Blended posture state classification and therapy delivery

Patent metadata

Field	Value
Publication number	US-9327129-B2
Application number	US-43303809-A
Country	US
Kind code	B2
Filing date	Apr 30, 2009
Priority date	Jul 11, 2008
Publication date	May 3, 2016
Grant date	May 3, 2016

Abstract

Techniques for classification of a posture state of a patient using multiple posture state definitions, and for delivering therapy according to the patient's classified posture state. Detected parameter values describing a patient's posture state are compared to posture state definitions. This comparison is used to determine similarity values describing how similar the patient's posture state is to each of the posture states described by the posture state definitions. Weighting factors may be determined from the similarity values and used to weight therapy parameter values that are associated with each of the posture state definitions. The resulting weighted therapy parameter values may be used to derive a blended therapy parameter value for use in delivering therapy to the patient. The patient's posture state may be expressed in terms of a blending of the multiple posture state definitions.

First claim

What is claimed is:

1. A method, comprising:
obtaining a detected parameter value for use in classifying a posture state of a patient;
for each of multiple posture state definitions, obtaining a respective defined parameter value and a respective therapy parameter value;
determining, for each of a plurality of the posture state definitions, a similarity between the detected parameter value and the respective defined parameter value;
determining a blended therapy parameter value based on the similarities and respective therapy parameter values for the plurality of the posture state definitions; and
delivering therapy to the patient via a medical device according to the blended therapy parameter value.

2. The method of claim 1 , wherein the detected parameter value is indicative of a posture of the patient, each of the defined parameter values is indicative of a respective defined posture, and wherein determining, for each of a plurality of the posture state definitions, a similarity comprises determining, for each of the plurality of the posture state definitions, how close the posture of the patient is to the defined posture that is indicated by the respective defined parameter value.

3. The method of claim 2 , wherein the detected parameter value comprises a detected posture vector, wherein the respective defined parameter value comprises a respective defined posture vector, and wherein determining, for each of a plurality of the posture state definitions, a similarity further comprises determining, for each of the plurality of the posture state definitions, a cosine of an angle between the detected posture vector and the respective defined posture vector.

4. The method of claim 1 , wherein determining, for each of a plurality of the posture state definitions, a similarity between the detected parameter value and the respective defined parameter value comprises selecting the plurality of the posture state definitions.

5. The method of claim 1 , further comprising determining a respective weighting factor W for each of the similarities and wherein determining a blended therapy parameter value comprises using the respective weighting factor to weight a respective therapy parameter value.

6. The method of claim 5 , wherein each weighting factor is determined using a weighting function.

7. The method of claim 6 , wherein determining, for each of a plurality of the posture state definitions, a similarity between the detected parameter value and the respective defined parameter value comprises determining a distance between the detected parameter value and the respective defined parameter value, and further comprising selecting the weighting function to map the distance to a value between 0 and a predetermined maximum positive number.

8. The method of claim 5 , wherein each of the plurality of posture state definitions is included in a set I and the respective therapy parameter value is a therapy parameter value P, and wherein the blended therapy parameter value is determined as

∑

i
∈
I

⁢

W
i

·

P
i

∑

i
∈
I

⁢

W
i

.

9. The method of claim 1 , further comprising selecting a subset of multiple positive ones of the similarities for use in determining the blended therapy parameter value.

10. The method of claim 1 , further comprising:
determining a weighting factor for each of the similarities;
normalizing each of the weighting factors; and
classifying the posture state based on the normalized weighting factors.

11. The method of claim 1 , further comprising:
using selected ones of the similarities to determine time-averaged weighting factors;
normalizing all of the time-averaged weighting factors with respect to each other; and
determining from any one of the normalized time-averaged weighting factors an amount of time attributable to an associated one of the multiple posture state definitions over a predetermined period of time.

12. The method of claim 1 , wherein the detected parameter value is indicative of a posture of the patient, and further comprising:
obtaining a second detected parameter value for use in classifying an activity state of a patient;
determining, for each of a second plurality of the posture state definitions, a similarity between the second detected parameter value and the respective defined parameter value;
using the similarity between the second detected parameter value and the respective defined parameter value to weight the respective therapy parameter value;
determining a second blended therapy parameter value based the weighted therapy parameter values; and
delivering therapy to the patient according to the blended therapy parameter value and the second blended therapy parameter value.

13. The method of claim 1 , further comprising delivering electrical stimulation therapy to the patient by an implantable medical device according to the blended therapy parameter value.

14. The method of claim 1 , wherein the detected parameter value is indicative of motion of the patient, and wherein the blended therapy parameter value is adapted to deliver therapy to the patient in response to the motion.

15. A system, comprising:
a sensor configured to provide a detected parameter value indicative of a posture state of a patient;
a storage device configured to store posture state definitions, each posture state definition being associated with a defined parameter value and a therapy parameter value; and
a processor configured to perform the steps of:
determining a similarity between the detected parameter value and each of a plurality of the defined parameter values associated with a plurality of the posture state definitions; and
determining a blended therapy parameter value for use in delivering therapy to the patient based on the similarities and on the therapy parameter values associated with the plurality of the posture state definitions.

16. The system of claim 15 , wherein the detected parameter value indicates a detected posture vector, the defined parameter values each indicates a defined posture vector, and wherein the processor is further configured to determine the similarity based on how close the detected posture vector is to a defined posture vector.

17. The system of claim 16 , wherein the processor is further configured to determine the similarity based on a cosine of an angle between the detected posture vector and a defined posture vector.

18. The system of claim 15 , wherein the processor is further configured to perform the steps of:
determining a respective weighting factor from each similarity;
multiplying each weighting factor by a therapy parameter value for an associated posture state defi

Assignees

• Panken Eric J
• Medtronic Inc

Inventors

• Panken Eric J

Classifications

• G16H50/20

  for computer-aided diagnosis, e.g. based on medical expert systems · CPC title

• A61B5/686

  Permanently implanted devices, e.g. pacemakers, other stimulators, biochips (A61B5/6861 takes precedence) · CPC title

• A61B2562/0219

  Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches · CPC title

• A61B5/7264

  Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems · CPC title

• A61N1/36542 Primary

  controlled by body motion, e.g. acceleration · CPC title