METHOD AND APPARATUS FOR DETECTION OF NERVOUS SYSTEM DISORDERS

• US 20080269835A1
• Filed: 12/12/2006
• Published: 10/30/2008
• Est. Priority Date: 04/21/2006
• Status: Abandoned Application

• Current Assignee: Medtronic Incorporated (Medtronic Plc)
• Original Assignee: Medtronic Incorporated (Medtronic Plc)
• Inventors: Giftakis, Jonathon E., Panken, Eric J., Carlson, David L.
• Application Number:
  US11/609,446
• Publication Number:
  US 20080269835A1
• Time in Patent Office: Days
• US Class Current: 607/45
• CPC Class Codes: A61B 5/316 Modalities, i.e. specific diagnostic methods
• CPC Class Codes: A61B 5/346 Analysis of electrocardiograms
• CPC Class Codes: A61B 5/369 Electroencephalography [EEG] devices for psychotechnics A61B5/16
• 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: A61N 1/36082 Cognitive or psychiatric applications, e.g. dementia or Alzheimer's disease
• CPC Class Codes: G16H 40/63 for local operation

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 second neurological event following a first neurological event, the method comprising:

acquiring EEG signal data following the first neurological event, the EEG signal data comprising a stream of data values;

determining a short-term representation of the EEG signal data based on data values acquired over a first sample interval, the first sample interval occurring after a predetermined lock-out period following the first neurological event, the first sample interval including relatively recently acquired data values;

determining a long-term representation of the EEG signal data based on data values acquired over a second sample interval, the second sample interval being longer than the first sample interval;

determining an event monitoring parameter which approximates a ratio of the short-term representation to the long-term representation;

comparing the event monitoring parameter to a low level threshold, the low level threshold having a value of less than about 0.5; and

detecting a precursor to a neurological event when the event monitoring parameter decreases below the low level threshold.

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

3. The method of claim 1 wherein the minimum ratio threshold is less than about 0.2.

4. The method of claim 1 wherein the minimum ratio threshold is less than about 0.1.

5. The method of claim 1 where the minimum ratio threshold is about 0.08.

6. The method of claim 1 wherein the lock-out period begins upon detection of the first neurological event.

7. The method of claim 1 wherein the lock-out period begins upon termination of the first neurological event.

8. The method of claim 1 wherein the lock-out period begins when the event monitoring parameter decreases below a high level threshold after first rising above the high level threshold.

9. The method of claim 8 wherein high level threshold has a value greater than about 2.

10. The method of claim 1 wherein the lock-out period begins upon completion of therapy delivery.

11. The method of claim 10 wherein completion of therapy delivery occurs at the end of a period of electrical stimulation.

12. The method of claim 1 wherein the data values acquired over the second sample interval are comprised of the short-term representation values.

13. The method of claim 12 wherein the short-term representation values are downsampled prior to being used as data values for determining the long-term representation.

14. The method of claim 1 further comprising acquiring at least a minimum amount of EEG signal data following the lock-out period.

15. The method of claim 7 further comprising acquiring at least a minimum amount of EEG signal data following the termination of the first neurological event.

16. The method of claim 7 further comprising acquiring at least a minimum amount of EEG signal data following the lock-out period.

17. The method of claim 1 further comprising acquiring EEG signal data for at least a predetermined time interval following the lock-out period.

18. The method of claim 17 wherein the predetermined time interval is greater than about 2 minutes.

19. The method of claim 17 wherein the predetermined time interval is greater than about 10 minutes.

20. The method of claim 7 further comprising acquiring EEG signal data for at least a predetermined minimum amount of time following the termination of the first neurological event.

21. The method of claim 20 wherein the predetermined minimum amount of time is greater than about 2 minutes.

22. The method of claim 20 wherein the predetermined minimum amount of time is greater than about 10 minutes.

23. The method of claim 1 wherein at least a portion of the data values acquired during the lock-out period are ignored.

24. The method of claim 1 further comprising setting the value of the long-term representation to a specified minimum value if the long-term representation value determined is less than the specified minimum value.

25. The method of claim 24 further comprising applying a low-pass filter to the long-term representation.

26. The method of claim 1 wherein a precursor to a neurological event is detected when the event monitoring parameter decreases below the low level threshold for a specified duration.

27. The method of claim 26 wherein a precursor to a neurological event is detected when a number of consecutive values of the event monitoring parameter are below the low level threshold.

28. The method of claim 26 wherein a precursor to a neurological event is detected when a percentage of values of the event monitoring parameter are below the low level threshold.

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

acquire EEG signal data following the first neurological event, the EEG signal data comprising a stream of data values;

determine a short-term representation of the EEG signal data based on data values acquired over a first sample interval, the first sample interval occurring after a predetermined lock-out period following the first neurological event, the first sample interval including relatively recently acquired data values;

determine a long-term representation of the EEG signal data based on data values acquired over a second sample interval, the second sample interval being longer than the first sample interval;

determine an event monitoring parameter which approximates a ratio of the short-term representation to the long-term representation;

compare the event monitoring parameter to a low level threshold, the low level threshold having a value of less than about 0.5; and

detect a precursor to a neurological event when the event monitoring parameter decreases below the low level threshold.

30. 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 following the first neurological event, the EEG signal data comprising a stream of data values;

determine a short-term representation of the EEG signal data based on data values acquired over a first sample interval, the first sample interval occurring after a predetermined lock-out period following the first neurological event, the first sample interval including relatively recently acquired data values;

determine a long-term representation of the EEG signal data based on data values acquired over a second sample interval, the second sample interval being longer than the first sample interval;

determine an event monitoring parameter which approximates a ratio of the short-term representation to the long-term representation;

compare the event monitoring parameter to a low level threshold, the low level threshold having a value of less than about 0.5; and

detect a precursor to a neurological event when the event monitoring parameter decreases below the low level threshold.