METHOD AND APPARATUS FOR DETECTION OF NERVOUS SYSTEM DISORDERS

• US 20080046024A1
• Filed: 12/12/2006
• Published: 02/21/2008
• Est. Priority Date: 04/21/2006
• Status: Active Grant

• Current Assignee: Medtronic Incorporated (Medtronic Plc)
• Original Assignee: Medtronic Incorporated (Medtronic Plc)
• Inventors: Drew, Touby, Panken, Eric, Werder, Jonathan, Carlson, David
• Granted Patent: US 8,165,683 B2
• Time in Patent Office: Days
• US Class Current: 607/45
• CPC Class Codes: A61B 5/02405 Determining heart rate variability
• CPC Class Codes: A61B 5/352 Detecting R peaks, e.g. for synchronising diagnostic apparatus; Estimating R-R interval
• CPC Class Codes: A61B 5/369 Electroencephalography [EEG] devices for psychotechnics A61B5/16
• CPC Class Codes: A61B 5/372 Analysis of electroencephalograms
• CPC Class Codes: A61B 5/375 using biofeedback
• CPC Class Codes: A61B 5/386 Accessories or supplementary instruments therefor
• CPC Class Codes: A61B 5/4094 Diagnosing or monitoring seizure diseases, e.g. epilepsy
• CPC Class Codes: A61B 5/7221 Determining signal validity, reliability or quality A61B5/7207 and A61B5/7217 take precedence
• 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: A61N 2/006 for magnetic stimulation of nerve tissue
• CPC Class Codes: G06F 2218/14 by matching peak patterns
• 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

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 neurological event, the method comprising:

acquiring an EEG signal comprising a stream of sampled data values;

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

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

deriving a magnitude threshold from the long-term representation;

comparing the data magnitude values to the magnitude threshold to produce a stream of comparator output values, each comparator output value indicating whether a given data magnitude value exceeds the magnitude threshold;

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 neurological event when the event monitoring parameter exceeds the onset threshold.

2. The method of claim 1 wherein the neurological event is an epileptic 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 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.

6. The method of claim 5 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.

7. The method of claim 5 wherein the previous value of the long-term representation has a predetermined initial value.

8. The method of claim 5 wherein the increment and decrement amounts are the same.

9. The method of claim 5 wherein at least one of the increment and decrement amounts is greater during an initial period after starting the method than following the initial period.

10. The method of claim 5 wherein at least one of the increment and decrement amounts is greater during a post-detection period after termination of an episode than following the post-detection period.

11. The method of claim 5 wherein the long-term representation cannot exceed a predefined maximum value.

12. The method of claim 5 wherein the long-term representation cannot decrease below a predefined minimum value.

13. The method of claim 1 wherein calculating the event monitoring parameter includes counting the comparator output values in the rolling window.

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

15. The method of claim 14 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.

16. The method of claim 14 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.

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

18. The method of claim 17 wherein the end of a neurological event is determined when the event monitoring parameter decreases below a termination threshold for a termination duration.

19. The method of claim 18 wherein the termination duration is complete when a specified number of consecutive values of the event monitoring parameter are below the termination threshold.

20. The method of claim 18 wherein the termination duration is complete when a predetermined percentage of values of the event monitoring parameter are below the termination threshold.

21. The method of claim 17 further comprising holding the long-term representation value constant when a neurological event is detected until the end of the neurological event.

22. The method of claim 17 further comprising assigning a predetermined initial value to the long-term representation at the end of a neurological event.

23. The method of claim 1 wherein the magnitude threshold is proportional to the long-term representation.

24. The method of claim 23 wherein the magnitude threshold is a user-selectable multiple of the long-term representation.

25. The method of claim 23 wherein the magnitude threshold equals the long-term representation multiplied by a seizure threshold factor, the seizure threshold factor ranging from about 2 to 64.

26. The method of claim 25 wherein the seizure threshold factor is about 22.

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

sample an EEG signal at a sample rate to form a stream of sampled data values;

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

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

derive a magnitude threshold from the long-term representation;

compare the data magnitude values to the magnitude threshold to produce a stream of comparator output values, each comparator output value indicating whether a given data magnitude value exceeds the magnitude threshold;

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 neurological event when the event monitoring parameter exceeds the onset threshold.

28. A system for detecting a neurological event, comprising:

an electrode adapted to sense an EEG signal from a brain of a patient; and

an implantable medical device (IMD) coupled to the electrode and adapted to receive the sensed EEG signal, the IMD comprising a housing, a memory, and a processor, the processor being adapted to

sample an EEG signal at a sample rate to form a stream of sampled data values;

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

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

derive a magnitude threshold from the long-term representation;

compare the data magnitude values to the magnitude threshold to produce a stream of comparator output values, each comparator output value indicating whether a given data magnitude value exceeds the magnitude threshold;

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 neurological event when the event monitoring parameter exceeds the onset threshold.

29. The system of claim 28, wherein the IMD is adapted to receive multiple channels of EEG signals, wherein the event monitoring parameter compared to the onset threshold is a logical combination of event monitoring parameters calculated for each channel.

30. The system of claim 29 wherein the event monitoring parameter compared to the onset threshold is a maximum function of event monitoring parameters calculated for each channel.

31. The system of claim 28 wherein the IMD prepares to deliver a therapy when the event monitoring parameter exceeds the onset threshold.

32. The system of claim 31 wherein preparing to deliver therapy includes charging stimulation circuitry.

33. The system of claim 31 wherein the IMD is adapted to deliver a therapy after the event monitoring parameter has exceeded the onset threshold for an onset duration.

34. The system of claim 28 wherein the IMD is adapted to deliver electrical stimulation therapy via the electrode.