Low Power Device With Variable Scheduling

• US 20080161713A1
• Filed: 12/27/2006
• Published: 07/03/2008
• Est. Priority Date: 12/27/2006
• Status: Active Grant

• Current Assignee: Cyberonics, Inc
• Original Assignee: Cyberonics, Inc
• Inventors: Leyde, Kent, Harris, John
• Granted Patent: US 9,913,593 B2
• Time in Patent Office: Days
• US Class Current: 600/544
• CPC Class Codes: A61B 2560/0209 adapted for power saving
• CPC Class Codes: A61B 5/0006 ECG or EEG signals
• CPC Class Codes: A61B 5/369 Electroencephalography [EEG] devices for psychotechnics A61B5/16
• CPC Class Codes: A61B 5/4094 Diagnosing or monitoring seizure diseases, e.g. epilepsy
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: G16H 40/63 for local operation

Abstract

Medical device systems and methods for operating medical device systems conserve energy by efficiently managing computational demands of the systems. Signals from a subject are processed and analyzed and an estimate of a propensity for a subject to have a neurological event is determined. Based on the results of the analysis and the estimate, further analysis may be performed and the estimate may be refined. Succeeding cycles of signal measurement and analysis are scheduled depending on the results of the analysis and the estimate. The schedule may be varied temporally or with regard to the types and intensities of analyses performed.

Claims

1. A method of operating a medical device system, the method comprising:

receiving at least one signal from a physiological sensor at a first time;

processing the at least one signal to detect pre-onset characteristics of a neurological event; and

scheduling subsequent receiving at least one signal and subsequent processing the at least one signal, wherein said scheduling is based at least in part on the processing of the at least one signal.

2. The method as recited in claim 1 wherein scheduling subsequent receiving at least one signal and subsequent processing the at least one signal comprises determining a time when subsequent receiving at least one signal and subsequent processing the at least one signal is to be performed.

3. The method as recited in claim 2 wherein said scheduling is further based at least in part on a charge condition of a battery associated with the medical device system.

4. The method as recited in claim 2 wherein said scheduling is further based at least in part on a measurement indicative of sleep.

5. The method as recited in claim 2 wherein said scheduling is further based at least in part on the time of day.

6. The method as recited in claim 1 wherein the physiological sensor measures an electrical signal from a brain.

7. The method as recited in claim 1 wherein processing the at least one signal is performed by a programmed computer processing unit.

8. The method as recited in claim 1 wherein the processing the at least one signal comprises performing an analysis on the at least one signal to estimate a propensity for a subject to have a neurological event within a specified time horizon.

9. The method as recited in claim 8 wherein performing an analysis to estimate a propensity for the subject to have a neurological event comprises estimating a time horizon during which an estimated likelihood that the subject will have a neurological event is below a predetermined threshold.

10. The method as recited in claim 9 wherein scheduling subsequent operations comprises determining a time when subsequent operations are to be performed, the determination of a time being based on the estimate of a time horizon during which an estimated propensity for the subject to have a neurological event is below a predetermined threshold.

11. The method as recited in claim 10 wherein the time when subsequent operations are to be performed is between one half and one hundredth of the estimate of a time horizon after the time the analysis was performed.

12. The method as recited in claim 2 wherein scheduling subsequent receiving at least one signal and subsequent processing the at least one signal further comprises selecting at least one analysis system for subsequent processing the at least one signal wherein the at least one analysis system for subsequent processing is selected based at least in part on the detection of pre-onset characteristics of a neurological event.

13. The method as recited in claim 8 wherein processing the at least one signal to estimate a propensity for the subject to have a neurological event comprises:

performing a first analysis to estimate a first propensity for the subject to have a neurological event; and

performing a second analysis to estimate a second propensity for the subject to have a neurological event when the first estimate meets one or more specified criteria.

14. A neurological measurement system comprising:

at least one sensor input that receives at least one electrical signal indicative of a physiological measurement;

logic arranged to process the at least one electrical signal and estimate a propensity for a future neurological event to occur; and

a processor and memory programmed to activate the logic at a variable time interval wherein the variable time interval is adjusted in response to the estimate of a propensity for a future neurological event to occur.

15. The system as recited in claim 14 wherein the logic comprises a processor and programmed memory.

16. The system as recited in claim 14 further comprising a sensor that measures electrical signals indicative of brain activity.

17. The system as recited in claim 16 wherein the future neurological event is an epileptic seizure.

18. The system as recited in claim 14 wherein the processor is external to the subject.

19. The system as recited in claim 14 wherein the variable time interval is adjusted at least in part in response to a charge condition of a battery associated with the medical device system.

20. The system as recited in claim 14 wherein the variable time interval is adjusted at least in part in response to a state of wakefulness of the subject.

21. The system as recited in claim 14 wherein the variable time interval is adjusted at least in part in response to the time of day.

22. The system as recited in claim 14 wherein said logic is arranged to:

process the at least one electrical signal and estimate a first propensity for the subject to have a future neurological event; and

perform a second analysis to estimate a second propensity for the subject to have a future neurological event when the first estimate meets one or more specified criteria.

23. A system for estimating a propensity for a subject to have an epileptic seizure comprising:

at least one sensor input that receives at least one electrical signal indicative of a physiological measurement from a subject;

first logic arranged to extract one or more characteristics from at least one electrical signal and to classify the extracted characteristics to estimate a first propensity of the subject to have an epileptic seizure;

second logic configured to schedule subsequent signal receiving and subsequent extraction of one or more characteristics of subsequently received signals based at least in part on the estimate of a propensity for the subject to have an epileptic seizure.

24. The system as recited in claim 23 further comprising:

an implanted device for wirelessly transmitting data representative of said at least one electrical signal; and

an external receiver for receiving the transmitted data representative of said at least one electrical signal.

25. The system as recited in claim 24 further comprising an output device for communicating information related to the estimate of the propensity to the subject.

26. A device comprising:

means for inputting at least one signal indicative of a physiological characteristic of a subject;

means for processing the at least one signal to determine an estimate of a propensity for the subject to undergo a future neurological event; and

means for scheduling said means for inputting and said means for processing in response to the estimate of a propensity for the subject to undergo a neurological event.

27. The device as recited in claim 26 wherein said means for scheduling said means for inputting and said means for processing comprise means for scheduling said means for inputting and said means for processing at time intervals that are varied in response to the estimate of a propensity for the subject to undergo a neurological event.

28. The device as recited in claim 26 wherein said means for scheduling said means for inputting and said means for processing comprise means for varying the processing performed by said means for processing in response to the estimate of a propensity for the subject to undergo a neurological event.

29. A method comprising:

receiving at least one electrical signal indicative of brain activity of a subject at a first time;

processing the at least one electrical signal to detect pre-onset characteristics of an epileptic seizure; and

scheduling subsequent receiving at least one signal and subsequent processing the at least one signal, wherein said scheduling is based at least in part on the processing of the at least one signal.

30. The method as recited in claim 29 wherein processing the at least one electrical signal comprises performing an analysis on the at least one signal to estimate a propensity for the subject to have an epileptic seizure within a specified time horizon.

31. The method as recited in claim 30 further comprising communicating information related to the estimate of a propensity to the subject.

32. The method as recited in claim 29 wherein:

performing an analysis to estimate a propensity for the subject to have a neurological event comprises estimating a time horizon during which an estimated likelihood that the subject will have a neurological event is below a predetermined threshold; and

scheduling subsequent operations comprises determining a time when subsequent operations are to be performed, the determination of a time being based on the estimate of a time horizon during which an estimated propensity for the subject to have a neurological event is below a predetermined threshold.

33. The method as recited in claim 29 wherein processing the at least one electrical signal comprises applying at least one feature extractor to the at least one electrical signal.