Filtering noise from a signal subjected to blanking

• US 9,375,181 B2
• Filed: 10/24/2014
• Issued: 06/28/2016
• Est. Priority Date: 10/24/2014
• Status: Active Grant

• Current Assignee: Medtronic Incorporated (Medtronic Plc)
• Original Assignee: Medtronic Incorporated (Medtronic Plc)
• Inventors: Hemming, Michael T., Greenhut, Saul E.
• Primary Examiner(s): MANUEL, GEORGE C
• Application Number:
  US14/522,938
• Publication Number:
  US 20160113586A1
• Time in Patent Office: 613 Days
• US Class Current: 1/1
• CPC Class Codes: A61B 5/0538 invasively, e.g. using a catheter
• CPC Class Codes: A61B 5/1107 Measuring contraction of parts of the body, e.g. organ, muscle apparatus for measuring work or force in general G01L
• CPC Class Codes: A61B 5/316 Modalities, i.e. specific diagnostic methods
• CPC Class Codes: A61B 5/318 Heart-related electrical modalities, e.g. electrocardiography [ECG]
• CPC Class Codes: A61B 5/349 Detecting specific parameters of the electrocardiograph cycle
• CPC Class Codes: A61B 5/686 Permanently implanted devices, e.g. pacemakers, other stimulators, biochips A61B5/6861 takes precedence
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: A61N 1/365 controlled by a physiological parameter, e.g. heart potential evoked response A61N1/371
• CPC Class Codes: A61N 1/3718 Monitoring of or protection against external electromagnetic fields or currents

Abstract

The disclosure describes techniques and systems for filtering noise from a physiological signal. In one example, one or more processors are configured to receive a signal indicative of physiological activity of a patient, wherein the signal comprises noise at one or more frequencies, and filter the noise from the signal according to a noise rejection model, wherein the noise rejection model predicts the noise at the one or more frequencies. The one or more processors may also be configured to, responsive to initiation of a blanking period for the signal, advance the noise rejection model in time during the blanking period, and, responsive to termination of the blanking period, filter, based on the noise rejection model advanced in time, the noise at the one or more frequencies from the signal.

Claims

1. A method comprising:

receiving a signal indicative of physiological activity of a patient, wherein the signal comprises noise at one or more frequencies;

filtering the noise from the signal according to a noise rejection model, wherein the noise rejection model predicts the noise at the one or more frequencies;

responsive to initiation of a blanking period for the signal, advancing the noise rejection model in time during the blanking period; and

responsive to termination of the blanking period, filtering, based on the noise rejection model advanced in time, the noise at the one or more frequencies from the signal.

2. The method of claim 1, further comprising generating, from the received signal, the noise rejection model for the one or more frequencies.

3. The method of claim 2, wherein generating the noise rejection model comprises adapting, based on the received signal, the noise rejection model over time.

4. The method of claim 2, further comprising pausing the adaption of the noise rejection model during the blanking period.

5. The method of claim 2, wherein the noise rejection model comprises a finite impulse response model, and wherein the method further comprises developing the finite impulse response model using least means square adaptation.

6. The method of claim 2, wherein generating the noise rejection model comprises detecting the noise at the one or more frequencies in the received signal and modeling the detected noise.

7. The method of claim 1, wherein advancing the noise rejection model comprises:

calculating, for each of the one or more frequencies, a phase change of the noise rejection model for a duration of the blanking period; and

determining, based on the phase change in the noise rejection model, an expected phase and an expected amplitude of the noise in the received signal predictive of an actual phase and an actual amplitude of the noise in the received signal at the termination of the blanking period.

8. The method of claim 1, wherein the one of more frequencies comprises one or more of 50 Hz, 60, Hz, 100 Hz, and 120 Hz.

9. The method of claim 1, wherein the blanking period comprises a blanking period during which a pacing pulse is delivered to the patient.

10. The method of claim 1, wherein the physiological activity comprises electrical activity of a heart of the patient.

11. The method of claim 10, further comprising:

analyzing the filtered signal to detect a physiological event;

generate an electrical stimulation therapy in response to the processor detecting the physiological event; and

delivering the electrical stimulation therapy to the heart of the patient.

12. A device comprising:

a filtering module configured to;

receive a signal indicative of physiological activity of a patient, wherein the signal comprises noise at one or more frequencies;

filter the noise from the signal according to a noise rejection model, wherein the noise rejection model predicts the noise at the one or more frequencies;

responsive to initiation of a blanking period for the signal, advance the noise rejection model in time during the blanking period; and

responsive to termination of the blanking period, filter, based on the noise rejection model advanced in time, the noise at the one or more frequencies from the signal.

13. The device of claim 12, wherein the filtering module is configured to generate, from the received signal, the noise rejection model for the one or more frequencies.

14. The device of claim 13, wherein the filtering module is configured to generate the noise rejection model by adapting, based on the received signal, the noise rejection model over time.

15. The device of claim 13, wherein the noise rejection model comprises a finite impulse response model, and wherein the filtering module includes one or more processors configured to develop the finite impulse response model using least means square adaptation.

16. The device of claim 12, wherein the filtering module includes one or more processors configured to advance the noise rejection model by:

calculating, for each of the one or more frequencies, a phase change of the noise rejection model for a duration of the blanking period; and

determining, based on the phase change in the noise rejection model, an expected phase and an expected amplitude of the noise in the received signal predictive of an actual phase and an actual amplitude of the noise in the received signal at the termination of the blanking period.

17. The device of claim 12, wherein the one of more frequencies comprises one or more of 50 Hz, 60, Hz, 100 Hz, and 120 Hz.

18. The device of claim 12, wherein the physiological activity comprises electrical activity of a heart of the patient.

19. The device of claim 12, wherein the device comprises an implantable medical device, and wherein the implantable medical device comprises a housing that contains the filtering module.

20. The device of claim 12, further comprising:

a processor configured to analyze the filtered signal to detect a physiological event; and

a signal generator configured to generate an electrical stimulation therapy in response to the processor detecting the physiological event.

21. The device of claim 20, further comprising:

a housing configured to be implanted subcutaneously within the patient, wherein the filtering module, the processor, and the signal generator are contained within the housing;

an electrical stimulation lead coupled to the housing and including a plurality of electrodes configured to at least one of sense the signal indicative of physiological activity of the patient or deliver the electrical stimulation therapy to the patient.

22. The device of claim 21, wherein the electrodes of the electrical stimulation lead sense the signal indicative of the physiological activity from an extravascular location.

23. The device of claim 22, wherein the extravascular location is one of a subcutaneous location and a substernal location.

24. The device of claim 20, further comprising:

a housing sized to be implanted within a chamber of the heart and having at least two electrodes on the housing,

wherein the filtering module, the processor, and the signal generator are contained within the housing; and

wherein the at least two electrodes on the housing sense the signal indicative of the physiological activity.

25. A system comprising:

means for receiving a signal indicative of physiological activity of a patient, wherein the signal comprises noise at one or more frequencies;

means for filtering the noise from the signal according to a noise rejection model, wherein the noise rejection model predicts the noise at the one or more frequencies;

means for, responsive to initiation of a blanking period for the signal, advancing the noise rejection model in time during the blanking period; and

means for, responsive to termination of the blanking period, filtering, based on the noise rejection model advanced in time, the noise at the one or more frequencies from the signal.