# Rotor Location During Atrial Fibrillation: A Framework Based on Data Fusion and Information Quality
## 2 Materials and Methods
### Proposed JDL-Based Framework  
Figure 6 illustrates the proposed JDL-based framework, which was originally expanded to six levels by [28] and adapted for identifying and evaluating potential ablation zones using EGMs derived from rotor simulations under AF conditions. The levels of the JDL model are specified as follows:  
1. Level 0: The EGM signals are normalized to the interval [\(-\)1, 1], and wavelet filtering is performed to eliminate the PLI noise. Spikes and lost samples are identified, and these samples are approximated using the inverse distance-weighted algorithm, considering the spatially closest signals. Missing signals are approximated using the same algorithm by considering all known EGMs. 2. Level 1: The association, extraction, and selection of EGM features are carried out. The resulting features are used to generate maps of the tissue, aiming to pinpoint the rotor location. Signal fusion is achieved using particle filters to obtain a signal with reduced uncertainty due to noise. This step should be implemented when multiple signals of the same target are available. Feature extraction is performed using the ApEn, SampEn, ShEn, mean, and STD to construct the maps. The resulting maps are merged using the wavelet fusion technique, applied to a pair of images selected based on IQ maximization through an optimization process. In this work, the particle swarm optimization (PSO) algorithm was adopted due to its demonstrated generality and effectiveness in non-linear optimization problems [45]. 3. Level 2 and level 3: Expert knowledge is expected to be emulated through the processes at these levels, such as case-based reasoning or fuzzy inference systems. The outcomes aim to assess situations, risks, vulnerabilities, and opportunities by considering the information on the rotor tip location and the IQ. Level 2: The situation is assessed based on the IQ of the merged map, considering the rotor tip location as a target. Several fuzzy inference systems (FISs) were designed to  
Figure 5: Maps of the statistical features computed from the 22,500 noise-free EGMs correspond to a rotor simulation in the 2D atrial model. (**a**) SampEn, (**b**) ApEn, (**c**) mean, (**d**) STD, and (**e**) ShEn. The color scale depicts the normalized values of statistical estimates. Figure 6: Proposed JDL-based framework adapted to determine the ablation zone (rotor tip) using EGMs. The six levels of the JDL model are specified. HCI stands for human-computer interaction. analyze the effect of different IQ levels due to the erroneous reasoning of the experts represented in this model. The determination of the rotor tip location is guided by expert-established rules based on experience, which is implemented in a FIS. This system correlates information gathered from previous levels and IQ assessments to identify specific situations. In this work, we propose \(n\) situations based on the available information and the IQ, as follows:  
\[\text{Rule }(1):\] If \[IQ_{1}\] is \[A_{1}\] AND \[IQ_{2}\] is \[B_{1}\] AND \[IQ_{3}\] is \[C_{1}\] THEN Situation is \[D_{x}\] Rule Figure 6:0 If Figure 6:1 is Figure 6:2 AND Figure 6:3 is Figure 6:4 AND Figure 6:5 is Figure 6:6 THEN Situation is Figure 6:7  
where \(IQ_{1}\), \(IQ_{2}\), and \(IQ_{3}\) refer to the accuracy, precision, and interpretability of the merged maps, respectively. Accuracy is the proportion of correct predictions made by a model relative to the total number of predictions. Precision measures how accurately the model identifies the positive class, i.e., the proportion of the positive predictions belongs to the positive class. Interpretability refers to the extent to which users or researchers can understand and explain the decisions or predictions of the model. \(A_{n}\), \(B_{m}\), and \(C_{p}\) correspond to the output fuzzy sets. \(D_{x}\) corresponds to the output fuzzy sets. Level 3: At this stage, the same procedure is adopted as in level 2, but it is applied to risk/impact assessment.