Method and apparatus for selection and use of virtual sensing vectors

• US 9,566,012 B2
• Filed: 10/27/2014
• Issued: 02/14/2017
• Est. Priority Date: 10/27/2014
• Status: Active Grant

• Current Assignee: Medtronic Incorporated (Medtronic Plc)
• Original Assignee: Medtronic Incorporated (Medtronic Plc)
• Inventors: Greenhut, Saul E., Zhang, Xusheng, Stadler, Robert W.
• Primary Examiner(s): Johnson, Nicole F
• Application Number:
  US14/524,090
• Publication Number:
  US 20160113536A1
• Time in Patent Office: 841 Days
• Field of Search: 600/512, 600/518
• US Class Current: 1/1
• 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 5/0245 by using sensing means generating electric signals, i.e. ECG signals
• CPC Class Codes: A61B 5/287 Holders for multiple electrodes, e.g. electrode catheters for electrophysiological study [EPS]
• CPC Class Codes: A61B 5/316 Modalities, i.e. specific diagnostic methods
• CPC Class Codes: A61B 5/341 Vectorcardiography [VCG]
• CPC Class Codes: A61B 5/349 Detecting specific parameters of the electrocardiograph cycle
• CPC Class Codes: A61B 5/35 by template matching
• CPC Class Codes: A61B 5/352 Detecting R peaks, e.g. for synchronising diagnostic apparatus; Estimating R-R interval
• CPC Class Codes: A61B 5/366 Detecting abnormal QRS complex, e.g. widening
• CPC Class Codes: A61B 5/4836 Diagnosis combined with treatment in closed-loop systems or methods A61B5/0036 takes precedence
• 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 5/7282 Event detection, e.g. detecting unique waveforms indicative of a medical condition A61B5/4094, A61B5/4818, A61B5/349, A61B5/0823 take precedence
• CPC Class Codes: A61N 1/3702 Physiological parameters A61N1/365 takes precedence; evoked response A61N1/371
• CPC Class Codes: A61N 1/3925 Monitoring; Protecting
• CPC Class Codes: A61N 1/3956 Implantable devices for applying electric shocks to the heart, e.g. for cardioversion
• CPC Class Codes: A61N 1/39622 Pacing therapy
• CPC Class Codes: A61N 1/3987 characterised by the timing or triggering of the shock

Abstract

A medical device is configured to receive at least two physical cardiac electrical signals from a patient'"'"'s heart via electrodes defining at least two physical sensing vectors. The medical device determines a signal feature for each of a plurality of virtual sensing vectors extending at a plurality of angles relative to one of the at least two physical sensing vectors during a known cardiac rhythm, compares the determined signal features and establishes criteria for confirming a suspected condition in response to the comparing.

Claims

1. A method performed by a medical device, comprising:

receiving at least two physical cardiac electrical signals from a patient'"'"'s heart via a plurality of electrodes that define at least two physical sensing vectors;

computing a plurality of virtual cardiac electrical signals using the at least two physical cardiac electrical signals during a first, known cardiac rhythm, each of the plurality of virtual cardiac electrical signals corresponding to one of a plurality of virtual sensing vectors extending at a respective one of a plurality of angles relative to one of the at least two physical sensing vectors, wherein computing the plurality of virtual cardiac electrical signals comprises calculating a projection of the at least two physical cardiac electrical signals along each of the plurality of virtual sensing vectors;

determining, for each of the plurality of virtual cardiac electrical signals, a plurality virtual cardiac electrical signal features;

comparing the determined signal features;

establishing criteria for confirming a suspected condition in response to the comparing;

detecting a suspected condition during a second, unknown cardiac rhythm; and

confirming the suspected condition in response to the established criteria being met during the second, unknown cardiac rhythm.

2. The method of claim 1, wherein:

establishing the criteria for confirming the suspected condition comprises determining one of the at least two physical sensing vectors and the plurality of virtual sensing vectors as a cardiac electrical axis based on the comparing during the first, known cardiac rhythm;

confirming the suspected condition comprises determining a different one of the at least two physical sensing vectors and the plurality of virtual sensing vectors as the cardiac electrical axis during the second, unknown cardiac rhythm.

3. The method of claim 2, wherein determining one of the at least two physical sensing vectors and the plurality of virtual sensing vectors as the cardiac electrical axis comprises:

identifying an isoelectric cardiac electrical signal feature from among the at least two physical sensing vectors and the plurality of virtual sensing vectors;

identifying a vector of the isoelectric cardiac electrical signal feature; and

selecting a vector orthogonal to the identified vector of the isoelectric cardiac electrical signal feature as the cardiac electrical axis.

4. The method of claim 2, wherein determining one of the at least two physical sensing vectors and the plurality of virtual sensing vectors as the cardiac electrical axis comprises:

determining a maximum peak R-wave amplitude for each of the at least two physical sensing vectors and the plurality of virtual sensing vectors;

comparing the determined maximum peak R-wave amplitudes to identify a greatest maximum peak R-wave amplitude; and

identifying the cardiac electrical axis as one of the at least two physical sensing vectors and the plurality of virtual sensing vectors having the greatest maximum peak R-wave amplitude.

5. The method of claim 1,

wherein establishing the criteria for confirming the suspected condition comprises determining a first order of at least the plurality of virtual sensing vectors based on the comparing of the signal features determined during the first, known cardiac rhythm;

the method further comprising determining a second order of at least the plurality of virtual sensing vectors based on determining and comparing the signal features for the plurality of virtual cardiac electrical signals during the second, unknown cardiac rhythm; and

wherein confirming the suspected condition comprises confirming the suspected condition in response to the first order being different than the second order.

6. The method of claim 5, wherein determining the first order and the second order comprises ranking the determined signal features from largest to smallest.

7. The method of claim 1,

wherein establishing the criteria for confirming the suspected condition comprises identifying one of the at least two physical sensing vectors and the plurality of virtual sensing vectors having a lowest T-wave window signal energy;

and

wherein confirming the suspected condition comprises;

redetermining the T-wave window signal energy during the second, unknown rhythm from the identified vector having the lowest T-wave window signal energy during the first, known cardiac rhythm; and

detecting an increase in the T-wave window signal energy of the identified vector.

8. The method of claim 7, further comprising detecting T-wave oversensing in response to the T-wave window signal energy during the second, unknown rhythm not being greater than the T-wave window signal energy during the first, known cardiac rhythm.

9. The method of claim 1, wherein establishing the criteria for confirming the suspected cardiac condition comprises:

determining the signal features for each of the at least two physical sensing vectors and the plurality of virtual sensing vectors during a third cardiac rhythm,

identifying one of the at least two physical sensing vectors and the plurality of virtual sensing vectors having a greatest difference between the signal feature determined during the first, known cardiac rhythm and the signal feature determined during the third cardiac rhythm, the first known cardiac rhythm being a non-shockable rhythm and the third cardiac rhythm being a shockable rhythm.

10. The method of claim 1, further comprising:

selecting a detection vector among the at least two physical sensing vectors and the plurality of virtual sensing vectors based on the comparing;

wherein confirming the suspected condition in response to the established criteria comprises determining a cardiac electrical signal feature of the detection vector during the second, unknown cardiac rhythm.

11. The method of claim 10, further comprising:

selecting a monitoring vector from among the at least two physical sensing vectors and the plurality of virtual sensing vectors;

wherein detecting the suspected condition comprises detecting the suspected condition in response to a signal feature of the monitoring vector.

12. The method of claim 10, wherein selecting the detection vector comprises identifying among the at least two physical sensing vectors and the plurality of virtual sensing vectors a vector having at least one of:

a lowest T-wave amplitude, a highest R-wave amplitude, a highest R-wave amplitude to T-wave amplitude ratio, a highest R-amplitude and T-wave amplitude difference, a most biphasic T-wave signal, a most monophasic R-wave signal, a lowest baseline noise metric, a highest low slope content, a highest normalized waveform area, and a lowest waveform variability metric.

13. The method of claim 1, further comprising:

detecting a plurality of different patient body posture signals during the first, known rhythm;

repeating the steps of receiving, computing, determining, comparing and establishing for each of the plurality of the patient body posture signals;

wherein confirming the suspected condition in response to the established criteria being met during the second, unknown cardiac rhythm comprises detecting a body posture signal during the second, unknown cardiac rhythm and using the criteria established during a matching one of the plurality of different patient body posture signals during the first, known cardiac rhythm.

14. The method of claim 1, wherein confirming the suspected condition comprises detecting a shockable rhythm, the method further comprising delivering a therapy to the patient'"'"'s heart in response to detecting the shockable rhythm.

15. The method of claim 1, further comprising:

detecting a plurality of cardiac events comprising suspected T-wave oversensed events in response at least one of the physical cardiac electrical signals;

for at least two of the plurality of cardiac events comprising suspected T-wave oversensed events, set a T-wave window of at least one of the virtual sensing vectors;

determine a first T-wave window signal energy and a second T-wave window signal energy of the at least one virtual sensing vector; and

confirm T-wave oversensing based on a difference between the first T-wave window signal energy and the second T-wave window signal energy.

16. The method of claim 1, further comprising:

determining the plurality of virtual cardiac electrical signal features during a third, known cardiac rhythm;

determine a long term value of each of the plurality of virtual cardiac electrical signal features using the plurality of virtual cardiac electrical signal features determined during the third, known cardiac rhythm and the plurality of virtual cardiac electrical signal features determined during the first, known cardiac rhythm;

comparing the long term values; and

selecting a vector from among the virtual sensing vectors based on comparing the long term values for use in at least one of detecting the suspected condition and confirming the suspected condition.

17. The method of claim 1, further comprising:

identifying one of the at least two physical sensing vectors and the plurality of virtual sensing vectors as a first cardiac electrical axis during the first, known cardiac rhythm based on the plurality of virtual cardiac electrical signal features determined during the first, known cardiac rhythm;

determining a plurality of virtual cardiac electrical signal features during the second, unknown cardiac rhythm;

identifying one of the at least two physical sensing vectors and the plurality of virtual sensing vectors as a second cardiac electrical axis during the second, unknown cardiac rhythm based on the plurality of virtual cardiac electrical signal features determined during the second, unknown cardiac rhythm;

determining a plurality of virtual cardiac electrical signal features during a third, known cardiac rhythm;

identifying one of the at least two physical sensing vectors and the plurality of virtual sensing vectors as a third cardiac electrical axis during the third, known cardiac rhythm based on the plurality of virtual cardiac electrical signal features determined during the third known, cardiac rhythm; and

detecting the second unknown cardiac rhythm as one of the first known cardiac rhythm and the third known cardiac rhythm in response to the second cardiac electrical axis identified during the second, unknown cardiac rhythm matching a respective one of the first cardiac electrical axis and the third cardiac electrical axis.

18. A medical device system, comprising:

a sensing module configured to receive at least two physical cardiac electrical signals via a plurality of electrodes that define at least two physical sensing vectors; and

a control module coupled to the sensing module and configured to;

compute a plurality of virtual cardiac electrical signals using the at least two physical cardiac electrical signals during a first, known cardiac rhythm, each of the plurality of virtual cardiac electrical signals corresponding to one of a plurality of virtual sensing vectors extending at a respective one of a plurality of angles relative to one of the at least two physical sensing vectors, wherein computing the plurality of virtual cardiac electrical signals comprises calculating a projection of the at least two physical cardiac electrical signals along each of the plurality of virtual sensing vectors;

determine, for each of the plurality of virtual cardiac electrical signals, a plurality of virtual cardiac electrical signal features;

comparing the determined signal features;

establishing criteria for confirming a suspected condition in response to the comparing;

detecting a suspected condition during a second, unknown cardiac rhythm; and

confirming the suspected condition in response to the established criteria being met during the second, unknown cardiac rhythm.

19. The system of claim 18, wherein the control module is configured to:

establish the criteria for confirming the suspected condition by determining one of the at least two physical sensing vectors and the plurality of virtual sensing vectors as a cardiac electrical axis based on the comparing during the first, known cardiac rhythm;

confirm the suspected condition by determining a different one of the at least two physical sensing vectors and the plurality of virtual sensing vectors as the cardiac electrical axis during the second, unknown cardiac rhythm.

20. The system of claim 19, wherein the control module is configured to determine one of the at least two physical sensing vectors and the plurality of virtual sensing vectors as the cardiac electrical axis by:

identifying an isoelectric cardiac electrical signal feature from among the at least two physical sensing vectors and the plurality of virtual sensing vectors;

identifying a vector of the isoelectric cardiac electrical signal feature; and

selecting a vector orthogonal to the identified vector of the isoelectric cardiac electrical signal feature as the cardiac electrical axis.

21. The system of claim 19, wherein the control module is configured to determine one of the at least two physical sensing vectors and the plurality of virtual sensing vectors as the cardiac electrical axis by:

determining a maximum peak R-wave amplitude for each of the at least two physical sensing vectors and the plurality of virtual sensing vectors;

comparing the determined maximum peak R-wave amplitudes to identify a greatest maximum peak R-wave amplitude; and

identifying the cardiac electrical axis as one of the at least two physical sensing vectors and the plurality of virtual sensing vectors having the greatest maximum peak R-wave amplitude.

22. The system of claim 18, wherein the control module is configured to:

establish the criteria for confirming the suspected condition by at least determining a first order of at least the plurality of virtual sensing vectors based on the comparing of the signal features determined during the first, known cardiac rhythm;

determine a second order of at least the plurality of virtual sensing vectors based on determining and comparing the signal features for the plurality of virtual cardiac electrical signals during the second, unknown cardiac rhythm; and

confirm the suspected condition in response to the first order being different than the second order.

23. The system of claim 22, wherein the control module is configured to determine the first order and the second order by ranking the determined signal features from largest to smallest.

24. The system of claim 18, wherein the control module is configured to:

establish the criteria for confirming the suspected condition by at least identifying one of the at least two physical sensing vectors and the plurality of virtual sensing vectors having a lowest T-wave window signal energy; and

confirm the suspected condition by;

redetermining the T-wave window signal energy during the second, unknown rhythm from the identified vector having the lowest T-wave window signal energy during the first, known cardiac rhythm; and

detecting an increase in the T-wave window signal energy of the identified vector.

25. The system of claim 24, wherein the control module is further configured to detect T-wave oversensing in response to the T-wave window signal energy not being greater during the second, unknown rhythm compared to the T-wave window signal energy during the first, known cardiac rhythm.

26. The system of claim 18, wherein the control module is further configured to establish the criteria for confirming the suspected cardiac condition by:

determining the signal features for each of the at least two physical sensing vectors and the plurality of virtual sensing vectors during a third cardiac rhythm,

identifying one of the at least two physical sensing vectors and the plurality of virtual sensing vectors having a greatest difference between the signal feature determined during the first, known cardiac rhythm and the signal feature determined during the third cardiac rhythm, the first known cardiac rhythm being a non-shockable rhythm and the third cardiac rhythm being a shockable rhythm.

27. The system of claim 18, wherein the control module is configured to:

select a detection vector among the at least two physical sensing vectors and the plurality of virtual sensing vectors based on the comparing;

wherein confirming the suspected condition in response to the established criteria comprises determining a cardiac electrical signal feature from the detection vector during the second, unknown cardiac rhythm.

28. The system of claim 27, wherein the control module is further configured to:

select a monitoring vector from among the at least two physical sensing vectors and the plurality of virtual sensing vectors; and

wherein detecting the suspected condition comprises detecting the suspected condition in response to a signal feature of the monitoring vector.

29. The system of claim 27, wherein the control module is configured to select the detection vector by identifying among the at least two physical vectors and the plurality of virtual sensing vectors at least one of:

a lowest T-wave amplitude, a highest R-wave amplitude, a highest R-wave amplitude to T-wave amplitude ratio, a highest R-amplitude and T-wave amplitude difference, a most biphasic T-wave signal, a most monophasic R-wave signal, a lowest baseline noise metric, a highest low slope content, a highest normalized waveform area, and a lowest waveform variability metric.

30. The system of claim 18, further comprising a posture sensor, wherein the control module is further configured to:

detect a plurality of different patient body posture signals during the first, known rhythm;

repeat the steps of receiving, computing, determining, comparing and establishing for each of the plurality of the patient body posture signals; and

confirm the suspected condition in response to the established criteria being met during the second, unknown cardiac rhythm by detecting a body posture signal during the second, unknown cardiac rhythm and using the criteria established during a matching one of the plurality of different patient body posture signals during the first, known cardiac rhythm.

31. The system of claim 18, further comprising a therapy delivery module configured to generate and deliver a therapy to the patient'"'"'s heart via the plurality of electrodes;

wherein the control module is configured to confirm the suspected condition by detecting a shockable rhythm and control the therapy delivery module to deliver the therapy in response to detecting the shockable rhythm.

32. The system of claim 18, wherein:

the sensing module is configured to detect a plurality of cardiac events comprising suspected T-wave oversensed events in response at least one of the physical cardiac electrical signals;

the control module is configured to;

for at least two of the plurality of cardiac events comprising suspected T-wave oversensed events, set a T-wave window of at least one of the virtual sensing vectors;

determine a first T-wave window signal energy and a second T-wave window signal energy of the at least one virtual sensing vector; and

confirm T-wave oversensing based on a difference between the first T-wave window signal energy and the second T-wave window signal energy.

33. The system of claim 18, wherein the control module is further configured to:

determine the plurality of virtual cardiac electrical signal features during a third, known cardiac rhythm;

determine a long term value of each of the plurality of virtual cardiac electrical signal features using the plurality of virtual cardiac electrical signal features determined during the third, known cardiac rhythm and the plurality of virtual cardiac electrical signal features determined during the first, known cardiac rhythm;

comparing the long term values; and

selecting a vector from among the virtual sensing vectors based on comparing the long term values for use in at least one of detecting the suspected condition and confirming the suspected condition.

34. The system of claim 18, wherein the control module is further configured to:

identify one of the at least two physical sensing vectors and the plurality of virtual sensing vectors as a first cardiac electrical axis during the first known cardiac rhythm based on the plurality of virtual cardiac electrical signal features determined during the first known cardiac rhythm;

determine a plurality of virtual cardiac electrical signal features during the second unknown cardiac rhythm;

identify one of the at least two physical sensing vectors and the plurality of virtual sensing vectors as a second cardiac electrical axis during the second unknown cardiac rhythm based on the plurality of virtual cardiac electrical signal features determined during the second, unknown cardiac rhythm;

determine a plurality of virtual cardiac electrical signal features during a third known cardiac rhythm;

identify one of the at least two physical sensing vectors and the plurality of virtual sensing vectors as a third cardiac electrical axis during the third, known cardiac rhythm based on the plurality of virtual cardiac electrical signal features determined during the third known cardiac rhythm; and

detect the second unknown cardiac rhythm as one of the first known cardiac rhythm and the third known cardiac rhythm in response to the second cardiac electrical axis identified during the second unknown cardiac rhythm matching a respective one of the first cardiac electrical axis and the third cardiac electrical axis.

35. The system of claim 18, further comprising a medical electrical lead coupled to the sensing module and carrying at least a portion of the plurality of electrodes.

36. A non-transitory, computer-readable storage medium comprising a set of instructions which, when executed by a control module of a medical device, cause the medical device to:

receive at least two physical cardiac electrical signals from a patient'"'"'s heart via a plurality of electrodes that define at least two physical sensing vectors;

compute a plurality of virtual cardiac electrical signals using the at least two physical cardiac electrical signals during a first, known cardiac rhythm, each of the plurality of virtual cardiac electrical signals corresponding to one of a plurality of virtual sensing vectors extending at a respective one of a plurality of angles relative to one of the at least two physical sensing vectors, wherein computing the plurality of virtual cardiac electrical signals comprises calculating a projection of the at least two physical cardiac electrical signals along each of the plurality of virtual sensing vectors;

determine, for each of the plurality of virtual cardiac electrical signals, one or more virtual cardiac electrical signal features;

compare the determined signal features;

establish criteria for confirming a suspected condition in response to the comparing;

detect a suspected condition during a second, unknown cardiac rhythm; and

confirm the suspected condition in response to the established criteria being met during the second, unknown cardiac rhythm.