Therapy program modification based on a therapy field model

• US 9,789,252 B2
• Filed: 01/22/2009
• Issued: 10/17/2017
• Est. Priority Date: 04/29/2008
• Status: Active Grant

• Current Assignee: Medtronic Incorporated (Medtronic Plc)
• Original Assignee: Medtronic Incorporated (Medtronic Plc)
• Inventors: Gerber, Martin T., Rondoni, John C.
• Primary Examiner(s): MALAMUD, DEBORAH LESLIE
• Application Number:
  US12/989,754
• Publication Number:
  US 20110208012A1
• Time in Patent Office: 3,190 Days
• Field of Search: 607 1- 2, 607 59, 607 62, 607 66, 607115, 600300-301, 600512
• CPC Class Codes: A61M 2205/054 with electrotherapy
• CPC Class Codes: A61M 2210/0693 Brain, cerebrum
• CPC Class Codes: A61M 5/14276 specially adapted for implantation
• CPC Class Codes: A61M 5/1723 using feedback of body parameters, e.g. blood-sugar, pressure measurement of body parameters A61B5/00
• CPC Class Codes: A61N 1/36003 of motor muscles, e.g. for walking assistance
• CPC Class Codes: A61N 1/36007 of urogenital or gastrointestinal organs, e.g. for incontinence control
• CPC Class Codes: A61N 1/36034 specified by the stimulation parameters
• CPC Class Codes: A61N 1/36071 Pain
• CPC Class Codes: A61N 1/36082 Cognitive or psychiatric applications, e.g. dementia or Alzheimer's disease
• CPC Class Codes: A61N 1/36185 Selection of the electrode configuration
• CPC Class Codes: A61N 1/37235 Aspects of the external programmer
• CPC Class Codes: A61N 1/37247 User interfaces, e.g. input or presentation means
• CPC Class Codes: A61N 1/37264 Changing the program; Upgrading firmware
• CPC Class Codes: G16H 20/10 relating to drugs or medications, e.g. for ensuring correct administration to patients
• CPC Class Codes: G16H 20/30 relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 40/20 for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders

Abstract

Techniques for modeling therapy fields for therapy delivered by medical devices are described. Each therapy field model is based on a set of therapy parameters and represents where therapy will propagate from the therapy system delivering therapy according to the set of therapy parameters. Therapy field models may be useful in guiding the modification of therapy parameters. As one example, a processor compares an algorithmic model of a therapy field to a reference therapy field and adjusts at least one therapy parameter based on the comparison. As another example, a processor adjusts at least one therapy parameter to increase an operating efficiency of the therapy system while substantially maintaining the modeled therapy field.

Claims

1. A method comprising:

determining, by a processor, a first therapy program that comprises a set of therapy parameters values;

generating, by the processor, an algorithmic model of a therapy field based on the first therapy program, the algorithmic model representing where therapy will propagate from a therapy system delivering therapy according to the first therapy program; and

automatically determining, by the processor, a second therapy program that increases an operating efficiency of the therapy system while substantially maintaining the therapy field.

2. The method of claim 1, further comprising controlling, by the processor, the therapy system to deliver therapy to a patient according to the second therapy program.

3. The method of claim 1, wherein the algorithmic model of the therapy field comprises a first algorithmic model of a first therapy field, the method further comprising generating, by the processor, a second algorithmic model of a second therapy field representing where therapy will propagate from the therapy system based on the second therapy program.

4. The method of claim 3, further comprising presenting the first algorithmic model of the first therapy field and the second algorithmic model of the second therapy field to a user.

5. The method of claim 1, wherein automatically determining the second therapy program comprises automatically determining the second therapy program based on at least one of an amplitude-duration curve, a dose-response curve, a strength-duration curve, or a three-dimensional (3D) depolarization field model.

6. The method of claim 5, wherein the at least one amplitude-duration curve, dose-response curve, strength-duration curve, or 3D depolarization field model is configured based on at least one of a patient condition, a desired therapeutic outcome, or a tissue characteristic of a target delivery site.

7. The method of claim 1, wherein the second therapy program increases the operating efficiency of the therapy system by at least one of decreasing power consumption or operating at an efficient amplitude determined based on a voltage multiplier level.

8. The method of claim 1, wherein the algorithmic model of the therapy field comprises a first algorithmic model of a first therapy field, the method further comprising generating a second algorithmic model of a second therapy field based on the second therapy program, wherein substantially maintaining the therapy field comprises maintaining a difference between the first therapy field and the second therapy field below a threshold value, wherein the threshold value defines a maximum allowable change in at least one field characteristic.

9. The method of claim 8, wherein the at least one field characteristic comprises at least one of a centroid, a volume, an amplitude, a width at a defined amplitude, or a charge density.

10. The method of claim 8, wherein the threshold value comprises a weighted threshold of a plurality of field characteristics.

11. The method of claim 1, wherein generating the algorithmic model of the therapy field comprises representing where therapy will propagate from the therapy system based upon the first therapy program and an anatomical data set.

12. The method of claim 11, wherein the anatomical data set comprises at least one of an anatomical image of a patient, a reference anatomical image, an anatomical atlas, or a tissue conductivity data set.

13. The method of claim 1, wherein the therapy parameters comprise at least one of an electrode combination, pulse width, frequency or amplitude.

14. The method of claim 1, wherein the algorithmic model of the therapy field comprises at least one of a two dimensional algorithmic model or a three dimensional algorithmic model.

15. A therapy system comprising:

a medical device configured to deliver a therapy to a patient according to a first therapy program that comprises a first set of therapy parameters; and

a processor configured to;

generate an algorithmic model of a therapy field based on the first therapy program, wherein the algorithmic model represents where the therapy will propagate from the medical device delivering therapy according to the first therapy program, and

automatically determine a second therapy program that increases an operating efficiency of the therapy system while substantially maintaining the therapy field.

16. The therapy system of claim 15, wherein the medical device is configured to deliver therapy from the therapy system to the patient according to the second therapy program.

17. The therapy system of claim 15, wherein the algorithmic model of the therapy field comprises a first algorithmic model of a first therapy field, and wherein the processor is configured to generate a second algorithmic model of a second therapy field that represents where the therapy will propagate from the therapy system based on the second therapy program.

18. The therapy system of claim 17, further comprising a user interface that presents the first algorithmic model of the first therapy field and the second algorithmic model of the second therapy field to a user.

19. The therapy system of claim 15, wherein the processor is configured to automatically determine the second therapy program based on at least one of at least one of an amplitude-duration curve, a dose-response curve, a strength-duration curve, or a three-dimensional (3D) depolarization field model.

20. The therapy system of claim 19, wherein the at least one amplitude-duration curve, dose-response curve, strength-duration curve, or 3D depolarization field model is based on at least one of a patient condition, a desired therapeutic outcome, or a tissue characteristic of a target delivery site.

21. The therapy system of claim 15, wherein the second therapy program increases the operating efficiency of the therapy system by at least one of decreasing power consumption or operating at an efficient amplitude determined based on voltage multiplier levels.

22. The therapy system of claim 15, wherein the algorithmic model of the therapy field comprises a first algorithmic model of a first therapy field, wherein the processor is configured to generate a second algorithmic model of a second therapy field based on the second therapy program, and wherein substantially maintaining the therapy field comprises maintaining a difference between the first therapy field and the second therapy field below a threshold value, wherein the threshold value comprises a maximum allowable change in at least one field characteristic.

23. The therapy system of claim 22, wherein the at least one field characteristic comprises at least one of a centroid, an area, an amplitude, a width at a defined amplitude, or a charge density.

24. The therapy system of claim 22, wherein the threshold value comprises a weighted threshold of a plurality of field characteristics.

25. The therapy system of claim 15, wherein the processor is configured to generate the algorithmic model of the therapy field based upon the set of therapy parameters and an anatomical data set.

26. The therapy system of claim 15, wherein the medical device comprises the processor.

27. The therapy system of claim 15, further comprising a medical device programmer that comprises the processor.

28. The therapy system of claim 15, wherein the medical device is configured to deliver at least one of electrical stimulation therapy or a therapeutic agent to the patient.

29. A system comprising:

means for determining a first therapy program that comprises a set of therapy parameters values;

means for generating an algorithmic model of a therapy field based on the first therapy program, the algorithmic model representing where therapy will propagate from a therapy system delivering therapy according to the first therapy program; and

means for automatically determining a second therapy program that increases an operating efficiency of the therapy system while substantially maintaining the therapy field.

30. The system of claim 29, wherein the means for automatically determining the second therapy program determines the second therapy program based on at least one of at least one of an amplitude-duration curve, a dose-response curve, a strength-duration curve, or a three-dimensional (3D) depolarization field model.