Method and system for atrial fibrillation analysis, characterization, and mapping

1. A method comprising:

generating a finite element model (FEM) representing a physical structure of a heart,

said FEM comprising a plurality of elements each corresponding to a location in the heart;

sensing electrogram data at a plurality of location in the heart;

mapping said electrogram data for each of said plurality of locations to a corresponding one of said plurality of elements of said FEM;

concurrently calculating at least one functional parameter for each said plurality of elements of said FEM based on electrogram data mapped to the elements;

assigning an ablation priority based on the said functional parameter to individual element of said FEM enabling identification of a priority order of ablation and localization of tissue to be ablated in response to the sensed electrogram data.

2. The method of claim 1 , further comprising:

using an artificial neural network in localizing cardiac arrhythmia positions in a heart indicating a priority order of ablation and location of tissue.

3. The method of claim 2 , further comprising:

generating at least one FEM function map image showing said at least one function parameter for each of said plurality of elements and wherein

the step of assigning an ablation priority comprises assigning an ablation priority in response to detected Atrial Fibrillation energy of locations of said FEM.

4. The method of claim 3 , further comprising:

displaying said FEM function map image; and

updating said FEM function map image in real time based on change in the electrogram data mapped to each of the plurality of elements of said FEM.

5. The method of claim 2 , wherein said step of simultaneously calculating at least one function parameter for each of said plurality of elements of said FEM comprises:

applying at least one signal processing analysis to the electrogram data mapped to each of said plurality of elements of said FEM.

6. The method of claim 2 , wherein said at least one function parameter comprises at least one of AF energy, excitation time, dominant frequency, energy level, and arrhythmia priority.

7. The method of claim 2 , wherein the step of concurrently calculating at least one function parameter for each of said plurality of elements of said FEM comprises:

calculating said at least one function parameter for each of said plurality of elements of said FEM using an artificial neural network (ANN) which receives the electrogram data mapped to each of the plurality of elements of said FEM as input.

8. The method of claim 7 , wherein said ANN receives patient data and physical measurement data as input, and said step of calculating said at least one function parameter for each of said plurality of elements of said FEM using an ANN comprises:

calculating said at least one function parameter for each of said plurality of elements of said FEM based on the electrogram data, the patient data, and the physical measurement data using said ANN.

9. The method of claim 2 , wherein said at least one function parameter comprises an ablation location function parameter, which indicates, for each of said plurality of elements of said FEM, whether the corresponding location in the heart needs ablation.

10. The method of claim 2 , wherein said at least one function parameter comprises and ablation priority function parameter, which determines, for each of said plurality of elements of said FEM, a priority for ablation.

11. The method of claim 1 , further comprising:

displaying an FEM function map showing the electrogram data mapped to the plurality of elements of the FEM.

12. An apparatus comprising:

means for generating a finite element model (FEM) representing a physical structure of a heart, said FEM comprising a plurality of elements each corresponding to a location in the heart;

means for sensing electrogram data at a plurality of locations in the heart to correspond to one of said plurality of elements of said FEM;

means for concurrently calculating at least one functional parameter for each of said plurality of elements of said FEM based on electrogram data mapped to the element; and

means for assigning an ablation priority to individual elements of said FEM enabling identification of priority order of ablation and location of tissue to be ablated in response to sensed electrogram data.

13. The method of claim 12 , further comprising:

using an artificial neural network in localizing cardiac arrhythmia positions in a heart indicating a priority order of ablation and location of tissue.

14. The apparatus of claim 13 , further comprising:

means for displaying an FEM function map image showing said at least one function parameter for each of said plurality of elements;

means for updating said FEM function map image in real time based on change in the electrogram data mapped to each of the plurality of elements of said FEM; and wherein

the means for assigning an ablation priority assigns an ablation priority in response to detected Atrial Fibrillation energy of locations of said FEM.

15. The apparatus of claim 13 , wherein said means for simultaneously calculating at least one function parameter for each of said plurality of elements of said FEM comprises:

means for applying at least one signal processing analysis to the electrogram data mapped to each of said plurality of elements of said FEM.

16. The apparatus of claim 13 , wherein said means for simultaneously calculating at least one function parameter for each of said plurality of elements of said FEM comprises:

means for executing an artificial neural network (ANN) configured to calculate said at least one function parameter for each of said plurality of elements of said FEM based on the electrogram data mapped to the element.

17. The apparatus of claim 16 , wherein said ANN receives the electrogram data, patient data, and physical measurement data as input, and said ANN is configured to calculate said at least one function parameter for each of said plurality of elements of said FEM based on the electrogram data, the patient data, and the physical measurement data.

18. The apparatus of claim 13 , wherein said at least one function parameter comprises an ablation location function parameter, which indicates, for each of said plurality of elements of said FEM, whether the corresponding location in the heart needs ablation.

19. The apparatus of claim 13 , wherein said at least one function parameter comprises and ablation priority function parameter, which determines, for each of said plurality of elements of said FEM, a priority for ablation.

20. The apparatus of claim 12 , further comprising:

means for displaying an FEM function map showing the electrogram data mapped to the plurality of elements of the FEM.

21. The apparatus of claim 12 , wherein said means for sensing electrogram data comprises and electrophysiology catheter.

22. A non-transitory computer readable medium encoded with computer executable instructions, the computer instructions defining steps comprising:

generating a finite element model (FEM) representing a physical structure of a heart, said FEM comprising a plurality of elements each corresponding to a location in the heart;

receiving electrogram data sensed at a plurality of locations in the heart;

mapping said electrogram data from each of said plurality of location to a corresponding one of said plurality of elements of said FEM;

assigning an ablation priority to individual elements of said FEM enabling identification of a priority order of ablation and location of tissue to be ablated in response to the sensed electrogram data,

concurrently calculating at lease one functional parameter for each of said plurality of elements of said FEM based on electrogram data mapped to the elements; and

identifying individual elements of said FEM for ablation and location of tissue to be ablated in response to determined Atrial Fibrillation energy locations of said FEM derived from the sensed electrogram data.

23. The computer readable medium of claim 22 , further comprising computer executable instructions defining the steps of:

using an artificial neural network for localizing cardiac arrhythmia positions in a heart indicating a priority order of ablation and location of tissue.

24. The computer readable medium of claim 23 , further comprising computer executable instructions defining the steps of:

displaying an FEM function map image showing said at least one function parameter for each of said plurality of elements;

updating said FEM function map image in real time based on change in the electrogram data mapped to each of the plurality of elements of said FEM; and

assigning an ablation priority in response to detected Atrial Fibrillation energy of locations of said FEM.

25. The computer readable medium of claim 23 , wherein the computer executable instructions defining the step of simultaneously calculating at least one function parameter for each of said plurality of elements of said FEM comprise computer executable instructions defining the steps of:

executing an artificial neural network (ANN) configured to calculate said at least one function parameter for each of said plurality of elements of said FEM based on the electrogram data mapped to the element.

26. The computer readable medium of claim 25 , wherein said ANN receives the electrogram data, patient data, and physical measurement data as input, and said ANN is configured to calculate said at least one function parameter for each of said plurality of elements of said FEM based on the electrogram data, the patient data, and the physical measurement data.

27. The computer readable medium of claim 23 , wherein said at least one function parameter comprises an ablation location function parameter, which indicates, for each of said plurality of elements of said FEM, whether the corresponding location in the heart needs ablation.

28. The computer readable medium of claim 23 , wherein said at least one function parameter comprises and ablation priority function parameter, which determines, for each of said plurality of elements of said FEM, a priority for ablation.

29. The computer readable medium of claim 22 , further comprising computer executable instructions defining the step of:

displaying an FEM function map showing the electrogram data mapped to the plurality of elements of the FEM.