Methods and systems for detecting epileptic events using nonlinear analysis parameters

• US 8,172,759 B2
• Filed: 04/24/2009
• Issued: 05/08/2012
• Est. Priority Date: 04/24/2009
• Status: Active Grant

• Current Assignee: LivaNova USA, Inc. (LivaNova Plc)
• Original Assignee: Cyberonics, Inc
• Inventors: Bukhman, Vladislav
• Primary Examiner(s): Layno, Carl H
• Assistant Examiner(s): Wu, Eugene
• Application Number:
  US12/429,746
• Publication Number:
  US 20100274303A1
• Time in Patent Office: 1,110 Days
• Field of Search: 600/483, 600/508, 600/509, 600/544, 607/2, 607/3, 607/45
• US Class Current: 600/483
• 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 comprising:

receiving data relating to a beat sequence of a 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;

performing a first comparison of the at least one regularity nonlinear analysis parameter to a first adjustable threshold;

performing a second comparison of the at least one predictability nonlinear analysis parameter to a second adjustable threshold;

detecting an epilepsy event based on the first comparison and the second comparison, the epilepsy event comprising 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, and a seizure; and

providing an output indicative of the epilepsy event.

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), and wherein at least one of the first adjustable threshold and the second adjustable threshold is occasionally adjusted based in part on at least one of the patient'"'"'s physiological condition, a patient'"'"'s environment, and circadian rhythms.

3. A method comprising:

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

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

performing a comparison of the at least one regularity nonlinear analysis parameter to an adjustable threshold;

detecting an epilepsy event based on the comparison, the epilepsy event comprising 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, and a seizure; and

providing an output indicative of the epilepsy event.

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

5. A method comprising:

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

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

performing a comparison of the at least one predictability nonlinear analysis parameter to an adjustable threshold;

detecting an epilepsy event based on the comparison, the epilepsy event comprising 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, and a seizure; and

providing an output indicative of the epilepsy event.

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

7. A method comprising:

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

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

performing a comparison of the at least one nonlinear analysis parameter to an adjustable threshold;

detecting an epilepsy event based on the comparison, the epilepsy event comprising 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, and a seizure; and

providing an output indicative of the epilepsy event.

8. The method of claim 7, wherein receiving the data relating to the beat sequence of the patient'"'"'s heart comprises:

receiving a series of R-R intervals,

sensing a time of beat sequence of the patient'"'"'s heart, and

generating a time series data stream from the time of the beat sequence, 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.

9. The method of claim 7, wherein the adjustable threshold is adjustable using an external device.

10. The method of claim 7, wherein determining the at least one 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 an approximate entropy (ApproxEN) value or a sample entropy (SampEN) value associated with the data relating to the beat sequence and the stability nonlinear analysis parameter is a Similarity of distribution value associated with the data relating to the beat sequence.

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

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

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

delivering a drug to the patient; and

cooling a neural structure of the patient.

14. The method of claim 13, wherein applying the 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 the patient, a spinal cord of the patient, a sympathetic nerve structure of the patient, and a peripheral nerve of the patient.

15. A medical device comprising:

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

a nonlinear analysis parameter processing module adapted to determine at least one nonlinear analysis parameter associated with the beat sequence of the patient'"'"'s heart, adapted to perform a comparison of the at least one nonlinear analysis parameter to an adjustable threshold, and adapted to detect an epilepsy event based on the comparison, the epilepsy event including 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, and a seizure; and

a communication unit adapted to provide an output indicative of the epilepsy event.

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

a stimulation unit adapted to apply an electrical signal to a neural structure to treat the seizure, and

a lead interface adapted to provide the electrical signal to a lead that is adapted to be 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 the patient, a spinal cord of the patient, a sympathetic nerve structure of the patient, and a peripheral nerve of the patient.

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

a threshold value module to store and to calculate the adjustable threshold; and

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

18. The medical device of claim 15, wherein the adjustable threshold is adjustable using a device external to 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 and 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 and a Similarity of distribution value based upon the data relating to the beat sequence.

21. The 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 heart beat data based on the heart beat signal to determine various properties of a time series of the patient'"'"'s heart beat.

22. The 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 to convert the heart beat signal into a digital form to provide the 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 an interval between consecutive heart 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 based on the beat interval data.

23. A computer readable program storage device encoded with instructions that, when executed by a processor, cause the processor to:

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

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

perform a comparison of the at least one nonlinear analysis parameter to an adjustable threshold;

detect an epilepsy event based on the comparison, the epilepsy event comprising 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, and a seizure; and

provide an output indicative of the epilepsy event.

24. The computer readable program storage device of claim 23, wherein the instructions are further executable to cause the processor to take a responsive action selected from providing a warning, logging a time of the seizure, computing and storing one or more seizure severity indices, and treating the epilepsy event based upon the comparison of the at least one nonlinear analysis parameter to the adjustable threshold.

25. The computer readable program storage device of claim 24, wherein the treating the epilepsy event includes at least one of:

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

delivering a drug to the patient; and

cooling the neural structure of the patient.

26. The computer readable program storage device 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 and applying the electrical signal to a cranial nerve of the patient.

27. A medical system comprising:

a sensing module adapted to receive data related to a beat sequence of a patient'"'"'s heart;

a nonlinear analysis parameter processing module adapted to determine at least one nonlinear analysis parameter associated with the beat sequence of the patient'"'"'s heart, to perform a comparison of the at least one nonlinear analysis parameter to an adjustable threshold, and to detect an epilepsy event based on the comparison, the epilepsy event comprising 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, and a seizure; and

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

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

29. The medical system of claim 27, further comprising;

a threshold value module to store and to calculate the adjustable threshold; and

a stimulation unit adapted to apply an electrical signal to a neural structure to treat an impending epilepsy event based upon the comparison of the at least one nonlinear analysis parameter to the adjustable threshold.

30. The medical system of claim 27, further comprising a stimulation unit adapted to apply an electrical signal to a neural structure to treat the epilepsy event based upon the comparison of the at least one nonlinear analysis parameter to the adjustable threshold.

31. The medical system of claim 27, wherein the sensing module is part of an implantable medical device that is adapted to be implanted into a 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 a communications module in the implantable medical device.

32. The medical system of claim 31, wherein the nonlinear analysis parameter processing module is external to the body of the patient.