Automated adjustment of posture state definitions for a medical device

• US 8,758,274 B2
• Filed: 04/28/2010
• Issued: 06/24/2014
• Est. Priority Date: 01/08/2010
• Status: Active Grant

• Current Assignee: Medtronic Incorporated (Medtronic Plc)
• Original Assignee: Medtronic Incorporated (Medtronic Plc)
• Inventors: Sahasrabudhe, Rajeev M., Davenport, Lynn, Davis, Jon P., Dewing, Wende L., Fehrmann, Elizabeth A., Goetz, Steven, Gokaldas, Shyam, Panken, Eric J.
• Primary Examiner(s): HINDENBURG, MAX F
• Application Number:
  US12/769,431
• Publication Number:
  US 20110172927A1
• Time in Patent Office: 1,518 Days
• Field of Search: 600/587, 600/595
• US Class Current: 600/595
• CPC Class Codes: A61B 2560/0223 of calibration, e.g. protocols for calibrating sensors
• CPC Class Codes: A61B 2560/0475 Special features of memory means, e.g. removable memory cards
• CPC Class Codes: A61B 5/021 Measuring pressure in heart or blood vessels A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/024 Detecting, measuring or recording pulse rate or heart rate A61B5/0205, A61B5/021 take precedence
• CPC Class Codes: A61B 5/1116 Determining posture transitions
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/369 Electroencephalography [EEG] devices for psychotechnics A61B5/16
• CPC Class Codes: A61B 5/389 Electromyography [EMG]
• CPC Class Codes: A61B 5/4839 combined with drug delivery
• CPC Class Codes: A61B 5/686 Permanently implanted devices, e.g. pacemakers, other stimulators, biochips A61B5/6861 takes precedence
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 5/7282 Event detection, e.g. detecting unique waveforms indicative of a medical condition A61B5/4094, A61B5/4818, A61B5/349, A61B5/0823 take precedence
• CPC Class Codes: A61B 5/742 using visual displays A61B5/339 takes precedence
• CPC Class Codes: A61B 5/7475 User input or interface means, e.g. keyboard, pointing device, joystick
• CPC Class Codes: A61N 1/36071 Pain
• CPC Class Codes: A61N 1/36535 controlled by body position or posture
• CPC Class Codes: A61N 1/37247 User interfaces, e.g. input or presentation means
• CPC Class Codes: G16H 20/30 relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16H 50/20 : for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

Techniques relate to operating a medical device by classifying a detected posture state of a patient. This classification may be performed by comparing the detected posture state of the patient to posture state definitions available within the system. Each definition may be described in terms of a parameter (e.g., vector) indicative of a direction in three-dimensional space. The posture state definitions may be calibrated by automatically estimating values for these parameters, thereby eliminating the need for the patient to assume each posture state during the calibration process to capture actual parameter values. According to another aspect, the estimated parameter values may be updated as the patient assumes various postures during a daily routine. For instance, estimated vectors initially used to calibrate the posture state definitions may be changed over time to more closely represent posture states the patient actually assumes, and to further adapt to changes in a patient'"'"'s condition.

Claims

1. A method, comprising:

creating posture state definitions, each including a defined vector describing a corresponding posture state;

receiving from a sensor signals indicative of a detected vector describing a detected posture state of the patient; and

identifying one of the posture state definitions to potentially update based on the detected vector;

determining whether the detected vector meets a requirement associated with the identified posture state definition; and

if the detected vector meets the requirement, updating the defined vector of the identified posture state definition based on a weighting function applied to the detected vector and the defined vector,

wherein one or more of the creating, identifying, determining and updating steps is performed by a processor.

2. The method of claim 1, further comprising:

determining whether the detected vector meets multiple requirements associated with the identified posture state definition; and

if the detected vector meets the requirements, updating the defined vector of the identified posture state definition based on the weighting function applied to the detected vector and the defined vector.

3. The method of claim 1, wherein determining whether the detected vector meets a requirement associated with the identified posture state definition comprises determining whether the detected vector is within a predetermined distance of the defined vector of the identified posture state.

4. The method of claim 1, wherein determining whether the detected vector meets a requirement associated with the identified posture state definition comprises determining whether the detected vector remains stable for at least a predetermined period of time.

5. The method of claim 1, further comprising:

receiving a trigger event;

in response to the trigger event, capturing one or more samples of the signals from the sensor; and

deriving the detected vector from the one or more samples.

6. The method of claim 5, wherein the trigger event is an indication received from a programmer.

7. The method of claim 1, further comprising selecting the weighting function based on a least one of the identified posture state definition, a scheduling function, and a patient parameter.

17. The method of claim 1, wherein the weighting function changes over time.

18. The method of claim 1, wherein the posture state definitions are used to classify the posture state of the patient, and wherein updating the defined vector of the identified posture state definition comprises updating the defined vector prior to using the posture state definitions to classify another posture state of the patient.

19. The method of claim 1, further comprising selecting the weighting function based on the identified one of the posture state definitions.

20. The method of claim 1, wherein the identified posture state definition defines a first region in three dimensional space and wherein determining whether the detected vector meets a requirement associated with the identified posture state definition comprises determining whether the detected vector falls within a second region in three-dimensional space that is located within the first region.

21. The method of claim 1, wherein the identified posture state definition defines a first region in three dimensional space, wherein determining whether the detected vector meets a requirement associated with the identified posture state definition comprises determining whether the detected vector falls within a second region in three-dimensional space, and wherein the first and second regions are not co-extensive.

22. The method of claim 1, further comprising storing a history of revisions made to the defined vector of the identified posture state definition.

8. A medical device, comprising:

a memory adapted to store a defined vector indicative of a corresponding defined posture state;

a sensor adapted to detect a vector indicative of a detected posture state of a patient; and

a processor adapted to update the defined vector based on a weighting function applied to the defined vector and the detected vector.

9. The device of claim 8, wherein the sensor is adapted to detect multiple samples of the detected vector and wherein the processor is adapted to select one or more of the samples of the detected vector to be used to update the defined vector.

10. The device of claim 9, wherein the processor is adapted to select the one or more of the samples based on a spatial relationship between the one or more of the samples and the defined vector.

11. The device of claim 9, wherein the processor is adapted to select the one or more of the samples based on stability of the one or more of the samples.

12. The device of claim 8, wherein the processor is adapted to automatically generate an estimated value for use as the defined vector before the defined vector is updated.

13. The device of claim 8, wherein the processor is adapted to initialize the defined vector based on a vector obtained from the sensor while a patient carrying the medical device assumes the corresponding defined posture state.

14. A system, comprising:

a device as in claim 8; and

a programmer to provide a trigger event to cause the processor to update the defined vector.

15. The device of claim 8, wherein the processor is adapted to automatically update the defined vector based on the detected vector indicating that the device has likely changed orientation with a patient.

23. The medical device of claim 8, wherein the memory is adapted to store multiple defined vectors, each indicative of a corresponding defined posture state, and wherein the processor is adapted to select the defined vector to update by determining a spatial relationship between the detected vector and each of the multiple defined vectors.

24. The medical device of claim 8, wherein the weighting function is determined based on the defined posture state.

25. The medical device of claim 8, wherein the weighting function is determined based on a scheduling function.

26. The medical device of claim 8, wherein the weighting function is determined based on a patient parameter.

27. The medical device of claim 8, wherein the memory is adapted to store multiple defined vectors, each indicative of a corresponding defined posture state, wherein the sensor is adapted to detect multiple vectors, each indicative of a detected posture state of the patient, and wherein the processor is adapted to, for each of the detected vectors, identify one of the multiple defined vectors to potentially update based on the detected vector, determine whether the detected vector meets a requirement associated with the identified one of the multiple defined vectors, if the detected vector meets the requirement, update the identified one of the multiple defined vectors based on a weighting function applied to the detected vector and the identified one of the multiple defined vectors.

16. A system, comprising:

means for providing an indication of a posture state of a patient;

means for classifying a posture state of the patient based on the indication and a set of defined posture vectors; and

means for updating one of the defined posture vectors in the set based on a weighting function applied to the indication of the posture state of the patient and the one of the defined posture vectors.

28. A method comprising:

defining a vector indicative of a corresponding defined posture state;

detecting, by a sensor, a vector indicative of a detected posture state of a patient; and

updating, by a processor, the defined vector based on a weighting function applied to the defined vector and the detected vector.

29. The method of claim 28, further comprising classifying, by the processor, the posture state of the patient based on the detected vector and the defined vector.

30. The method of claim 29, further comprising delivering, by a therapy module, a therapy to the patient in response to the posture state in which the patient is classified.

31. The method of claim 28, further comprising determining, based on the detected vector, whether the detected posture state of the patient is stable, and wherein updating, by the processor, the defined vector comprises updating the defined vector only if the detected posture state is stable.

32. The method of claim 31, wherein determining, based on the detected vector, whether the detected posture state is stable comprises determining whether the patient is classified in a same one of the defined posture states throughout a predetermined time period.

33. The method of claim 31, wherein determining, based on the detected vector, whether the detected posture state is stable comprises determining whether the detected posture state is stable based on a filter criteria that is adjusted over time.