METHODS, SYSTEMS AND APPARATUSES FOR DETECTING INCREASED RISK OF SUDDEN DEATH

• US 20130281797A1
• Filed: 04/23/2012
• Published: 10/24/2013
• Est. Priority Date: 04/23/2012
• Status: Active Grant

• Current Assignee: LivaNova USA, Inc. (LivaNova Plc)
• Original Assignee: Cyberonics, Inc
• Inventors: SABESAN, Shivkumar
• Granted Patent: US 10,448,839 B2
• Time in Patent Office: Days
• US Class Current: 600/301
• CPC Class Codes: A61B 2505/07 Home care
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/0816 Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• CPC Class Codes: A61B 5/1112 Global tracking of patients, e.g. by using GPS
• CPC Class Codes: A61B 5/318 Heart-related electrical modalities, e.g. electrocardiography [ECG]
• CPC Class Codes: A61B 5/33 specially adapted for cooperation with other devices
• 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 5/4094 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: A61B 5/746 Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms alarms per se G08B
• CPC Class Codes: A61B 5/7465 Arrangements for interactive communication between patient and care services, e.g. by using a telephone network telemetry of measured physiological signal A61B5/0002
• CPC Class Codes: G16H 20/17 delivered via infusion or injection
• CPC Class Codes: G16H 20/30 relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 40/63 for local operation
• 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

Methods, systems, and apparatuses for detecting seizure events are disclosed, including a system for identification of an increased risk of a severe neurological event. The system may include an electroencephalogram (“EEG”) monitoring unit configured to collect EEG data from the patient during at least a postictal phase of one or more seizures and a processing unit configured to receive the EEG data from the EEG monitoring unit. The processing unit is configured to detect postictal EEG suppression from the EEG data and to identify the increased risk of the severe neurological event based on the detected postictal EEG suppression. Other embodiments are described and claimed.

Claims

1. A system for identification of an increased risk of a severe neurological event, comprising:

an electroencephalogram (“

EEG”

) monitoring unit configured to collect EEG data from the patient during at least a postictal phase of one or more seizures;

a processing unit configured to receive the EEG data from the EEG monitoring unit, the processing unit configured to detect postictal EEG suppression from the EEG data, the processing unit configured to identify the increased risk of the severe neurological event based on the detected postictal EEG suppression.

2. The system of claim 1, wherein the severe neurological event is sudden unexplained death in epilepsy (SUDEP).

3. The system of claim 1, wherein the postictal EEG suppression is comprised of multiple suppression periods interleaved with non-suppression periods during the postictal phase of one or more seizures.

4. The system of claim 3, wherein the postictal EEG suppression is progressive postictal EEG suppression characterized by a first trend of generally increasing duration with time of the multiple suppression periods during the postictal phase of one or more seizures.

5. The system of claim 4, wherein at least a first EEG suppression period of the multiple suppression periods occurs after a first seizure and at least a second EEG suppression period of the multiple suppression periods occurs after a second seizure, the second seizure occurring after the first seizure.

6. The system of claim 4, wherein the progressive postictal EEG suppression is further characterized by a second trend of generally decreasing duration with time of non-suppression periods during the postictal phase of the one or more seizures.

7. The system of claim 1, wherein the postictal EEG suppression is detected when the EEG data crosses an EEG threshold for at least a predetermined time period.

8. The system of claim 7, further comprising:

a respiratory monitoring unit configured to collect respiratory data from the patient'"'"'s respiration, wherein the processing unit is configured to receive the respiratory data from the respiratory monitoring unit and to determine whether the respiratory data crosses a respiration threshold.

9. The system of claim 8, wherein the processing unit is configured to determine whether the respiration data crosses the respiration threshold in response to a determination that the EEG data crosses the EEG threshold.

10. The system of claim 8, further comprising:

an electrocardiogram (“

EKG”

) monitoring unit configured to collect EKG data for the patient'"'"'s heart, wherein the processing unit is configured to receive the EKG data from the EKG monitoring unit and to determine whether the EKG data crosses an EKG threshold.

11. The system of claim 10, wherein the processing unit is configured to determine whether the EKG data crosses the EKG threshold in response to a determination that the respiration data crosses the respiration threshold.

12. A system for identification of an increased risk of a severe neurological event, comprising:

an electroencephalogram (“

EEG”

) monitoring unit configured to collect EEG data from the patient'"'"'s brain during at least a postictal phase of one or more seizures;

a processing unit configured to receive the EEG data from the EEG monitoring unit, the processing unit configured to detect postictal EEG suppression from the EEG data when the EEG data crosses an EEG threshold for at least a predetermined time period;

a respiratory monitoring unit configured to collect respiratory data from the patient'"'"'s respiration during at least the postictal phase of the one or more seizures in response to detection of the postictal EEG suppression, wherein the processing unit configured to receive the respiratory data from the respiratory monitoring unit and to determine whether the respiratory data crosses a respiratory threshold; and

an electrocardiogram (“

EKG”

) monitoring unit configured to collect EKG data for the patient'"'"'s heart, wherein the processing unit is configured to receive the EKG data from the EKG monitoring unit and to determine whether the EKG data crosses an EKG threshold, wherein the processing unit is configured to determine whether the EKG data crosses the EKG threshold in response to a determination that the respiration data crosses the respiration threshold;

wherein the processing unit configured to identify the increased risk of the severe neurological event based on the detected postictal EEG suppression, the determination that the respiration data crosses the respiration threshold, and the determination that the EKG data crosses the EKG threshold.

13. The system of claim 12, wherein the severe neurological event is sudden unexplained death in epilepsy (SUDEP).

14. The system of claim 12, wherein the postictal EEG suppression is comprised of multiple suppression periods interleaved with non-suppression periods during the postictal phase of one or more seizures.

15. The system of claim 14, wherein the postictal EEG suppression is progressive postictal EEG suppression characterized by a first trend of generally increasing duration with time of the multiple suppression periods and a second trend of generally decreasing duration with time of non-suppression periods during the postictal phase of the one or more seizures.

16. A method for detecting a condition in a patient that poses an increased risk of sudden unexplained death in epilepsy (SUDEP), comprising:

collecting encephalogram (“

EEG”

) data from a patient during at least a postictal phase of one or more seizures; and

determining whether the EEG data indicates postictal EEG suppression when the EEG data crosses an EEG threshold.

17. The method of claim 16, further comprising:

activating a warning device when the EEG data indicates postictal EEG suppression for a predetermined period of time.

18. The method of claim 16, further comprising:

collecting respiratory data from the patient'"'"'s respiration;

determining whether the respiratory data crosses a first threshold;

collecting electrocardiogram (“

EKG”

) data for the patient'"'"'s heart; and

determining whether the EKG data crosses a second threshold.

19. The method of claim 18, further comprising:

activating a warning device when the EEG data indicates postictal EEG suppression for a predetermined period of time, the respiratory data crosses the first threshold, and the EKG data crosses the second threshold.

20. The method of claim 16, wherein the postictal EEG suppression is progressive postictal EEG suppression comprised of multiple suppression periods interleaved with non-suppression periods.