Signal quality monitoring for multiple sense vectors in cardiac devices

• US 10,264,989 B2
• Filed: 10/19/2016
• Issued: 04/23/2019
• Est. Priority Date: 10/23/2015
• Status: Active Grant

• Current Assignee: Cardiac Pacemakers Incorporated (Boston Scientific Corporation)
• Original Assignee: Cardiac Pacemakers Incorporated (Boston Scientific Corporation)
• Inventors: Brisben, Amy Jean, Allavatam, Venugopal, Siejko, Krzysztof Z., Mahajan, Deepa, Wika, Kevin G., Herrmann, Keith L., Hahn, Stephen J.
• Primary Examiner(s): Tejani, Ankit D
• Application Number:
  US15/297,568
• Publication Number:
  US 20170113053A1
• Time in Patent Office: 916 Days
• Field of Search: None
• CPC Class Codes: A61B 5/02416 using photoplethysmograph signals, e.g. generated by infrared radiation A61B5/14552 takes precedence
• CPC Class Codes: A61B 5/0245 by using sensing means generating electric signals, i.e. ECG signals
• CPC Class Codes: A61B 5/283 Invasive
• 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 5/318 Heart-related electrical modalities, e.g. electrocardiography [ECG]
• CPC Class Codes: A61B 5/327 Generation of artificial ECG signals based on measured signals, e.g. to compensate for missing leads
• 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 5/364 Detecting abnormal ECG interval, e.g. extrasystoles, ectopic heartbeats
• CPC Class Codes: A61B 5/366 Detecting abnormal QRS complex, e.g. widening
• CPC Class Codes: A61B 5/686 Permanently implanted devices, e.g. pacemakers, other stimulators, biochips A61B5/6861 takes precedence
• CPC Class Codes: A61B 5/6869 Heart
• CPC Class Codes: A61B 5/72 Signal processing specially adapted for physiological signals or for diagnostic purposes character recognition, recognising digital ink, document-oriented image-based pattern recognition G06V30/00; recognition or understanding of postal images G06V30/424
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/7221 Determining signal validity, reliability or quality A61B5/7207 and A61B5/7217 take precedence
• CPC Class Codes: A61N 1/046 Specially adapted for shock therapy, e.g. defibrillation
• CPC Class Codes: A61N 1/05 for implantation or insertion into the body, e.g. heart electrode A61N1/06 takes precedence
• CPC Class Codes: A61N 1/0563 : specially adapted for defibrillation or cardioversion
• CPC Class Codes: A61N 1/3622 : comprising two or more electrodes co-operating with different heart regions
• CPC Class Codes: A61N 1/3625 : External stimulators
• CPC Class Codes: A61N 1/36514 : controlled by a physiological quantity other than heart potential, e.g. blood pressure controlled by two or more physical parameters A61N1/36585
• CPC Class Codes: A61N 1/3704 : Circuits specially adapted therefor, e.g. for sensitivity control
• 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 1/3987 : characterised by the timing or triggering of the shock

Abstract

New and alternative approaches to the monitoring of cardiac signal quality for external and/or implantable cardiac devices. In one example, signal quality is monitored continuously or in response to a triggering event or condition and, upon identification of a reduction in signal quality, a device may reconfigure its sensing state. In another example, one or more trends of signal quality are monitored by a device, either continuously or in response to a triggering event or condition, and sensing reconfiguration may be performed in response to identified trends and events. In yet another example, a device may use a looping data capture mode to track sensing data in multiple vectors while primarily relying on less than all sensing vectors to make decisions and, in response to a triggering event or condition, the looped data can be analyzed automatically, without waiting for additional data capture to reconfigure sensing upon identification of the triggering event or condition. In another example a device calculates a composite cardiac cycle by overlaying signal morphology for a number of cardiac cycles and analyzes the composite cardiac cycle to calculate signal quality metrics.

Claims

1. A cardiac rhythm management device for use with a patient having a plurality of electrodes coupled to sensing circuitry to allow a plurality of sensing configurations to be defined thereby and operational circuitry configured to perform the following:

detect cardiac cycles of the patient using a first sensing configuration;

identify a triggering event for sensing configuration analysis;

analyze data from two or more of the cardiac cycles of the patient

obtain sensing quality data from the analyzed data from the two or more cardiac cycles of the patient;

identify a trend in the sensing quality data;

track the trend to monitor an indication of a signal quality of the detected cardiac cycles;

determine that the tracked trend indicates the first sensing configuration is an unfavorable sensing configuration;

select a second sensing configuration which is not one which has been identified as unfavorable in light of the trend; and

apply the second sensing configuration to detect and analyze cardiac signal data.

2. The device of claim 1 wherein operational circuitry is configured to track the trend by:

capturing data within sensing windows defined for the trend;

calculating a composite variability factor by analysis of the data captured within each sensing window; and

finding that the variability factor indicates relatively high variability for the first configuration.

3. The device of claim 2 wherein each sensing window comprises a plurality of sample points and the variability factor is determined by calculating one or more of a variance, a standard deviation, or a range of detected signal amplitudes on a sample by sample basis within the sensing windows.

4. The device of claim 1 wherein the operational circuitry is configured to track the trend by:

calculating a signal quality metric for the trend;

observing variability of the signal quality metric for the trend; and

finding high variability of the signal quality metric.

5. The device of claim 1 wherein the operational circuitry is configured to track the trend by:

analyzing the the trend to identify one or more of noise or overdetection;

calculating a frequency with which the one or more of noise or overdetection occurs; and

finding a high frequency of occurrence of the noise or overdetection.

6. The device of claim 1 wherein the operational circuitry is configured to track the trend by:

analyzing the the trend to identify one or more of noise or overdetection;

calculating a frequency with which one or more of noise or overdetection occurs as a function of time; and

finding that the frequency of occurrence of noise or overdetection is increasing with time.

7. The device of claim 1 wherein the operational circuitry is configured to track the trend by:

calculating stability of a signal quality metric for the trend; and

identifying the stability of the signal quality metric indicated low signal quality of the detected cardiac cycles.

8. The device claim 1 wherein the device is a wearable cardiac rhythm management device.

9. The device of claim 1 wherein the device is an implantable cardiac rhythm management device adapted to deliver therapy.

10. The device of claim 1 wherein the device is an implantable cardiac monitoring device.

11. A method of operation in a cardiac rhythm management device, the device having a plurality of electrodes coupled to sensing circuitry to allow a plurality of sensing configurations to be defined thereby and operational circuitry for performing analysis of cardiac signals captured by one or more of the sensing configurations, the method comprising:

the operational circuitry detecting cardiac cycles of the patient using a first sensing configuration;

the operational circuitry identifying a triggering event for sensing configuration analysis;

the operational circuitry analyzing data from two or more of the cardiac cycles of the patient

the operational circuity obtaining sensing quality data from the analyzed data from the two or more cardiac cycles of the patient;

the operational circuitry identifying a trend in the sensing quality data;

the operational circuity tracking the trend to monitor an indication of a signal quality of the detected cardiac cycles;

the operational circuity determining that the tracked trend indicates the first sensing configuration is an unfavorable sensing configuration;

the operational circuitry selecting a second sensing configuration which is not one which has been identified as unfavorable in light of the trend; and

the operational circuitry applying the second sensing configuration to detect and analyze cardiac signal data.

12. The method of claim 11 further comprising:

the operational circuitry capturing data within sensing windows defined for the trend;

the operational circuitry calculating a composite variability factor by analysis of the data captured within each sensing window; and

the operational circuitry finding that the variability factor indicates relatively high variability for the first configuration.

13. The method of claim 11 wherein each sensing window comprises a plurality of sample points and the variability factor is determined by calculating one or more of a variance, a standard deviation, or a range of detected signal amplitudes on a sample by sample basis within the sensing windows.

14. The method of claim 11 wherein the step of tracking the trend includes:

the operational circuitry calculating a signal quality metric for the trend;

the operational circuitry observing variability of the signal quality metric for the trend; and

the operational circuitry finding high variability of the signal quality metric.

15. The method of claim 11 wherein the step of tracking the trend includes:

the operational circuitry analyzing the the trend to identify one or more of noise or overdetection;

the operational circuitry calculating a frequency with which the one or more of noise or overdetection occurs; and

the operational circuitry finding a high frequency of occurrence of the noise or overdetection.

16. The method of claim 11 wherein the step of tracking the trend includes:

the operational circuitry analyzing the the trend to identify one or more of noise or overdetection;

the operational circuitry calculating a frequency with which one or more of noise or overdetection occurs as a function of time; and

the operational circuitry finding that the frequency of occurrence of noise or overdetection is increasing with time.

17. The method of claim 11 wherein the step of tracking the trend includes:

the operational circuitry calculating stability of a signal quality metric for the trend; and

the operational circuitry identifying the stability of the signal quality metric indicated low signal quality of the detected cardiac cycles.

18. The method of claim 11 wherein the device is a wearable cardiac rhythm management device and the electrodes are placed cutaneously on the skin of the patient to capture cardiac signals for the sensing configurations.

19. The method of claim 11 wherein the device is an implantable cardiac rhythm management device adapted to deliver therapy, and the method further comprises analyzing the detected cardiac cycles to determine whether a treatable arrhythmia is present and delivering therapy in response to determining that a treatable arrhythmia is present.

20. The method of claim 11 wherein the device is an implantable cardiac monitoring device and the method comprises storing data in response to detecting an elevated cardiac rate based upon the detected cardiac cycles.