Identifying seizures using heart data from two or more windows

Patent metadata

Field	Value
Publication number	US-9498162-B2
Application number	US-201113093613-A
Country	US
Kind code	B2
Filing date	Apr 25, 2011
Priority date	Apr 25, 2011
Publication date	Nov 22, 2016
Grant date	Nov 22, 2016

Abstract

Methods and systems for characterizing a seizure event in a patient, including determining a time of beat sequence of the patient's heart, determining a first HR measure for a first window, determining a second HR measure for a second window, wherein at least a portion of the first window occurs after the second window, determining at least one HR parameter based upon said first HR measure and said second HR measure, identifying an onset of the seizure event in response to determining that at least one HR parameter crosses an onset threshold, identifying an end of the seizure event in response to determining that at least one HR parameter crosses an offset threshold.

First claim

What is claimed is:

1. A method for characterizing a seizure event of a patient, the method comprising:
receiving, at an analyzer device, first data during a first time period, the first data corresponding to a first beat sequence of a heart of the patient;
determining, via the analyzer device, a first heart rate (HR) measure for a first window of the first time period based on the first data;
determining, via the analyzer device, a second HR measure for a second window of the first time period based on the first data, wherein the first window of the first time period occurs after the second window of the first time period, and wherein an intermediate window of the first time period spans from an end of the second window to a start of the first window; and
determining, via the analyzer device, whether an onset of the seizure event has occurred based on a ratio of the first HR measure to the second HR measure, a ratio of the second HR measure to the first HR measure, or both, wherein the analyzer device determines the onset of the seizure event without requiring brain activity data to verify the heart rate data.

2. The method of claim 1 , wherein the first window of the first time period, the intermediate window of the first time period, and the second window of the first time period are consecutive time windows.

3. The method of claim 1 , wherein the first HR measure is a measure of a standard deviation of HR in the first window of the first time period and wherein the second HR measure is a measure of a standard deviation of HR in the second window of the first time period.

4. The method of claim 1 , further comprising:
identifying an end of the seizure event; and
sending information indicative of the end of the seizure event to an output device.

5. The method of claim 1 , wherein the first window comprises a shorter duration than the intermediate window, and wherein the intermediate window comprises a shorter duration than the second window.

6. The method of claim 1 , further comprising:
identifying the second heart rate measure based on the second window, wherein the second heart rate measure comprises a stable heart rate;
identifying the first heart rate measure based on the first window, wherein the first heart rate measure comprises an increasing heart rate; and
isolating a transitional effect, the transitional effect comprises a duration, wherein the stable heart rate transitions to the increasing heart rate.

7. The method of claim 1 , wherein at least the first window of the first time period of the second window of the first time period are sliding windows, and further comprising identifying, via the analyzer device, the onset of the seizure event based on a first window of a second time period and a second window of the second time period.

8. The method of claim 7 , wherein the second time period at least partially overlaps the first time period.

9. The method of claim 7 , wherein the second window of the second time period at least partially overlaps the first window of the first time period.

10. The method of claim 1 , wherein the first window of the first time period and the second window of the first time period are sliding windows, and further comprising:
receiving, at the analyzer device, second data corresponding to a second beat sequence of the heart of the patient during a second time period;
determining, via the analyzer device, a third HR measure for a first window of the second time period based on the second data;
determining, via the analyzer device, a fourth HR measure for a second window of the second time period based on the second data, wherein the first window of the second time period occurs after the second window of the second time period; and
identifying, via the analyzer device, the onset of the seizure event in response to determining that a second ratio based on the third HR measure and the fourth HR measure, or both, exceed an onset threshold.

11. A system for identifying seizures, the system comprising:
one or more processors; and
one or more memory units coupled to the one or more processors, wherein the one or more memory units comprise instructions executable by the one or more processors to:
receive data corresponding to a beat sequence of a heart of a patient during a time period;
determine a first heart rate (HR) measure for a first window of the time period based on the data;
determine a second HR measure for a second window of the time period based on the data, wherein the first window occurs after the second window, and wherein an intermediate window of the time period spans from an end of the second window to a start of the first window;
identify an onset of a seizure event in response to a determination that one of a ratio of the first HR measure to the second HR measure or a ratio of the second HR measure to the first HR measure satisfies an onset threshold associated with the onset of the seizure event, wherein the one or more processors determines the onset of the seizure event without requiring brain activity data to verify the heart rate data; and
identify an end of the seizure event.

12. The system of claim 11 , wherein the instructions are executable by the one or more processors to:
determine a duration of time between the onset of the seizure event and the end of the seizure event;
compare the duration of time to a threshold; and
send an output to at least one output device in response to a determination that the duration of time satisfies the threshold, the output includes an indication that a seizure is detected.

13. The system of claim 11 , wherein the first HR measure is one of a measure of a mean heart rate in the first window or a median heart rate in the first window, and wherein the second HR measure is one of a measure of a mean heart rate in the second window or a median heart rate in the second window.

14. A non-transitory computer-readable medium comprising instructions executable by a processor to:
determine a first heart rate (HR) measure for a first window of a time period based on data, wherein the data corresponds to a beat sequence of a heart of a patient during the time period;
determine a second HR measure for a second window of the time period based on the data, wherein the first window occurs after the second window, and wherein an intermediate window of the time period spans from an end of the second window to a start of the first window;
determine a ratio based on the first HR measure and the second HR measure;
identify an onset of a seizure event in response to a determination that the ratio satisfies an onset threshold, wherein the processor determines the onset of the seizure event without requiring brain activity data to verify the heart rate data; and
send information indicative of the onset of the seizure event to an output device.

15. The non-transitory computer-readable medium of claim 14 , where the first window, the intermediate window, and the second window are time windows or number-of-beats windows.

16. The non-transitory computer-readable medium of claim 14 , wherein the first HR measure comprises a statistical measure of central tendency of HR in the first window, and wherein the second HR measure comprises a statistical measure of central tendency of HR in the second window.

17. The non-transitory computer-readable medium of claim 16 , wherein the statistical measure of the central tendency of HR in the first window includes one of a mean heart rate in the first window and a standard deviation of HR in the first window, and wherein the statistical

Assignees

• Liao Wangcai
• Zhang Jicong
• Cyberonics Inc

Inventors

• Liao Wangcai
• Zhang Jicong

Classifications

• A61B5/024

  Measuring pulse rate or heart rate · CPC title

• A61B5/0245

  by using sensing means generating electric signals, {i.e. ECG signals} · CPC title

• A61B5/02438

  with portable devices, e.g. worn by the patient · CPC title

• A61B5/7282 Primary

  Event detection, e.g. detecting unique waveforms indicative of a medical condition (cough events A61B5/0823; seizures A61B5/4094; sleep apnoea A61B5/4818) · CPC title

• A61B5/4094

  Diagnosing or monitoring seizure diseases, e.g. epilepsy · CPC title