METHOD FOR DETECTING NEUROLOGICAL AND CLINICAL MANIFESTATIONS OF A SEIZURE

• US 20150164403A1
• Filed: 02/25/2015
• Published: 06/18/2015
• Est. Priority Date: 12/28/2007
• Status: Active Grant

• Current Assignee: LivaNova USA, Inc. (LivaNova Plc)
• Original Assignee: Cyberonics, Inc
• Inventors: Leyde, Kent W., Bland, Michael
• Granted Patent: US 11,406,317 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61B 5/0031 Implanted circuitry
• CPC Class Codes: A61B 5/11 Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb for measuring pulse A61B5/02 ;A61B5/1038 takes precedence; motion detection to correct for motion artifacts in physiological signals A61B5/721
• CPC Class Codes: A61B 5/291 for electroencephalography [EEG]
• CPC Class Codes: A61B 5/316 Modalities, i.e. specific diagnostic methods
• 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 5/7221 Determining signal validity, reliability or quality A61B5/7207 and A61B5/7217 take precedence
• CPC Class Codes: A61B 5/7246 using correlation, e.g. template matching or determination of similarity
• 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

Abstract

Methods for detecting neurological and clinical manifestations of a seizure are provided. Systems are described including a monitoring device having a communication assembly for receiving neurological data transmitted external to a patient from a transmitter implanted in a patient; a processor that processes the neurological data to estimate the patient'"'"'s brain state; and an assembly for automatically recording clinical manifestation data in response to a brain state estimate by the processor.

Claims

1. A method of detecting a neurological status of a subject, the method comprising:

acquiring a neurological signal from the subject;

using a processor to perform a first determination of a neurological state of the subject based on the neurological signal;

acquiring a clinical manifestation signal from the subject contemporaneously with the neurological signal, the clinical manifestation signal comprising an accelerometer signal;

using the processor to perform a second determination of the neurological state of the subject based on the clinical manifestation signal;

comparing the first and second determinations to identify a preferred determination selected from at least one of the first and second determinations; and

identifying the neurological status of the subject based on the preferred determination.

2. The method of claim 1, wherein the neurological signal is at least one of an EEG signal and an ECoG signal.

3. The method of claim 1, wherein the first and second determinations are consistent with each other.

4. The method of claim 1, wherein the first and second determinations are inconsistent with each other.

5. The method of claim 4, wherein the first determination indicates that the subject is not experiencing a seizure and the second determination indicates that the subject is experiencing a seizure.

6. The method of claim 4, wherein the first determination indicates that the subject is experiencing a seizure and the second determination indicates that the subject is not experiencing a seizure.

7. The method of claim 1, wherein one of the first and second determinations does not indicate an occurrence of a seizure.

8. The method of claim 1, wherein the preferred determination is the first determination, and wherein the comparing of the first and second determinations includes confirming an accuracy of the first determination with the second determination.

9. The method of claim 1, wherein the preferred determination is the second determination, and wherein the comparing of the first and second determinations includes confirming an accuracy of the second determination with the first determination.

10. The method of claim 1, wherein the first determination is associated with a first accuracy value of the first determination and the second determination is associated with a second accuracy value of the second determination, and wherein the preferred determination is in part based on the first or second determination that has a greater accuracy value.

11. The method of claim 1, wherein the comparing of the first and second determinations includes identifying a deficiency in at least one of the first and second determinations.

12. A method of detecting a seizure status of a subject, the method comprising:

detecting a first seizure state using a neurological signal obtained from a neurological sensor monitoring the subject;

contemporaneously detecting a second seizure state using a clinical manifestation signal obtained from a clinical manifestation sensor monitoring the subject, the clinical manifestation signal comprising an accelerometer signal;

comparing the detection using the neurological signal and the detection using the clinical manifestation signal to identify a preferred detection selected from the detection using the neurological signal and the detection using the clinical manifestation signal; and

identifying the seizure status of the subject based on the preferred detection.

13. The method of claim 12, wherein the neurological sensor is disposed to monitor the subject'"'"'s brain, and wherein the neurological signal is at least one of an EEG signal and an ECoG signal.

14. The method of claim 12, wherein the first seizure state and the second seizure state are consistent with each other.

15. The method of claim 12, wherein the first seizure state and the second seizure state are inconsistent with each other.

16. The method of claim 15, wherein the first seizure state is a non-seizure state of the subject and the second seizure state is a seizure state of the subject.

17. The method of claim 15, wherein the first seizure state is a seizure state of the subject and the second seizure state is a non-seizure state of the subject.

18. The method of claim 12, wherein one of the first seizure state and the second seizure state does not indicate a seizure status of the subject.

19. The method of claim 12, wherein the preferred detection is the detection of the first seizure state, and wherein the comparing of the detection using the neurological signal and the detection using the clinical manifestation signal includes confirming an accuracy of the detection of the first seizure state with the detection of the second seizure state.

20. The method of claim 12, wherein the preferred detection is the detection of the second seizure state, and wherein the comparing of the detection using the neurological signal and the detection using the clinical manifestation signal includes confirming an accuracy of the detection of the second seizure state with the detection of the second seizure state.

21. The method of claim 12, wherein the detection of the first seizure state is associated with a first accuracy value and the detection of the second seizure state is associated with a second accuracy value, and wherein the preferred determination is in part based on the greater of the first and second accuracy values.

22. The method of claim 12, wherein the comparing of the detection using the neurological signal and the detection using the clinical manifestation signal includes identifying a deficiency in at least one of the detection of the first seizure state and the detection of the second seizure state.

23. A method of detecting a neurological status of a subject, the method comprising:

acquiring a neurological signal from the subject;

using a processor to identify a first parameter from the neurological signal, the first parameter associated with a first characterization of the neurological status of the subject;

acquiring a clinical manifestation signal from the subject contemporaneously with the neurological signal, the clinical manifestation signal comprising an accelerometer signal;

using the processor to identify a second parameter from the clinical manifestation signal, the second parameter associated with a second characterization of the neurological status of the subject;

comparing the first and second characterizations to identify a preferred characterization selected from at least one of the first and second characterizations; and

identifying the neurological status of the subject based on first and/or second parameter associated with the preferred determination.

24. The method of claim 23, wherein the neurological signal is at least one of an EEG signal and an ECoG signal.