System and method to estimate region of tissue activation
A computer-implemented method for determining the volume of activation of neural tissue. In one embodiment, the method uses one or more parametric equations that define a volume of activation, wherein the parameters for the one or more parametric equations are given as a function of an input vector that includes stimulation parameters. After receiving input data that includes values for the stimulation parameters and defining the input vector using the input data, the input vector is applied to the function to obtain the parameters for the one or more parametric equations. The parametric equation is solved to obtain a calculated volume of activation.
1. A system for determining parameters for electrical stimulation, the system comprising:
a memory having stored thereon processor-executable instructions for a volume of tissue activated (VTA) estimator;
a processor coupled to the memory configured to, when executing the processor-executable instructions for the VTA estimator, estimate, for each set of stimulation parameter values input into the VTA estimator, a volume of tissue that is activated by electrical stimulation using the set of stimulation parameter values, wherein the VTA estimator comprises a trained artificial intelligence module to estimate the volume of tissue that is activated by electrical stimulation using the set of stimulation parameter values, wherein the trained artificial intelligence module comprises an artificial neural network;
a user interface coupled to the processor and configured for input of the sets of stimulation parameter values; and
a display coupled to the processor and the user interface and configured for displaying the estimates generated by the VTA estimator.
2. The system of claim 1 , wherein the VTA estimator further comprises a VTA model module.
3. The system of claim 2 , wherein the VTA model module comprising at least one parametric equation model that defines a volume of activation.
4. The system of claim 3 , wherein at least one of the at least one parametric equation model comprises one or more parametric equations that represent a geometric shape.
5. The system of claim 4 , wherein the geometric shape is an ellipsoid shape or a super ellipsoid shape.
6. The system of claim 2 , wherein the VTA model module comprises having an electric field model of an electrode.
7. The system of claim 2 , wherein the VTA model module comprises a neural tissue model.
8. The system of claim 1 , wherein the set of stimulation parameter values comprises a value for each of one or more of pulse width, electrode contact impedance, encapsulation tissue conductivity, voltage, or electrode contact configuration.
9. The system of claim 1 , wherein the memory further comprises processor-executable instructions for a correlator, wherein the processor, when executing the processor-executable instructions for the correlator, is configured for correlating a target volume with the estimates generated by the VTA estimator.
10. The system of claim 9 , wherein the processor, when executing the processor-executable instructions for the correlator, is configured to provide a score indicative of an amount of overlap between the target volume and a one of the estimates generated by the VTA estimator.
11. A non-transitory computer-readable medium having processor-executable instructions for determining electrical stimulation parameters for providing electrical stimulation to a patient, the processor-executable instructions when installed onto a device enable the device to perform actions, the actions comprising:
receiving a target volume;
estimating, for each set of stimulation parameter values, a volume of tissue that is activated by electrical stimulation using the set of stimulation parameter values using a VTA estimator, wherein the VTA estimator comprises a trained artificial intelligence module to estimate the volume of tissue that is activated by electrical stimulation using the set of stimulation parameter values, wherein the trained artificial intelligence module comprises an artificial neural network;
comparing the estimated volumes of tissue with the target volume; and
selecting, based on the comparisons, one of the estimated volumes of tissue and the corresponding set of stimulation parameter values.
12. The computer-readable medium of claim 11 , wherein the VTA estimator further comprises a VTA model module.
13. The computer-readable medium of claim 12 , wherein the VTA model module comprising at least one parametric equation model that defines a volume of activation.
14. The computer-readable medium of claim 13 , wherein at least one of the at least one parametric equation model comprises one or more parametric equations that represent a geometric shape.
15. The computer-readable medium of claim 14 , wherein the geometric shape is an ellipsoid shape or a super ellipsoid shape.
16. The computer-readable medium of claim 12 , wherein the VTA model module comprises having an electric field model of an electrode.
17. The computer-readable medium of claim 12 , wherein the VTA model module comprises a neural tissue model.
18. The computer-readable medium of claim 11 , wherein the set of stimulation parameter values comprises a value for each of one or more of pulse width, electrode contact impedance, encapsulation tissue conductivity, voltage, or electrode contact configuration.