IP Library Granted Patent US 11,026,631
Granted Patent B2
US 11,026,631 · App. 16/152,152 · Granted Jun 8, 2021

Methods and systems for automatically identifying detection parameters for an implantable medical device

Inventors: Felice Sun (Palo Alto, CA); Rosana Esteller (Marietta, GA); Adam Lee (Mountain View, CA)
Assignee: NeuroPace, Inc.
A61B5/686A61B5/316A61B5/369A61B5/374A61B5/4094A61B5/748A61B5/7435A61N1/36064A61N1/36135A61B5/4836A61B5/6868A61B5/7278A61B5/7282
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Quick Facts
Patent No.
US 11,026,631
App. No.
16/152,152
Granted
Jun 8, 2021
Kind
B2
Abstract

An initial set of parameters for operating one or more detection tools is automatically derived and subsequently adjusted so that each detection tool is more or less sensitive to signal characteristics in a region of interest. Detection tool(s) may be applied to physiological signals sensed from a patient (such as EEG signals) and may be configured to run in an implanted medical device that is programmable with the parameters to look for rhythmic activity, spiking, and power changes in the sensed signals, etc. A detection tool may be selected and parameter values derived in a logical sequence and/or in pairs based on a graphical representation of an activity type which may be selected by a user, for example, by clicking and dragging on the graphic via a GUI. Displayed simulations allow a user to assess what will be detected with a derived parameter set and then to adjust the sensitivity of the set or start over as desired.

Claims (31)

1. A method of deriving a parameter set which can be used to program a detection tool in an implantable medical device, the method comprising:

translating, with a computer, characteristics present in a graphical representation of a physiological signal into an initial set of operating parameters of a detection tool for detecting similar characteristics when they occur in physiological signals sensed from a patient, wherein translating comprises:

analyzing the characteristics present in at least one region of interest in the graphical representation to determine from among a plurality of different activity types, a determined activity type with which to characterize the at least one region of interest, the plurality of different activity types comprising rhythmic activity, spiking activity, and a change in power of the physiological signal compared to a predetermined norm,

automatically selecting a type of detection tool based on the determined activity type, and

further analyzing the at least one region of interest to automatically derive an initial set of operating parameters for the selected type of detection tool;

simulating, with a computer, a physiological activity that the detection tool operating with the initial set of operating parameters of the detection tool would detect;

adjusting, with a computer, one or more values of the parameters in the initial set to modify a sensitivity of the detection tool so that it detects more or less of desired ones of the characteristics; and

generating, with a computer, a final set of operating parameters of the detection tool based on the adjusting.

2. The method of claim 1 , further comprising programming an implantable medical device with the final set of operating parameters.

3. The method of claim 1 , wherein the detection tool is one of a half wave detector configured to look for rhythmic activity, a half wave detector configured to look for spiking activity and a line length detector configured to look for a power change.

4. The method of claim 1 , further comprising displaying, with a computer, the simulation over a graphical user interface.

5. The method of claim 1 , wherein the determined activity type is rhythmic activity, the type of detection tool is a half wave detector, and the initial set of operating parameters comprises one or more of a half wave hysteresis parameter, a minimum half wave amplitude parameter, a minimum half wave width parameter, a half wave count criterion parameter, a half wave window size parameter, a qualified analysis window count parameter, and a detection analysis window size parameter.

6. The method of claim 1 , wherein the determined activity type is spiking activity, the type of detection tool is a half wave detector, and the initial set of operating parameters comprise one or more of a half wave hysteresis parameter, a minimum half wave amplitude parameter, a minimum half wave width parameter, a half wave count criterion parameter, a half wave window size parameter, a qualified analysis window count parameter, and a detection analysis window size parameter.

7. The method of claim 1 , wherein the determined activity type is an activity corresponding to a change in power of the physiological signal compared to a predetermined norm, the type of detection tool is a line length detector, and the initial set of operating parameters comprises one or more of a value of a short term window size parameter, a value of a long term window size parameter, a value of a detection threshold parameter, a value of a threshold logic parameter, a value of a threshold mode parameter, a value of a sample count parameter, a value of an inter-sample interval parameter, and a value of a persistence parameter.

8. The method of claim 1 , further comprising receiving, with a computer, an input corresponding to a desired sensitivity of the detection tool.

9. A system for deriving a parameter set which can be used to program a detection tool in an implantable medical device, the system comprising:

a memory; and

a processor coupled to the memory and configured to:

translate characteristics present in a graphical representation of a physiological signal into an initial set of operating parameters of a detection tool for detecting similar characteristics when they occur in physiological signals sensed from a patient, wherein the processor is configured to translate by being further configured to:

analyze the characteristics present in at least one region of interest in the graphical representation to determine from among a plurality of different activity types, a determined activity type with which to characterize the at least one region of interest, the plurality of different activity types comprising rhythmic activity, spiking activity, and a change in power of the physiological signal compared to a predetermined norm,

automatically select a type of detection tool based on the determined activity type, and

further analyze the at least one region of interest to automatically derive an initial set of operating parameters for the selected type of detection tool;

simulate a physiological activity that the detection tool operating with the initial set of operating parameters of the detection tool would detect;

adjust one or more values of the parameters in the initial set to modify a sensitivity of the detection tool so that it detects more or less of desired ones of the characteristics; and

generate a final set of operating parameters of the detection tool based on the adjusting.

10. The system of claim 9 , wherein the detection tool is one of a half wave detector configured to look for rhythmic activity, a half wave detector configured to look for spiking activity and a line length detector configured to look for a power change.

11. The system of claim 9 , further comprising a graphical user interface, wherein the processor is further configured to display the simulation over the graphical user interface.

12. The system of claim 9 , wherein the determined activity type is rhythmic activity, the type of detection tool is a half wave detector, and the initial set of operating parameters comprises one or more of a half wave hysteresis parameter, a minimum half wave amplitude parameter, a minimum half wave width parameter, a half wave count criterion parameter, a half wave window size parameter, a qualified analysis window count parameter, and a detection analysis window size parameter.

13. The system of claim 9 , wherein the determined activity type is spiking activity, the type of detection tool is a half wave detector, and the initial set of operating parameters comprise one or more of a half wave hysteresis parameter, a minimum half wave amplitude parameter, a minimum half wave width parameter, a half wave count criterion parameter, a half wave window size parameter, a qualified analysis window count parameter, and a detection analysis window size parameter.

14. The system of claim 9 , wherein the determined activity type is an activity corresponding to a change in power of the physiological signal compared to a predetermined norm, the type of detection tool is a line length detector, and the initial set of operating parameters comprises one or more of a value of a short term window size parameter, a value of a long term window size parameter, a value of a detection threshold parameter, a value of a threshold logic parameter, a value of a threshold mode parameter, a value of a sample count parameter, a value of an inter-sample interval parameter, and a value of a persistence parameter.

15. The system of claim 9 , further comprising a graphical user interface, wherein the processor is further configured to receive, through the graphical user interface, an input corresponding to a desired sensitivity of the detection tool.

Assignments (5)
SECURITY INTEREST Recorded Jun 25, 2025
From: NEUROPACE, INC.
To: MIDCAP FUNDING IV TRUST
Reel/Frame 071712/0422 →
RELEASE OF SECURITY INTEREST Recorded Jun 4, 2025
From: CRG SERVICING LLC AS SUCCESSOR TO CAPITAL ROYALTY PARTNERS II L.P., CAPITAL ROYALTY PARTNERS II - PARALLEL FUND "A" L.P., AND PARALLEL INVESTMENT OPPORTUNITIES PARTNERS II L.P.
To: NEUROPACE INC.
Reel/Frame 071495/0800 →
SECURITY INTEREST Recorded Sep 25, 2020
From: NEUROPACE, INC.
To: CRG SERVICING LLC
Reel/Frame 053885/0932 →
SECURITY INTEREST Recorded Apr 4, 2019
From: NEUROPACE, INC.
To: CRG SERVICING LLC
Reel/Frame 049466/0517 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 10, 2018
From: SUN, FELICE; ESTELLER, ROSANA; LEE, ADAM
To: NEUROPACE, INC.
Reel/Frame 047124/0744 →