows clear distinctions depending on the electrodes relative position from the re-entrant circuit as shown in Fig. \[fig:comparisonECG\] (b). Features gathered from these individual electrodes include: maximum voltage, minimum voltage, first stationary point position, 