METHOD AND APPARATUS FOR DETECTION OF NERVOUS SYSTEM DISORDERS

• US 20070249956A1
• Filed: 12/12/2006
• Published: 10/25/2007
• Est. Priority Date: 04/21/2006
• Status: Abandoned Application

• Current Assignee: Medtronic Incorporated (Medtronic Plc)
• Original Assignee: Medtronic Incorporated (Medtronic Plc)
• Inventors: Werder, Jonathan C., Drew, Touby A., Panken, Eric J., Carlson, David L.
• Application Number:
  US11/609,540
• Publication Number:
  US 20070249956A1
• Time in Patent Office: Days
• US Class Current: 600/544
• CPC Class Codes: A61B 5/374 Detecting the frequency distribution of signals, e.g. detecting delta, theta, alpha, beta or gamma waves
• CPC Class Codes: A61B 5/4094 Diagnosing or monitoring seizure diseases, e.g. epilepsy
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

Systems and methods for detecting and/or treating nervous system disorders, such as seizures, are disclosed. Certain embodiments of the invention relate generally to implantable medical devices (IMDs) adapted to detect and treat nervous system disorders in patients with an IMD. Certain embodiments of the invention include detection of seizures based upon comparisons of long-term and short-term representations of physiological signals. Other embodiments include prediction of seizure activity based upon analysis of physiological signal levels. An embodiment of the invention monitors the quality of physiological signals, and may be able to compensate for signals of low signal quality. A further embodiment of the invention includes detection of seizure activity following the delivery of therapy.

Claims

1. A method of detecting a precursor to a neurological event, the method comprising:

acquiring EEG signal data comprising a stream of data values;

transforming the stream of data values into a stream of data magnitude values;

determining a long-term representation of the EEG signal data from the data magnitude values;

comparing a scale multiple of the data magnitude values to the long-term representation to produce a stream of comparator output values, each comparator output value indicating whether the scale multiple of a given data magnitude value is below the long-term representation;

calculating an event monitoring parameter based on a rolling window of comparator output values;

comparing the event monitoring parameter to an onset threshold; and

detecting a precursor to a neurological event when the event monitoring parameter exceeds the onset threshold.

2. The method of claim 1 wherein the neurological event is a seizure.

3. The method of claim 1 wherein the data magnitude values comprise positive values derived from the stream of sampled data values.

4. The method of claim 1 wherein the long-term representation is a long-term average of the data magnitude values.

5. The method of claim 1 wherein the scale multiple is greater than about 2.

6. The method of claim 1 wherein the scale multiple is greater than about 5.

7. The method of claim 1 wherein the scale multiple is greater than about 10.

8. The method of claim 1 wherein the scale multiple is greater than about 12.

9. The method of claim 1 wherein determining the long-term representation comprises comparing a data magnitude value to a previous value of the long-term representation, and incrementing the previous value by a predetermined increment amount if the data magnitude value equals or exceeds the previous value, and decrementing the previous value by a predetermined decrement amount if the data magnitude value is less than the previous value.

10. The method of claim 9 wherein the data magnitude value that is compared to the previous value of the long-term representation is downsampled from the stream of data magnitude values.

11. The method of claim 9 wherein the previous value of the long-term representation has a predetermined initial value.

12. The method of claim 9 wherein the increment and decrement amounts are the same.

13. The method of claim 9 wherein the long-term representation cannot exceed a predefined maximum value.

14. The method of claim 9 wherein the long-term representation cannot decrease below a predefined minimum value.

15. The method of claim 1 wherein a neurological event is detected when the event monitoring parameter exceeds the onset threshold for an onset duration.

16. The method of claim 15 wherein a neurological event is detected when a specified number of consecutive values of the event monitoring parameter exceed the onset threshold for an onset duration.

17. The method of claim 15 wherein a neurological event is detected when a predetermined percentage of values of the event monitoring parameter exceed the onset threshold for a detection duration.

18. The method of claim 1 further comprising determining an end of a neurological event when the event monitoring parameter decreases below a termination threshold.

19. The method of claim 18 wherein the end of a neurological event is determined when the event monitoring parameter decreases below a termination threshold for a termination duration.

20. The method of claim 19 wherein the termination duration is complete when a specified number of consecutive values of the event monitoring parameter are below the termination threshold.

21. The method of claim 19 wherein the termination duration is complete when a predetermined percentage of values of the event monitoring parameter are below the termination threshold.

22. The method of claim 18 further comprising holding the long-term representation value constant when a neurological event is detected until the end of the neurological event.

23. The method of claim 18 further comprising assigning a predetermined initial value to the long-term representation at the end of a neurological event.

24. The method of claim 1 further comprising acquiring at least a minimum amount of EEG signal data.

25. The method of claim 1 further comprising acquiring at least a minimum amount of EEG signal data following a termination of a neurological event.

26. The method of claim 1 further comprising acquiring EEG signal data for at least a predetermined time interval.

27. The method of claim 26 wherein the predetermined time interval is greater than about 2 minutes.

28. The method of claim 26 wherein the predetermined time interval is greater than about 10 minutes.

29. The method of claim 1 further comprising acquiring EEG signal data for at least a predetermined minimum amount of time following a termination of a neurological event.

30. The method of claim 29 wherein the predetermined minimum amount of time is greater than about 2 minutes.

31. The method of claim 29 wherein the predetermined minimum amount of time is greater than about 10 minutes.

32. The method of claim 1 further comprising imposing a lock-out period following a prior neurological event, EEG signal data being effectively ignored during the lock-out period.

33. The method of claim 1 further comprising imposing a lock-out period following a prior neurological event during which an event monitoring parameter in not calculated.

34. The method of claim 32 further comprising acquiring at least a minimum amount of EEG signal data following the lock-out period.

35. The method of claim 32 wherein the lock-out period begins upon termination of the prior neurological event.

36. The method of claim 32 wherein the lock-out period begins upon completion of therapy delivery for the prior neurological event.

37. A computer-readable medium programmed with instructions for performing a method of detecting a precursor to a neurological event, the medium comprising instructions for causing a programmable processor to:

acquire EEG signal data comprising a stream of data values;

transform the stream of data values into a stream of data magnitude values;

determine a long-term representation of the EEG signal data from the data magnitude values;

compare a scale multiple of the data magnitude values to the long-term representation to produce a stream of comparator output values, each comparator output value indicating whether the scale multiple of a given data magnitude value is below the long-term representation;

calculate an event monitoring parameter based on a rolling window of comparator output values;

compare the event monitoring parameter to an onset threshold; and

detect a precursor to a neurological event when the event monitoring parameter exceeds the onset threshold.

38. A system for detecting a precursor to a neurological event, the system comprising:

an implantable medical device; and

an electrode adapted to sense EEG signals from a brain of a patient and communicate EEG signals to the device, wherein the device is adapted to acquire EEG signal data comprising a stream of data values;

transform the stream of data values into a stream of data magnitude values;

determine a long-term representation of the EEG signal data from the data magnitude values;

compare a scale multiple of the data magnitude values to the long-term representation to produce a stream of comparator output values, each comparator output value indicating whether the scale multiple of a given data magnitude value is below the long-term representation;

calculate an event monitoring parameter based on a rolling window of comparator output values;

compare the event monitoring parameter to an onset threshold; and

detect a precursor to a neurological event when the event monitoring parameter exceeds the onset threshold.