Systems and methods for VOA model generation and use
First Claim
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1. A computer-implemented method, comprising:
- obtaining, by a computer processor, electric field data corresponding to settings of a non-cylindrically symmetrical implanted leadwire that is adapted for stimulating anatomical tissue, the electric field data including for each of a plurality of neural elements a respective plurality of electric values for a same electric field parameter;
determining in a first determining step, by the processor and for each of the neural elements, a respective activation status based on the respective plurality of electric values associated with the respective neural element; and
the processor determining in a second determining step, and outputting an indication of, an estimated activated tissue region corresponding to a combination of points surrounding the leadwire corresponding to those of the neural elements for which an active status is determined;
wherein the determining of the second determining step is performed by executing a first module that at least one of;
does not base the determining of the second determining step on input of different sets of values of an electric field at different points in time;
does not use more than one differential equation;
oris generated based on observed functioning of a second module that uses differential equations, wherein the first module uses only linear equations.
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Abstract
A computer implemented system and method provides a volume of activation (VOA) estimation model that receives as input two or more electric field values of a same or different data type at respective two or more positions of a neural element and determines based on such input an activation status of the neural element. A computer implemented system and method provides a machine learning system that automatically generates a computationally inexpensive VOA estimation model based on output of a computationally expensive system.
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Citations
25 Claims
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1. A computer-implemented method, comprising:
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obtaining, by a computer processor, electric field data corresponding to settings of a non-cylindrically symmetrical implanted leadwire that is adapted for stimulating anatomical tissue, the electric field data including for each of a plurality of neural elements a respective plurality of electric values for a same electric field parameter; determining in a first determining step, by the processor and for each of the neural elements, a respective activation status based on the respective plurality of electric values associated with the respective neural element; and the processor determining in a second determining step, and outputting an indication of, an estimated activated tissue region corresponding to a combination of points surrounding the leadwire corresponding to those of the neural elements for which an active status is determined; wherein the determining of the second determining step is performed by executing a first module that at least one of; does not base the determining of the second determining step on input of different sets of values of an electric field at different points in time; does not use more than one differential equation;
oris generated based on observed functioning of a second module that uses differential equations, wherein the first module uses only linear equations. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A computer-implemented method, comprising:
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responsive to receipt of user input settings of an implanted leadwire that is adapted for stimulating anatomical tissue, wherein the implanted leadwire is non-cylindrically symmetrical; determining in a first determining step, by a computer processor, electric field data corresponding to the user input settings, the electric field data including for each of a plurality of neural elements a respective plurality of electric values for a same electric field parameter; determining in a second determining step, by the processor and for each of the neural elements, a respective activation status based on the respective plurality of electric values associated with the respective neural element; determining in a third determining step, by the processor, an estimated activated tissue region corresponding to a combination of points surrounding the leadwire corresponding to those of the neural elements for which an active status is determined; and generating and displaying, by the processor, a graphical representation of a volume relative to at least one of a graphical representation of the leadwire and a graphical representation of anatomical structures, the volume corresponding to, and being based on, the estimated activated tissue region, wherein one or more of the determining in the second determining step or the determining in the third determining step is performed by executing a first module that at least one of; does not base the one or more of the determining in the second determining step or the determining in the third determining step on input of different sets of values of an electric field at different points in time; does not use more than one differential equation;
oris generated based on observed functioning of a second module that uses differential equations, wherein the first module uses only linear equations.
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10. A computer-implemented method, comprising:
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obtaining, by a computer processor executing a machine learning module, output data of a first module that determines an activation status for each of a plurality of neural elements based on input characterizing stimulation settings of one or more non-cylindrically symmetrical implanted leadwires adapted for stimulating anatomical tissue; obtaining, by the processor executing the machine learning module, at least a portion of the input processed by the first module to produce the obtained output data; analyzing, by the processor executing the machine learning module, the obtained output data and input; and based on the analysis, automatically generating, by the processor executing the machine learning module, at least one second module that determines an activation status for each of a plurality of neural elements based on input that (a) is different than the input and (b) characterizes stimulation settings of one or more non-cylindrically symmetrical implanted leadwires adapted for stimulating anatomical tissue. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23)
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24. A computer-implemented method, comprising:
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obtaining, by a computer processor, electric field data corresponding to settings of non-cylindrically symmetrical implanted leadwire that is adapted for stimulating anatomical tissue, the electric field data including for each of a plurality of neural elements a respective plurality of electric values for a same electric field parameter; and determining and outputting, by the processor and for each of the neural elements, a respective activation threshold based on the respective plurality of electric values associated with the respective neural element; wherein the determining is performed by executing a first module that at least one of; does not base the determining on input of different sets of values of an electric field at different points in time; does not use more than one differential equation;
oris generated based on observed functioning of a second module that uses differential equations, wherein the first module uses only linear equations.
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25. A computer-implemented method, comprising:
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obtaining, by a computer processor executing a machine learning module, output data of a first module that determines an activation threshold for each of a plurality of neural elements based on input characterizing stimulation settings of one or more non-cylindrically symmetrical implanted leadwires adapted for stimulating anatomical tissue; obtaining, by the processor executing the machine learning module, at least a portion of the input processed by the first module to produce the obtained output; analyzing, by the processor executing the machine learning module, the obtained output data and input; and based on the analysis, automatically generating, by the processor executing the machine learning module, at least one second module that determines an activation threshold for each of a plurality of neural elements based on input that (a) is different than the input and (b) characterizes stimulation settings of one or more non-cylindrically symmetrical implanted leadwires adapted for stimulating anatomical tissue.
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Specification