Systems and methods for administering spinal cord stimulation based on temporal patterns of electrical stimulation

• US 10,232,179 B2
• Filed: 03/13/2014
• Issued: 03/19/2019
• Est. Priority Date: 03/13/2013
• Status: Active Grant

• Current Assignee: Duke University
• Original Assignee: Duke University
• Inventors: Grill, Warren M., Zhang, Tianhe
• Primary Examiner(s): Tejani, Ankit D
• Application Number:
  US14/774,156
• Publication Number:
  US 20160038740A1
• Time in Patent Office: 1,832 Days
• Field of Search: None
• CPC Class Codes: A61N 1/0551 Spinal or peripheral nerve electrodes
• CPC Class Codes: A61N 1/36071 Pain
• CPC Class Codes: A61N 1/36128 Control systems
• CPC Class Codes: A61N 1/36171 Frequency
• CPC Class Codes: A61N 1/36178 Burst or pulse train parameters
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders

Abstract

Systems and methods for administering spinal cord stimulation (SCS) based on temporal patterns of electrical stimulation are disclosed. According to an aspect, a method includes using a computational model of a wide-dynamic range (WDR) neuron to determine one or more non-regular temporal patterns that results in predetermined WDR neuronal output and stimulation activity for one of efficacy optimization and efficiency optimization. The method also includes administering to a subject spinal cord stimulation based on the determined one or more of the non-regular temporal patterns.

Claims

1. A method of identifying an optimized temporal pattern of spinal cord stimulation (SCS), the method comprising:

generating a plurality of non-regular temporal patterns of SCS using an optimization algorithm based on predetermined performance criteria;

evaluating the plurality of non-regular temporal patterns of SCS for efficacy optimization using a firing rate or a firing pattern of at least one model neuron within a computational model representing a network of spinal neurons and effects of SCS on the spinal neurons;

evaluating the plurality of non-regular temporal patterns of SCS for efficiency optimization using average stimulation frequency; and

identifying at least one candidate non-regular temporal pattern of SCS that results in an optimized firing rate or firing pattern of model neuron activity for efficacy optimization and an optimized stimulation frequency for efficiency optimization.

2. The method of claim 1, wherein identifying the at least one candidate non-regular temporal pattern of SCS comprises selecting the identifying the at least one candidate non-regular temporal pattern of SCS from among other patterns for one of minimizing firing rate of model neuron activity for efficacy optimization and minimizing average stimulation frequency for efficiency optimization.

3. The method of claim 1, comprising using an output of the computational model of a wide dynamic range (WDR) neuron as a measure of model spinal neuron firing rate or firing pattern for efficacy optimization.

4. The method of claim 1, comprising using spinal cord stimulation (SCS) stimulation frequency in the computational model as a proxy for the optimized stimulation frequency for efficiency optimization.

5. The method of claim 4, further comprising generating a cost function for identifying the at least one candidate non-regular temporal pattern of SCS.

6. The method of claim 1, wherein identifying the at least one candidate non-regular temporal pattern of SCS comprises using a search heuristic to determine the at least one candidate non-regular temporal pattern of SCS that results in the optimized firing rate or firing pattern of model neuron activity for efficacy optimization and an optimized stimulation frequency for efficiency optimization.

7. The method of claim 6, wherein using the search heuristic comprises using one of a genetic algorithm, a gradient descent, and a simulated annealing technique.

8. The method of claim 1, wherein the spinal neurons of the computational model comprise wide dynamic range (WDR) neurons.

9. The method of claim 1, further comprising administering to a subject the identified at least one candidate non-regular pattern of SCS.

10. The method of claim 9, wherein administering to a subject comprises applying the identified at least one non-regular temporal pattern to a targeted neurological tissue region of the subject.

11. The method of claim 10, wherein administering to a subject comprises placing at least one electrode in electrical communication with the targeted neurological tissue region for application of the identified at least one candidate non-regular temporal pattern of SCS.

12. The method of claim 10, wherein applying the identified at least one non-regular temporal pattern comprises applying the identified at least one non-regular temporal pattern to at least one sub-population of dorsal column nerve fibers, dorsal roots, dorsal root ganglia, or a peripheral nerve of the subject.

13. The method of claim 10, wherein identifying the at least one candidate non-regular temporal pattern of SCS comprises:

generating a cost function for optimizing spinal neuron firing rate or firing pattern and stimulating output frequency;

tuning the cost function for a pre-determined or patient-specific balance of optimized firing rate or firing pattern of model neuron activity for efficacy optimization and an optimized stimulation frequency for efficiency optimization; and

selecting the at least one candidate non-regular temporal pattern of SCS based on the cost function.

14. The method of claim 13, further comprising:

altering the applied non-regular temporal patterns;

determining when a threshold value for the cost function is obtained while altering the applied non-regular temporal patterns; and

determining that the non-regular temporal pattern applied when the threshold value is obtained is the one or more of the non-regular temporal patterns that results in the optimized firing rate or firing pattern of model neuron activity for efficacy optimization and an optimized stimulation frequency for efficiency optimization.

15. A system of identifying an optimized temporal pattern of spinal cord stimulation (SCS), the system comprising:

at least one processor and memory configured to;

generate a plurality of non-regular temporal patterns of SCS using an optimization algorithm based on predetermined performance criteria;

evaluate the plurality of non-regular temporal patterns of SCS for efficacy optimization using a firing rate or a firing pattern of at least one model neuron within a computational model representing a network of spinal neurons and effects of SCS on the spinal neurons;

evaluate the plurality of non-regular temporal patterns of SCS for efficiency optimization using average stimulation frequency; and

identify at least one candidate non-regular temporal pattern of SCS that results in an optimized firing rate or firing pattern of model neuron activity for efficacy optimization and an optimized stimulation frequency for efficiency optimization.

16. The system of claim 15, further comprising at least one electrode in electrical communication with a targeted neurological tissue region for application of the identified at least one candidate non-regular temporal pattern of SCS.

17. The system of claim 15, wherein the at least one processor and memory are configured to:

generate a cost function for optimizing a firing rate or a firing pattern of model neuron activity for efficacy optimization and an optimized stimulation frequency for efficiency optimization;

tune the cost function for a pre-determined or patient-specific balance of firing rate or firing pattern of model neuron activity for efficacy optimization and an optimized stimulation frequency for efficiency optimization; and

select the at least one candidate non-regular temporal pattern of SCS based on the cost function.

18. The system of claim 17, wherein the at least one processor and memory are configured to:

alter the applied non-regular temporal patterns;

determine when a threshold value for the cost function is obtained while altering the applied temporal patterns; and

determine that the temporal pattern applied when the threshold value is obtained is the one or more of the non-regular temporal patterns that results in the optimized firing rate or firing pattern of model neuron activity for efficacy optimization and an optimized stimulation frequency for efficiency optimization.

19. The system of claim 15, wherein the at least one processor and memory are configured to use an output of the computational model of a wide dynamic range (WDR) neuron as a measure of the optimized firing rate or firing pattern of model neuron activity for efficacy optimization.

20. The system of claim 15, wherein the at least one processor and memory are configured to use spinal cord stimulation (SCS) stimulation frequency in the computational model as a proxy for the optimized stimulation frequency for efficiency optimization.

21. The system of claim 20, wherein the at least one processor and memory are configured to generate a cost function for selection of the identified at least one candidate non-regular temporal pattern of SCS.

22. The system of claim 15, wherein the at least one processor and memory are configured to use a search heuristic to determine the at least one candidate non-regular temporal pattern of SCS that results in the optimized firing rate or firing pattern of model neuron activity for efficacy optimization and an optimized stimulation frequency for efficiency optimization.

23. The system of claim 22, wherein the search heuristic comprises one of a genetic algorithm, a gradient descent, and a simulated annealing technique.

24. The system of claim 15, wherein the at least one processor and memory are configured to control a pulse generator and one or more electrodes to administer to a subject spinal cord stimulation based on the identified at least one candidate non-regular temporal pattern of SCS.

25. The system of claim 24, further comprising a spinal cord stimulation (SCS) device configured to control the pulse generator and the one or more electrodes to apply the at least one candidate non-regular temporal pattern of SCS to a targeted neurological tissue region of a subject.

26. The system of claim 25, wherein the SCS device is configured to apply the identified at least one candidate non-regular temporal pattern of SCS to at least one sub-population of dorsal column nerve fibers, dorsal roots, dorsal root ganglia, or a peripheral nerve of the subject.