Methods and Systems for Detecting Epileptic Events Using Nonlinear Analysis Parameters

• US 20100274303A1
• Filed: 04/24/2009
• Published: 10/28/2010
• Est. Priority Date: 04/24/2009
• Status: Active Grant

• Current Assignee: LivaNova USA, Inc. (LivaNova Plc)
• Original Assignee: Cyberonics, Inc
• Inventors: Bukhman, Vladislav
• Granted Patent: US 8,172,759 B2
• Time in Patent Office: Days
• US Class Current: 607/3
• CPC Class Codes: A61B 5/349 Detecting specific parameters of the electrocardiograph cycle
• CPC Class Codes: A61B 5/4094 Diagnosing or monitoring seizure diseases, e.g. epilepsy
• CPC Class Codes: A61N 1/36064 Epilepsy
• CPC Class Codes: A61N 1/36135 using physiological parameters
• CPC Class Codes: A61N 1/37241 providing test stimulations

Abstract

Disclosed herein are methods, systems, and apparatus for detecting an epilepsy event in a patient using a medical device. The medical device is capable of determining an occurring epilepsy event, for example a seizure or an increased risk of a seizure. The determination is performed by determining at least one nonlinear analysis parameter associated with the beat sequence of the patient'"'"'s heart. The medical device may then take a responsive action, such as warning, logging the time of the seizure, computing and storing one or more seizure severity indices, and treating the epilepsy event.

Claims

1. A method of detecting an epilepsy event in a patient, comprising:

receiving data relating to a beat sequence of the patient'"'"'s heart;

determining at least one regularity nonlinear analysis parameter associated with the beat sequence of the patient'"'"'s heart and at least one predictability nonlinear analysis parameter associated with the beat sequence of the patient'"'"'s heart;

comparing the at least one of the at least one regularity nonlinear analysis parameter to a first threshold and the at least one predictability nonlinear analysis parameter to a second threshold; and

providing an output indicative of at least one of an unstable brain state, a brain state indicative of an elevated probability of a seizure, a brain state indicative of an impending seizure, or a seizure based on the comparison.

2. The method of claim 1, wherein the at least one regularity nonlinear analysis parameter is sample entropy (SampEN) and the at least one predictability nonlinear analysis parameter is similarity of distribution (SOD).

3. A method of detecting an epilepsy event in a patient, comprising:

receiving data relating to a beat sequence of the patient'"'"'s heart;

determining at least one regularity nonlinear analysis parameter associated with the beat sequence of the patient'"'"'s heart;

comparing at least one of the at least one regularity nonlinear analysis parameter to a first threshold; and

providing an output indicative of at least one of an unstable brain state, a brain state indicative of an elevated probability of a seizure, a brain state indicative of an impending seizure, or a seizure based on the comparison.

4. The method of claim 3, wherein the at least one regularity nonlinear analysis parameter is sample entropy (SampEN).

5. A method of detecting an epilepsy event in a patient, comprising:

receiving data relating to a beat sequence of the patient'"'"'s heart;

determining at least one predictability nonlinear analysis parameter associated with the beat sequence of the patient'"'"'s heart;

comparing the at least one predictability nonlinear analysis parameter to a second threshold; and

providing an output indicative of at least one of an unstable brain state, a brain state indicative of an elevated probability of a seizure, a brain state indicative of an impending seizure, or a seizure based on the comparison.

6. The method of claim 5, wherein the at least one predictability nonlinear analysis parameter is similarity of distribution (SOD).

7. A method of detecting an epilepsy event in a patient, comprising:

receiving data relating to a beat sequence of the patient'"'"'s heart;

determining at least one nonlinear analysis parameter associated with the beat sequence of the patient'"'"'s heart;

comparing the nonlinear analysis parameter to a threshold; and

providing an output indicative of at least one of an unstable brain state, a brain state indicative of an elevated probability of a seizure, a brain state indicative of an impending seizure, or a seizure.

8. The method of claim 7, wherein receiving the data relating to the beat sequence of the patient'"'"'s heart comprises sensing a time of beat sequence of a patient'"'"'s heart and generating a time series data stream from said time of the beat sequence.

9. The method of claim 8, wherein receiving the data relating to the beat sequence of the patient'"'"'s heart comprises receiving a series of R-R intervals, and wherein generating the time series data stream comprises sensing a plurality of R peaks from the R-R intervals and using the R peaks for providing a time stamp to generate the time series data stream based upon the time stamp.

10. The method of claim 7, wherein determining the nonlinear analysis parameter comprises determining at least one of a complexity nonlinear analysis parameter and a stability nonlinear analysis parameter.

11. The method of claim 10, wherein the complexity nonlinear analysis parameter is approximate entropy (ApproxEN) or sample entropy value (SampEN) associated with said data relating to said beat sequence and the stability nonlinear analysis parameter is a Similarity of distribution value associated with said data relating to said beat sequence.

12. The method of claim 7, further comprising taking a responsive action selected from warning, logging the time of the seizure, computing and storing one or more seizure severity indices, and treating the epilepsy event based upon the comparing of the nonlinear analysis parameter to the threshold.

13. The method of claim 12, wherein treating comprises at least one of:

applying an electrical signal to a neural structure of a patient;

delivering a drug to a patient;

or

cooling a neural structure of a patient.

14. The method of claim 10, wherein applying an electrical signal to the neural structure comprises applying the electrical signal to at least one of a brain structure of the patient, a cranial nerve of a patient, a spinal cord of a patient, a sympathetic nerve structure of the patient, or a peripheral nerve of the patient.

15. A medical device for detecting an epilepsy event in a patient, comprising:

a sensing module adapted to receiving data relating to a beat sequence of the patient'"'"'s heart;

a nonlinear analysis parameter processing module adapted to determining at least one nonlinear analysis parameter associated with the beat sequence of the patient'"'"'s heart, and adapted to compare the nonlinear analysis parameter to a threshold; and

a communication unit adapted to provide an output indicative of at least one of an unstable brain state, a brain state indicative of an elevated probability of a seizure, a brain state indicative of an impending seizure, or a seizure based upon the comparing of the nonlinear analysis parameter to the threshold.

16. The medical device of claim 15, further comprising a stimulation unit adapted to apply an electrical signal to a neural structure to treat a seizure.

17. The medical device of claim 15, further comprising:

a memory unit to store at least a portion of the result of the comparison of the nonlinear analysis parameter and the threshold.

18. The medical device of claim 16, further comprising a lead interface, the lead interface being adapted to provide the electrical signal to a lead capable of being operatively coupled to an electrode, wherein the electrode is adapted to couple to at least one of a portion of a brain structure of the patient, a cranial nerve of a patient, a spinal cord of a patient, a sympathetic nerve structure of the patient, or a peripheral nerve of the patient.

19. The medical device of claim 15, wherein the nonlinear analysis parameter processing module is adapted to generate at least one of a complexity nonlinear analysis parameter or a stability nonlinear analysis parameter from the data relating to the beat sequence.

20. The medical device of claim 15, wherein the nonlinear analysis parameter processing module is adapted to determine at least one of a sample entropy value or a Similarity of distribution value based upon the data relating to the beat sequence.

21. The implantable medical device of claim 15, further comprising:

a heart beat sensor unit adapted to receive a heart beat signal from a sensor; and

a heart beat data processing module adapted to process the heart beat data to determine various properties of the patient'"'"'s heart beat time series.

22. The implantable medical device of claim 21:

wherein the heart beat sensor unit comprises;

a heart beat signal receiver adapted to receive, amplify, and filter the heart beat signal;

an analog to digital converter for converting the heart beat signal into a digital form to provide heart beat data; and

a heart beat correlation unit to organize the heart beat data and provide a time series of heart beats; and

wherein the heart beat data processing module comprises;

a heart beat determination module adapted to determine heart beats as they appear in the time series of heart beats;

a beat interval determination module adapted to determine the interval between consecutive beats;

a beat interval time series storage to receive beat interval data from the beat interval determination module and store the beat interval data; and

a beat interval statistics module adapted to determine one or more statistical values of a plurality of the beat interval time data.

23. A computer readable program storage device encoded with instructions that, when executed by a computer, perform a method of detecting an epilepsy event, the method comprising:

receiving data relating to a beat sequence of the patient'"'"'s heart;

determining at least one nonlinear analysis parameter associated with the beat sequence of the patient'"'"'s heart;

comparing the nonlinear analysis parameter to a threshold; and

providing an output indicative of at least one of an unstable brain state, a brain state indicative of an elevated probability of a seizure, a brain state indicative of an impending seizure, or a seizure.

24. The computer readable program storage device encoded with instructions that, when executed by a computer, perform the method of claim 23, further comprising taking a responsive action selected from warning, logging the time of the seizure, computing and storing one or more seizure severity indices, and treating the epilepsy event based upon the comparing of the nonlinear analysis parameter to the threshold.

25. The computer readable program storage device encoded with instructions that, when executed by a computer, perform the method of claim 23, wherein the treating is selected from the group consisting of:

applying an electrical signal to a neural structure of a patient;

delivering a drug to a patient; and

cooling a neural structure of a patient.

26. The computer readable program storage device encoded with instructions that, when executed by a computer, perform the method of claim 25, wherein applying the electrical signal to the neural structure of the patient comprises at least one of applying a deep brain stimulation (DBS) signal to a brain structure or applying an electrical signal to a cranial nerve of a patient.

27. A medical system for detecting an epilepsy event in a patient, comprising a medical device comprising:

a sensing module adapted to receiving data relating to a beat sequence of the patient'"'"'s heart;

a nonlinear analysis parameter processing module adapted to determining at least one nonlinear analysis parameter associated with the beat sequence of the patient'"'"'s heart and compare the nonlinear analysis parameter to a threshold; and

a storage unit to store an indication of an epilepsy event.

28. The medical system of claim 27, wherein the medical device further comprises a communications module adapted to communicate the indication to at least one of a patient, a caregiver, or a healthcare provider.

29. The medical system of claim 27, wherein the medical device further comprises a stimulation unit adapted to apply an electrical signal to a neural structure to treat an impending epilepsy event based upon the comparing of the nonlinear analysis parameter to the threshold.

30. The medical system of claim 27, wherein the medical device further comprises a stimulation unit adapted to apply an electrical signal to a neural structure to treat an epilepsy event based upon the comparing of the nonlinear analysis parameter to the threshold.

31. The medical system of claim 27, wherein the sensing module is adapted to be implanted into the body of the patient, and wherein the medical system further comprises a communications interface module that is external to the body of the patient, wherein the communications interface module is adapted to communicate with the communications module in the medical device.

32. The medical system of claim 31, wherein the sensing module is adapted to be implanted into the body of the patient, and wherein the nonlinear analysis parameter processing module is external to the patient'"'"'s body.