阅读说明：本技术 用于识别假r-r间隔和假心律不齐检测的方法、设备和系统 (Method, apparatus and system for identifying false R-R intervals and false arrhythmia detection ) 是由 N.巴迪 J.吉尔 R.余 于 2021-06-02 设计创作，主要内容包括：本文描述了用于识别由于R波感测不足或间歇性AV传导阻滞引起的假R-R间隔和假心律不齐检测的方法、设备和系统。响应于R-R间隔的持续时间大于第一特定阈值,并且R-R间隔的持续时间作为获得其信息的至少X个其他R-R间隔的整数倍在第二指定阈值内,来将一个或多个R-R间隔中的每个R-R间隔分类为假R-R间隔,其中整数倍至少为2,并且其中X是1或更大的指定整数。当对致使潜在的心律不齐发作的检测的窗口中的R-R间隔执行分类时,分类的结果可以被用于确定潜在的心律不齐发作是否为假阳性检测。(Methods, devices, and systems are described herein for identifying false R-R intervals and false cardiac arrhythmia detection due to R-wave undersensing or intermittent AV conduction block. In response to the duration of an R-R interval being greater than a first particular threshold and the duration of the R-R interval being within a second specified threshold as an integer multiple of at least X other R-R intervals for which information is obtained, classify each of the one or more R-R intervals as a false R-R interval, wherein the integer multiple is at least 2, and wherein X is a specified integer of 1 or greater. When classification is performed on the R-R intervals in the window of detection that causes a potential arrhythmia episode, the results of the classification may be used to determine whether the potential arrhythmia episode is a false positive detection.)

1. A method for use by a device or system for monitoring cardiac activity, the method comprising:

obtaining information for at least three R-R intervals, wherein each R-R interval has a respective duration, and each R-R interval may be a true R-R interval or a false R-R interval; and is

Classifying one of the R-R intervals as a false R-R interval in response to both:

(i) determining that a duration of one of the R-R intervals is greater than a first specified threshold, an

(ii) Determining that a duration of one of the R-R intervals is within a second specified threshold as an integer multiple of at least X other R-R intervals for which information is obtained, wherein the integer multiple is at least 2,

and wherein X is a specified integer of 1 or greater.

2. The method of claim 1, wherein the other R-R intervals used in (ii) determining the duration of one of the R-R intervals as an integer multiple of at least X other R-R intervals within a second specified threshold comprise at least N adjacent R-R intervals, where N is a specified integer of 6 or greater, and N is greater than X.

3. The method of claim 2, wherein the at least N adjacent R-R intervals include at least M immediately preceding R-R intervals and at least M immediately succeeding R-R intervals, where M is a specified integer of 3 or greater.

4. The method of claim 2, wherein (ii) determining that the duration of the R-R interval is within the second specified threshold as an integer multiple of the duration of at least X adjacent R-R intervals comprises: for each of the at least X adjacent R-R intervals:

determining a ratio of a duration of an R-R interval to a duration of an adjacent R-R interval;

rounding the ratio to its nearest integer to produce a rounded ratio;

determining that the rounded ratio has a value of at least 2;

determining an indication of a difference between the R-R interval and the rounded ratio having a value of at least 2; and

determining that an indication of a difference between the R-R interval and the rounded ratio is within a difference threshold that includes the second specified threshold.

5. The method of any of claims 1-4, wherein the first specified threshold is 600ms, and (i) determining that the duration of one of the R-R intervals is greater than the first specified threshold comprises determining that the duration of one of the R-R intervals is greater than 600 ms.

6. The method of any of claims 1 to 4, wherein:

the at least three R-R intervals are included in a window that causes detection of a potential arrhythmia episode; and is

The method also includes using the results of the classifying to determine whether the potential arrhythmia episode is a false positive detection.

7. The method of claim 6, wherein using the results of the classification to determine whether a potential arrhythmia episode is a false positive comprises:

determining whether at least a threshold amount of R-R intervals within a window of detection that causes a potential arrhythmia episode are classified as false R-R intervals; and

using the results of the classification to determine whether a potential arrhythmia episode is a false positive detection is further based on: it is determined whether at least a threshold number of R-R intervals within a window of detection that causes the potential arrhythmia episode are classified as false R-R intervals.

8. The method of claim 7, wherein the potential arrhythmia episode includes a potential AF or VF episode, and wherein using the results of the classifying to determine whether the potential AF or VF episode is a false positive further comprises:

removing all R-R intervals classified as false R-R intervals from the window that caused detection of a potential AF or VF episode;

determining a median indicator of interval-to-interval differences for R-R intervals remaining in the window after the removing; and

a potential AF or VF episode is determined to be a false positive based on the median indicator of the interval-to-interval difference being less than another specified threshold.

9. The method of claim 1, further comprising:

grouping the R-R intervals into two or more groups based on the duration of the R-R intervals, such that R-R intervals that are within a third specified threshold of each other are grouped into the same group; and

classifying a group including the maximum number of R-R intervals as a dominant group;

wherein the other R-R intervals used in (ii) determining that the duration of one of the R-R intervals is within a second specified threshold as an integer multiple of at least X other R-R intervals comprise R-R intervals within the dominant group.

10. The method of claim 9, wherein:

the grouping results in a histogram comprising a plurality of bins, each bin corresponding to a group comprising R-R intervals within a third specified threshold of each other; and

classifying the one group as a dominant group by identifying a group corresponding to an interval of the histogram having a largest number of R-R intervals therein.

11. An apparatus, comprising:

one or more electrodes;

sensing circuitry coupled to the one or more electrodes and configured to obtain a signal indicative of cardiac electrical activity; and

at least one of a processor or a controller configured to:

determining information of at least three R-R intervals included in the signal based on the signal indicative of cardiac electrical activity, wherein each R-R interval has a respective duration and each R-R interval may be a true R-R interval or a false R-R interval,

determining whether a duration of one of the R-R intervals is greater than a first specified threshold,

determining whether a duration of one of the R-R intervals is within a second specified threshold as an integer multiple of at least X other R-R intervals for which information is obtained, wherein the integer multiple is at least 2, and wherein X is a specified integer of 1 or more, and

determining whether to classify one of the R-R intervals as a false R-R interval based on whether the duration of the one of the R-R intervals is determined to be greater than the first specified threshold and based on whether the duration of the one of the R-R intervals is determined to be within a second specified threshold as an integer multiple of at least X other R-R intervals for which information is obtained.

12. The apparatus of claim 11, wherein other R-R intervals within a second specified threshold that are used to determine whether the duration of one of the R-R intervals is an integer multiple of at least X other R-R intervals comprise at least N adjacent R-R intervals, where N is a specified integer of 6 or greater, and N is greater than X.

13. The apparatus of claim 12, wherein the at least N adjacent R-R intervals comprise at least M immediately preceding R-R intervals and at least M immediately succeeding R-R intervals, where M is a specified integer of 3 or greater.

14. The apparatus of claim 12, wherein to determine whether a duration of an R-R interval is within a second specified threshold as an integer multiple of a duration of at least X adjacent R-R intervals, at least one of the processor or controller is configured to, for each of the at least X adjacent R-R intervals:

determining a ratio of a duration of an R-R interval to a duration of an adjacent R-R interval;

rounding the ratio to its nearest integer to produce a rounded ratio;

determining whether the value of the rounded ratio is at least 2;

determining an indication of a difference between the R-R interval and the rounded ratio having a value of at least 2 if the rounded ratio has a value of at least 2; and

determining whether an indication of a difference between the R-R interval and the rounded ratio is within a difference threshold that includes the second specified threshold.

15. The apparatus of any of claims 11 to 14, wherein:

the at least three R-R intervals are included in a window that causes detection of a potential arrhythmia episode; and

at least one of the processor or controller is configured to determine whether a potential arrhythmia episode is false positive based on whether at least a threshold amount of R-R intervals within a window of detection causing the potential arrhythmia episode are classified as false R-R intervals.

16. The device of claim 15, wherein the potential arrhythmia episode includes a potential AF or VF episode, and wherein at least one of the processor or controller is configured to:

removing all R-R intervals classified as false R-R intervals from the window of detection that caused the potential AF or VF onset, thereby producing a corrected window;

determining a median indicator of interval-to-interval differences for R-R intervals remaining in the window after the removing; and

determining that a potential AF or VF onset is a false positive based on the median indicator of the interval-to-interval difference being less than another specified threshold.

17. The device of any of claims 11 to 14, wherein at least one of the processor or controller is configured to:

grouping the R-R intervals into two or more groups based on the duration of the R-R intervals, such that R-R intervals that are within a third specified threshold of each other are grouped into the same group; and

classifying a group including the maximum number of R-R intervals as a dominant group;

wherein the other R-R intervals used to determine whether the duration of one of the R-R intervals is within a second specified threshold as an integer multiple of at least X other R-R intervals comprise R-R intervals within the dominant group.

18. The apparatus of claim 11, wherein the apparatus comprises: an IMD including telemetry circuitry configured to enable the implantable medical device IMD to communicate with an external device; and a memory configured to store data corresponding to one or more arrhythmia episodes detected by the IMD, and wherein at least one of the processor or controller is further configured to at least one of:

prevent the telemetry circuitry from transmitting data corresponding to potential arrhythmia episodes detected by the IMD but later determined by the IMD to be false positive detection to an external device communicatively coupled to a patient care network;

allowing overwriting in the memory of data corresponding to potential arrhythmia episodes detected by the IMD but later determined by the IMD to be false positive detection; or

Preventing data corresponding to potential arrhythmia episodes detected by the IMD but later determined by the IMD to be a false positive detection from being stored in the memory.

19. A method for determining whether to classify a detection of an episode of potential atrial fibrillation AF or ventricular fibrillation VF as a false positive detection, comprising:

obtaining information of R-R intervals included in a window that causes detection of a potential AF or VF episode, wherein each R-R interval has a respective duration and may be a true R-R interval or a false R-R interval;

for each R-R interval of a plurality of R-R intervals included in the window, classifying the R-R interval as a false R-R interval associated with R-wave undersensing or AV conduction block in response to both:

determining that the duration of the R-R interval is greater than a first specified threshold, an

Determining that a duration of an R-R interval is within a second specified threshold as an integer multiple of at least X other R-R intervals for which information is obtained, wherein the integer multiple is at least 2, and wherein X is a specified integer of 1 or greater; and

the detection of a potential AF or VF episode is classified as a false positive detection in response to both:

at least a first threshold amount of R-R intervals within a window that causes detection of a potential AF or VF onset are classified as false R-waves associated with R-wave undersensing or AV conduction block, an

A median indicator of interval-to-interval differences of R-R intervals within the window that are not classified as false R-waves associated with R-wave undersensing or AV conduction block is greater than another specified threshold.

20. The method of claim 19, wherein the method is performed by an implantable medical device, IMD, and further comprising at least one of:

the IMD prevents transmission of data corresponding to potential AF or VF episodes detected by the IMD but later determined by the IMD to be false positive detection to an external device communicatively coupled to the patient care network;

the IMD allows overwriting of stored data corresponding to potential AF or VF episodes detected by the IMD but later determined by the IMD to be false positive detections; or

The IMD does not store data in memory corresponding to potential AF or VF episodes that were detected by the IMD but later determined by the IMD to be false positive detections.

21. An apparatus, comprising:

one or more electrodes;

sensing circuitry coupled to the one or more electrodes and configured to obtain a signal indicative of cardiac electrical activity; and

at least one of a processor or a controller configured to determine, based on the signal indicative of cardiac electrical activity, information of R-R intervals included in a window that causes detection of an onset of potential Atrial Fibrillation (AF) or Ventricular Fibrillation (VF), wherein each R-R interval has a respective duration and may be a true R-R interval or a false R-R interval;

for each R-R interval of a plurality of R-R intervals included in a window, classifying the R-R interval as a false R-R interval associated with R-wave undersensing or AV conduction block in response to both:

the duration of the R-R interval is greater than a first specified threshold, an

The duration of an R-R interval is within a second specified threshold as an integer multiple of at least X other R-R intervals for which information is obtained, wherein the integer multiple is at least 2, and wherein X is a specified integer of 1 or greater; and

the detection of a potential AF or VF episode is classified as a false positive detection in response to both:

at least a first threshold amount of R-R intervals within a window that causes detection of a potential AF or VF onset are classified as false R-waves associated with R-wave undersensing or AV conduction block, an

A median indicator of interval-to-interval differences of R-R intervals within the window that are not classified as false R-waves associated with R-wave undersensing or AV conduction block is greater than another specified threshold.

22. The apparatus of claim 21, wherein the apparatus comprises: an IMD including telemetry circuitry configured to enable the implantable medical device IMD to communicate with an external device; and a memory configured to store data corresponding to one or more arrhythmia episodes detected by the IMD, and wherein at least one of the processor or controller is further configured to at least one of:

prevent the telemetry circuitry from transmitting data corresponding to potential AF or VF episodes detected by the IMD but later determined by the IMD to be false positive detections to an external device communicatively coupled to a patient care network;

allowing overwriting in memory of data corresponding to potential episodes of AF or VF that were detected by the IMD but later determined by the IMD to be false positive detection; or

Data corresponding to potential AF or VF episodes that are detected by the IMD but are later determined by the IMD to be false positive detections is prevented from being stored in memory.

Technical Field

Embodiments described herein relate to techniques for identifying false R-R intervals and false cardiac arrhythmia detection due to R-wave undersensing or intermittent AV conduction block. The embodiments described herein may also be used to improve initial arrhythmia detection and to detect potential AV conduction blocks.

Priority requirement

The present application claims priority from U.S. non-provisional patent application No.17/319,847 filed on 13/5/2021, U.S. provisional patent application No.63/033,815 filed on 2/6/2020, and U.S. provisional patent application No.63/043,932 filed on 25/6/2020, each of which is incorporated herein by reference.

Background

Various types of Implantable Medical Devices (IMDs) are used to monitor cardiac arrhythmias. Some types of IMDs, such as implantable cardiac pacemakers and Implantable Cardiac Defibrillators (ICDs), are capable of providing appropriate therapy in response to a detected cardiac arrhythmia. Other types of IMDs, such as an insertion heart monitor (ICM), are used for diagnostic purposes. ICMs have been increasingly used to diagnose cardiac arrhythmias, particularly Atrial Fibrillation (AF).

Atrial Fibrillation (AF) is a very common type of supraventricular tachycardia (SVT), which causes about one-fifth of all strokes and is the major risk factor for ischemic strokes. However, AF is often asymptomatic and intermittent, which often results in failure to make proper diagnosis and/or treatment in a timely manner. To overcome this problem, many cardiac devices, such as ICMs, now monitor AF by obtaining an Electrogram (EGM) signal and measuring R-R interval variability based on the EGM signal. For example, the ICM or other IMD may compare the measure of R-R interval variability to a variability threshold to automatically detect AF when the variability threshold is exceeded. In practice, ICM identifies AF primarily by quantifying the variability of the R-R interval (i.e., by quantifying the variability of ventricular contraction timing). Other types of episodes of arrhythmia may additionally or alternatively be detected based on the detected R-R intervals, such as, but not limited to, tachycardia, bradycardia, cardiac arrest (also known as asystole), and Ventricular Fibrillation (VF).

When an AF episode or some other type of arrhythmia episode is detected by the IMD, information regarding the arrhythmia episode may be recorded and corresponding EGM segments (and/or other information) may be transmitted from the IMD to a patient care network for review by a clinician. False positive arrhythmia detection (e.g., false positive AF detection) is highly undesirable because the burden of classifying by a large number of clinically irrelevant arrhythmia episodes can be time consuming and expensive.

In various IMDs, such as ICMs, clinicians have the ability to program an R-wave sensing threshold against which a sample of an EGM is compared to detect R-waves in the EGM. If the IMD exhibits sufficient R-wave amplitude upon implantation and subsequent access, the clinician tends to maintain the R-wave sensing threshold at its nominal value. However, depending on various factors (such as the angle of implantation of the IMD relative to the heart), the R-wave amplitude may change dynamically and may sometimes be too small to be detected. Unless the clinician lowers the programmable R-wave sensing threshold to correct for this problem, this can result in insufficient R-wave sensing. In other cases, oversensing of P-waves and/or T-waves due to P-wave and/or T-wave amplitudes exceeding the R-wave sensing threshold may cause the clinician to raise the programmable R-wave sensing threshold, which may also result in inadequate sensing at the R-wave. Such R-wave undersensing, P-wave oversensing, and/or T-wave oversensing may lead to false positive detection of arrhythmias (such as AF). Another cause of false positive detection of arrhythmias, such as AF, is intermittent Atrioventricular (AV) conduction block, which results in intermittent absence of R-waves. While the R-R interval sensed by the IMD during intermittent AV conduction block may be correct, this phenomenon can also lead to R-R interval variability that leads to false positive detection of AF or VF. Thus, there remains a need to improve arrhythmia detection specificity, such as, but not limited to, AF and VF detection specificity.

Disclosure of Invention

Methods, devices, and systems are described herein for identifying false R-R intervals and false cardiac arrhythmia detection due to R-wave undersensing or intermittent AV conduction block. The embodiments described herein may also be used to improve initial arrhythmia detection and to detect potential AV conduction blocks. According to some embodiments, a method comprises: obtaining information for at least three R-R intervals, wherein each R-R interval has a respective duration, and each R-R interval may be a true R-R interval or a false R-R interval; and classifying one of the R-R intervals as a false R-R interval in response to both: (i) determining that a duration of one of the R-R intervals is greater than a first specified threshold and (ii) determining that the duration of one of the R-R intervals is within a second specified threshold as an integer multiple of at least X other R-R intervals for which information is obtained, wherein the integer multiple is at least 2, and wherein X is a specified integer of 1 or greater. In the case where this method is used to identify one or more false R-R intervals, the false R-R intervals are assumed to be associated with R-wave undersensing or AV conduction block.

According to some embodiments, the other R-R intervals used in (ii) determining that the duration of one of the R-R intervals is within the second specified threshold as an integer multiple of at least X other R-R intervals comprise at least N adjacent R-R intervals, where N is a specified integer of 6 or greater, and N is greater than X. In accordance with certain such embodiments, the at least N adjacent R-R intervals include at least M immediately preceding R-R intervals and at least M immediately succeeding R-R intervals, where M is a specified integer of 3 or greater.

According to some embodiments, (ii) determining that the duration of one of the R-R intervals is within the second specified threshold as an integer multiple of at least X adjacent R-R intervals comprises: for each adjacent R-R interval of at least X adjacent R-R intervals: determining a ratio of a duration of an R-R interval to a duration of an adjacent R-R interval; rounding the ratio to its nearest integer to produce a rounded ratio; determining a rounded ratio value of at least 2; determining an indication of a difference between the R-R interval and a rounded ratio having a value of at least 2; and determining that an indication of a difference between the R-R interval and the rounded ratio is within a difference threshold that includes a second specified threshold.

According to some embodiments, the first specified threshold is 600ms, and (i) determining that the duration of one of the R-R intervals is greater than the first specified threshold comprises determining that the duration of one of the R-R intervals is greater than 600 ms. According to some embodiments, the second specified threshold is a percentage, such as, but not limited to, 10%.

According to some embodiments, the at least three R-R intervals (for which information is obtained) are R-R intervals included in a window that causes detection of a potential arrhythmia episode (e.g., a potential AF episode); and the method further includes using the results of the classification to determine whether the potential arrhythmia episode (e.g., potential AF episode) is a false positive. According to some embodiments, using the results of the classification to determine whether the potential arrhythmia episode is a false positive comprises: determining whether at least a threshold amount of R-R intervals within a window of detection that causes a potential arrhythmia episode are classified as false R-R intervals (associated with R-wave undersensing or AV block); and using the results of the classification to determine whether the potential arrhythmia episode is a false positive detection is further based on: it is determined whether at least a threshold amount of R-R intervals within a window of detection that causes a potential AF episode are classified as false R-R intervals. According to some embodiments, using the results of the classifying to determine whether the potential episode of AF or VF is a false positive when the potential episode of arrhythmia is a potential episode of AF or VF further comprises: removing all R-R intervals classified as false R-R intervals (associated with R-wave undersensing or AV conduction block) from the window of detection that caused the potential AF or VF episode, thereby producing a corrected window; after removal, determining a median indicator of interval-to-interval differences for the remaining R-R intervals in the window; and determining that the potential AF or VF episode is a false positive based on the median indicator of the interval-to-interval difference being less than another specified threshold.

According to some embodiments, the method includes grouping the R-R intervals into two or more groups based on the duration of the R-R intervals, such that R-R intervals that are within a third specified threshold of each other are grouped into the same group; and classifying a group including the largest number of R-R intervals as a dominant group. In such an embodiment, the other R-R intervals used in (ii) determining that the duration of one of the R-R intervals is within the second specified threshold as an integer multiple of at least X other R-R intervals comprise R-R intervals within the dominant group. According to some such embodiments, the grouping results in a histogram comprising a plurality of bins, each bin corresponding to a group of R-R intervals included within a third specified threshold (e.g., 15%) of each other; and classifying the one group as a dominant group by identifying a group corresponding to an interval of the histogram having a largest number of R-R intervals therein.

Certain embodiments of the present technology are directed to an apparatus including one or more electrodes, a sensing circuit, and at least one of a processor or a controller. Sensing circuitry is coupled to one or more electrodes and configured to obtain a signal indicative of cardiac electrical activity, such as an EGM or Electrocardiogram (ECG). At least one of the processor or the controller is configured to: determining information for at least three R-R intervals included in the signal based on the signal indicative of cardiac electrical activity, wherein each R-R interval has a respective duration and each R-R interval may be a true R-R interval or a false R-R interval; determining whether a duration of one of the R-R intervals is greater than a first specified threshold; determining whether a duration of one of the R-R intervals is within a second specified threshold as an integer multiple of at least X other R-R intervals for which information is obtained, wherein the integer multiple is at least 2, and wherein X is a specified integer of 1 or greater; and determining whether to classify one of the R-R intervals as a false R-R interval based on whether the duration of the one of the R-R intervals is determined to be greater than a first specified threshold and based on whether the duration of the one of the R-R intervals is determined to be within a second specified threshold as an integer multiple of at least X other R-R intervals for which information is obtained.

According to some embodiments, the other R-R intervals used to determine whether the duration of one of the R-R intervals is within the second specified threshold as an integer multiple of at least X other R-R intervals comprise at least N adjacent R-R intervals, where N is a specified integer of 6 or greater, and N is greater than X. In accordance with certain such embodiments, the at least N adjacent R-R intervals include at least M immediately preceding R-R intervals and at least M immediately succeeding R-R intervals, where M is a specified integer of 3 or greater.

According to some embodiments, to determine whether the duration of one of the R-R intervals is within the second specified threshold as an integer multiple of the duration of at least X adjacent R-R intervals, at least one of the processor or the controller is configured to, for each of the at least X adjacent R-R intervals: determining a ratio of a duration of an R-R interval to a duration of an adjacent R-R interval; rounding the ratio to its nearest integer to produce a rounded ratio; determining whether the value of the rounded ratio is at least 2; determining an indication of a difference between the R-R interval and the rounded ratio having a value of at least 2 if the rounded ratio has a value of at least 2; and determining whether an indication of a difference between the R-R interval and the rounded ratio is within a difference threshold that includes a second specified threshold.

According to certain embodiments, at least three R-R intervals (for which information is obtained) are included in the window that causes detection of a potential arrhythmia episode, and at least one of the processor or the controller is configured to: determining whether the potential arrhythmia episode is a false positive based on whether at least a threshold amount of R-R intervals within a window of detection that causes the potential arrhythmia episode are classified as false R-R intervals. According to some such embodiments, at least one of the processor or the controller is configured to: removing all R-R intervals classified as false R-R intervals from the window of detection that caused the potential AF or VF onset, thereby producing a corrected window; after removal, determining a median indicator of interval-to-interval differences for the remaining R-R intervals in the window; and determining that the potential AF or VF episode is a false positive based on the median indicator of the interval-to-interval difference being less than another specified threshold.

According to some embodiments, at least one of the processor or the controller is configured to: grouping the R-R intervals into two or more groups based on the duration of the R-R intervals, such that R-R intervals that are within a third specified threshold of each other are grouped into the same group; and classifying a group including the maximum number of R-R intervals as a dominant group; wherein the other R-R intervals used to determine whether the duration of one of the R-R intervals is within the second specified threshold as an integer multiple of at least X other R-R intervals comprise R-R intervals within the dominant group.

According to certain embodiments, a device includes an Implantable Medical Device (IMD) including telemetry circuitry configured to enable the IMD to communicate with an external device, and a memory configured to store data corresponding to one or more arrhythmia episodes detected by the IMD. In certain such embodiments, at least one of the processor or the controller is further configured to at least one of: prevent the telemetry circuitry from transmitting data corresponding to potential arrhythmia episodes detected by the IMD but later determined by the IMD to be false positive detections to an external device communicatively coupled to a patient care network; allowing overwriting in memory of data corresponding to potential arrhythmia episodes detected by the IMD but later determined by the IMD to be false positive; or prevent storage in memory of data corresponding to potential arrhythmia episodes detected by the IMD but later determined by the IMD to be false positive detection.

Certain embodiments of the present technology are directed to a method for determining whether to classify a detection of a potential arrhythmia episode as a false positive detection. Such a method may include: information is obtained for at least three R-R intervals included in a window of detection causing the onset of the potential arrhythmia, where each R-R interval has a respective duration and each R-R interval may be a true R-R interval or a false R-R interval. The method may further include, for each R-R interval of a plurality of R-R intervals included in the window, classifying the R-R interval as a false R-R interval associated with R-wave undersensing or AV conduction block in response to both: determining that a duration of the R-R interval is greater than a first specified threshold; and determining that the duration of the R-R interval is within a second specified threshold as an integer multiple of at least X other R-R intervals for which information is obtained, wherein the integer multiple is at least 2, and wherein X is a specified integer of 1 or greater. The method may further comprise classifying detection of a potential AF or VF episode as a false positive detection in response to both: at least a first threshold amount of R-R intervals within a window of detection that causes a potential AF or VF onset are classified as false R-R intervals associated with R-wave undersensing or AV conduction block; and a median indicator of interval-to-interval differences of R-R intervals within the window that are not classified as false R-waves associated with R-wave undersensing or AV conduction block is greater than another specified threshold.

Certain embodiments of the present technology are directed to a device comprising one or more electrodes, sensing circuitry coupled to the one or more electrodes and configured to obtain a signal indicative of cardiac electrical activity, and at least one of a processor or a controller. The processor and/or controller is configured to determine, based on the signal indicative of cardiac electrical activity, information of R-R intervals included in a window that causes detection of a potential AF or VF episode, wherein each R-R interval has a respective duration, and each R-R interval may be a true R-R interval or a false R-R interval. The processor and/or controller is further configured to, for each of a plurality of R-R intervals included in the window, classify the R-R interval as a false R-R interval associated with R-wave undersensing or AV conduction block in response to both: the duration of the R-R interval is greater than a first specified threshold, and the duration of the R-R interval is within a second specified threshold as an integer multiple of at least X other R-R intervals for which information is obtained, wherein the integer multiple is at least 2, and wherein X is a specified integer of 1 or greater. The processor and/or controller is further configured to classify a detection of a potential AF or VF episode as a false positive detection in response to both: at least a first threshold amount of R-R intervals within a window that causes detection of a potential AF or VF episode are classified as false R-waves associated with R-wave undersensing or AV conduction block, and a median indicator of interval-to-interval differences of R-R intervals within the window that are not classified as false R-waves associated with R-wave undersensing or AV conduction block is greater than another specified threshold. According to certain embodiments, a device includes an IMD including telemetry circuitry configured to enable the IMD to communicate with an external device, and a memory configured to store data corresponding to one or more arrhythmia episodes detected by the IMD.

According to certain embodiments, the processor and/or controller of the IMD is further configured to at least one of: prevent the telemetry circuitry from transmitting data corresponding to potential AF or VF episodes detected by the IMD but later determined by the IMD to be false positive detections to an external device communicatively coupled to the patient care network; allowing overwriting in memory of data corresponding to potential episodes of AF or VF that were detected by the IMD but later determined by the IMD to be false positive detection; or prevent the storage in memory of data corresponding to potential AF or VF episodes that were detected by the IMD but later determined by the IMD to be false positive detections.

This summary is not intended to be a complete description of embodiments of the present technology. Other features and advantages of embodiments of the present technology will become apparent from the following description, taken in conjunction with the accompanying drawings and the claims, in which preferred embodiments are set forth in detail.

Drawings

Fig. 1 includes a portion of an EGM segment for AF detection due to an undersensing R-wave, and also includes a corresponding plot of Heart Rate (HR) versus time.

FIG. 2 includes a plot of the R-R interval of the window prior to AF detection in FIG. 1, which corresponds to the inverse of the heart rate shown in FIG. 1.

Fig. 3 includes a Poincare (Poincare) diagram illustrating the relationship between each R-R interval and its immediately succeeding R-R interval in the EGM segment shown in fig. 1, i.e. illustrating the relationship between successive R-R intervals.

Fig. 4A and 4B, which may be collectively referred to as fig. 4, comprise a high-level flow chart that is used to describe how a true R-R interval can be distinguished from a false R-R interval associated with R-wave undersensing or AV conduction block using exemplary embodiments of the present technique, and how the results of such analysis can be used to determine whether to classify the detection of a potential AF episode as a false positive detection.

FIG. 5 is a high-level flow chart summarizing methods used by devices or systems monitoring cardiac activity, wherein such methods may be used to identify false R-R intervals and/or false AF detection, in accordance with various embodiments of the present technique.

FIG. 6 illustrates an exemplary histogram that may be generated and used to determine which set of R-R intervals in the set of R-R intervals is the dominant set, and thus may include true R-R intervals that may be compared to R-R intervals outside of the dominant set to determine whether an R-wave outside of the dominant set is a false R-R interval associated with R-wave undersensing or AV conduction block.

Fig. 7 illustrates a block diagram of one embodiment of an IMD implanted within a patient, in accordance with certain embodiments of the present technique.

Detailed Description

As is well known, each cardiac cycle (cardiac cycle) represented within an EGM or ECG generally includes a P-wave, followed by a QRS complex (complex), followed by a T-wave, where a QRS complex includes a Q-wave, an R-wave, and an S-wave. The P-wave is caused by depolarization of the atria. This is followed by an atrial contraction, indicated by a slight increase in atrial pressure that helps to further fill the ventricle. Atrial contraction is followed by ventricular depolarization which, as indicated by the QRS complex, initiates contraction of the ventricles, resulting in an increase in ventricular pressure until it exceeds the pulmonary and aortic diastolic pressures, causing blood to flow forward with expulsion from the ventricles. Ventricular repolarization thereafter occurs, as indicated by the T-wave, and this is associated with the onset of ventricular diastole, where forward flow stops, the pressure in the ventricles drops below the atrial pressure, at which time the mitral and tricuspid valves open to begin passively filling the ventricles during diastole. The terms EGM, EGM signal, and EGM waveform are used interchangeably herein. Similarly, the terms ECG, ECG signal, and ECG waveform are used interchangeably herein. Both the ECG and EGM signals are signals indicative of the electrical activity of the patient's heart.

The R-wave is typically the largest wave in the QRS complex, and is often identified by comparing samples of the EGM or ECG to an R-wave threshold. Various measurements may be obtained based on the EGM or ECG waveform, including measurements of the R-R interval, where the R-R interval is the duration between a pair of consecutive R-waves. As described above, in the background art, a common technique for detecting AF is based on a measure of R-R interval variability. However, for various reasons (including the angle of implantation of the IMD relative to the heart), the dynamically changing R-wave amplitude may sometimes be too small to detect, resulting in inadequate R-wave sensing unless the clinician lowers the programmable R-wave sensing threshold to correct for this. In other cases, oversensing of P-waves and/or T-waves due to P-wave and/or T-wave amplitudes exceeding the R-wave sensing threshold may cause the clinician to raise the programmable R-wave sensing threshold, which may also result in undersensing of R-wave sensing. In the case where the T-wave and/or the P-wave are erroneously identified as the R-wave, a false R-R interval having high variability may be identified, resulting in erroneous detection of AF. In other words, oversensing P-waves and/or oversensing T-waves can lead to false positive AF detection. As used herein, the term "oversensed P-waves" refers to P-waves that are erroneously identified as R-waves. Similarly, as used herein, the term "oversensed T-waves" refers to T-waves that are erroneously identified as R-waves. As used herein, the term "undersensing R-waves" refers to R-waves that are not detected. As used herein, the term "oversensing R-waves" refers to features of the EGM or ECG that are erroneously identified as R-waves (e.g., P-waves or T-waves).

Inadequate R-wave sensing can lead to false positive detection of the onset of arrhythmia (such as AF). As also described above, another cause of false positive detection of an arrhythmia episode is intermittent AV conduction block that causes a measure of R-R interval variability that results in false positive detection of an arrhythmia, even if the R-R interval is correctly sensed by the IMD during the intermittent AV conduction block. Interestingly, both R-wave undersensing and intermittent AV conduction block can result in R-R interval measurements that are close to integer multiples of adjacent R-R intervals. Certain embodiments of the present technology described herein relate to techniques for identifying instances of R-wave undersensing or AV conduction block using only sensed R-R intervals. IMDs may use this technique to reject false positive arrhythmia (e.g., AF) detection before transmitting it to a clinician, thereby improving arrhythmia detection specificity and reducing downstream clinical resources. More specifically, certain embodiments rely on the fact that: an undersensing or blocked R-wave effectively doubles the perceived R-R interval. Likewise, two successive undersensing or blocked R-waves triples the R-R interval, and so on. Thus, the ratio of each R-R interval to its adjacent R-R intervals can be used to identify potential instances of R-wave undersensing or AV conduction block. According to some embodiments, if the ratio is close enough to an integer (e.g., 2.05, 3.96, etc.) and the R-R interval is long enough (e.g., greater than 0.6 seconds, and thus corresponds to a heart rate of less than 100 bpm), then the R-R interval is likely the result of one or more undersensing and/or blocked R waves. Explained another way, the duration of an R-R interval relative to the duration of its adjacent R-R interval can be used to identify potential instances of R-wave undersensing or AV conduction block. More specifically, where the duration of an R-R interval is sufficiently close to an integer multiple of the duration of its neighboring R-R interval (e.g., 2.05, 3.96, etc.) and the R-R interval is sufficiently long (e.g., greater than 0.6 seconds, and thus corresponds to a heart rate of less than 100 bpm), then the R-R interval is likely to be the result of one or more undersensing and/or blocked R waves. Because these above-mentioned criteria may still be met during an actual arrhythmia (e.g., actual AF), each potential arrhythmia detection should be validated (i.e., re-evaluated) after the potentially undersensing/blocked R-R intervals are removed or otherwise ignored.

Certain embodiments of the present technology relate to methods and apparatus that use sensed R-R intervals to determine whether R-wave undersensing and/or AV conduction block has occurred, and more generally, to distinguish true R-R intervals from false R-R intervals. For example, the embodiments may be advantageously used to block or reject false positive arrhythmia detections (e.g., false positive AF detections) prior to their transmission to a clinician, thereby improving arrhythmia detection specificity and reducing downstream clinical resources. As used herein, the term "true R-R interval" refers to the actual R-R interval corresponding to a period of non-AV conditional block. As used herein, the term "false R-R interval" refers to an interval that is erroneously identified as an R-R interval, but is not an actual R-R interval. False R-R intervals may occur due to insufficient R-wave sensing, for example, if an R-wave is correctly identified in the EGM portion corresponding to the nth cardiac cycle and the (n +2) th cardiac cycle, but an R-wave is not identified in the (n +1) th cardiac cycle due to insufficient R-wave sensing, resulting in an R-R interval measurement that is approximately twice the true R-R interval. False R-R intervals may alternatively or additionally occur due to AV condition blockage, for example, if an R-wave is present and correctly identified in the EGM portion corresponding to the nth cardiac cycle and the (n +2) th cardiac cycle, but is absent due to AV condition blockage in the (n +1) th cardiac cycle, resulting in an R-R interval measurement that is approximately twice the true R-R interval.

Other example types of intervals that may be erroneously identified as R-R intervals (and thus are examples of false R-R intervals) include, but are not limited to, P-R intervals, R-T intervals, P-T intervals, and T-P intervals. The P-R interval may be erroneously identified as an R-R interval if the P-wave is oversensed. The R-T interval may be erroneously identified as an R-R interval if the T-wave is oversensed. The P-T interval or T-P interval may be erroneously identified as an R-R interval if T-waves and P-waves are oversensing and R-waves are undersensing. These types of false R-R intervals may also be referred to as oversensing R-R intervals. Embodiments of the present technology described herein do not specifically address oversensing R-R intervals, but may be used with techniques for addressing these other types of false R-R intervals to further increase arrhythmia detection specificity and, more generally, increase arrhythmia detection accuracy.

Certain embodiments of the present technology described herein rely on the following phenomena: r-wave undersensing or AV conduction block effectively causes the measured R-R interval to be substantially similar to an integer multiple (e.g., 2x or 3x) of the normal R-R interval, which may also be referred to as the true R-R interval or the actual R-R interval. Thus, certain embodiments of the present technology identify intervals similar to the previous three (or some other number) intervals or integer multiples of the next three (or some other number) intervals, which are actual R-R intervals and do not correspond to R-wave undersensing or AV conduction block. Further analysis (e.g., arrhythmia detection analysis) may then be performed using only the remaining R-R intervals.

According to some embodiments, a list of sensed R-R intervals is obtained for recorded EGM clips (clips), which may also be referred to as EGM clips or EGM clips. Because this list of R-R intervals may actually include one or more false R-R intervals (e.g., due to insufficient R-wave sensing and/or intermittent AV conduction block), unless explicitly referred to as "true R-R intervals," any interval referred to herein generally as an R-R interval may be a false R-R interval or a true R-R interval. It should also be noted that the term "potential R-R interval" refers to an R-R interval that may be a false R-R interval or a true R-R interval. Additionally, it should be noted that while the following description and much of the patient examples discussed below describe R-wave sensing insufficiency, the same principles apply to intermittent AV conduction block as well.

Directly obtained from implantation of ConfirmRX^TMEGM clip files of ICM patients, an example of R-wave undersensing is shown in fig. 1. While this particular example corresponds to an R-R interval pattern due to R-wave undersensing, the same R-R interval pattern may be the result of intermittent AV conduction block, and the same principles would apply. At the bottom of fig. 1, a portion of EGM segment 102 is shown, which results in AF detection due to an undersensing R-wave. At the top of fig. 1, a graph or plot 122 is shown, which includes Heart Rate (HR) in beats per minute (bpm) along the vertical axis, and time(s) in seconds along the horizontal axis. The vertical dashed line 124 corresponds to AF detection occurring at a point in time corresponding to-82 seconds, and therefore, the vertical line 124 is also marked as AF trigger. Because the AF detection represented by the vertical dashed line 124 may actually be false AF detection, it may also be referred to more specifically as potential AF detection, where the potential AF detection may or may not be true AF detection. For example, if a measure of R-R interval variability exceeds a corresponding threshold, a potential AF detection may have been detected, but is not limited thereto. Example techniques for Detecting AF episodes (or more specifically, potential AF episodes) are described in U.S. patent No.8,121,675 to Shaquer et al, entitled "Device and Method for Detecting atomic contamination," which is incorporated herein by reference. The use of other techniques for detecting potential AF episodes as well as other types of arrhythmias is also possible and described hereinWithin the scope of the embodiments described.

Fig. 2 illustrates a graph or plot of the R-R interval in milliseconds (ms) in the 30 second(s) window before the AF trigger 124 in fig. 1, which corresponds to the inverse of the heart rate shown in fig. 1. In FIG. 2, the circles within dashed outline 202 correspond to R-R intervals that are true R-R intervals, while the circles within dashed outline 204 correspond to R-R intervals associated with undersensing R-waves (where the maximum ratio and% difference relative to adjacent R-R intervals are indicated next to each circle within dashed outline 204). Since the R-R intervals within the dashed outline 204 are not true R-R intervals, they may be referred to as false R-R intervals.

The Poincare (Poincare) diagram shown in fig. 3 plots the relationship between each R-R interval in the EGM segment 102 and its immediately succeeding R-R interval, i.e., illustrates the relationship between successive R-R intervals. The circles within the dashed outline 302 correspond to the true R-R spacing. The circles within the dashed outline 304 correspond to false R-R intervals due to inadequate R-wave sensing. Similar false R-R intervals may result from intermittent AV conduction blocks rather than R-wave undersensing.

According to some embodiments, for each R-R interval in a window (e.g., a 30-second window) that precedes AF triggering (i.e., that causes detection of a potential AF episode), a ratio ("R") is calculated relative to each of a plurality of adjacent R-R intervals (e.g., the immediately preceding three intervals and the immediately following three intervals). In a particular embodiment, the analysis skips the first three (or some other number) R-R intervals and the last three (or some other number) R-R intervals in the 30 second window, because the R-R intervals near the beginning and end of the window are the fewest neighbors to one side. All ratios rounded to less than 2 are eliminated.

Next, after eliminating R-R intervals having a rounded ratio less than 2, an indicator of the difference between each remaining analyzed R-R interval and its neighboring R-R interval is determined. In certain embodiments, the indicator of the difference between each analyzed R-R interval and its adjacent R-R interval is a percentage difference calculated using the following formula:

% difference (100 × | r-round (r) |/round (r)

Wherein the content of the first and second substances,

r is the ratio of the analyzed R-R interval to the adjacent R-R interval, and

round (r) is the calculated ratio rounded to the nearest integer.

The minimum percentage difference (or more generally, a minimum indicator of difference) of the analyzed R-R interval relative to all six (or some other number) neighbors may then be used to potentially flag the analyzed R-R interval as being associated with undersensing or AV conduction block. These rounded rates and percentage differences are listed next to each circle within dashed outline 204 in fig. 2. More specifically, for the circle labeled 206 (approximately 25 seconds before AF trigger), the ratio of rounding is 2: 1 and the percentage difference is 0%; for the circle labeled 208 (approximately 20 seconds before AF trigger), the ratio of rounding is 3: 1 and a percentage difference of 3%; for the circle labeled 210 (approximately 18 seconds before AF trigger), the ratio of rounding is 2: 1 and the percentage difference is 1%; for the circle labeled 212 (approximately 7 seconds before AF trigger), the ratio of rounding is 2: 1 and the percentage difference is 1%; and for the circle labeled 214 (approximately 4 seconds before AF trigger), the ratio of rounding is 2: 1 and a percentage difference of 2%.

Specifically, referring to the circle labeled 206 (approximately 25 seconds before AF triggering), the duration of the undersensing R-R interval (also referred to as the "value") is 1500 milliseconds (ms). The durations (also referred to as "values") of three adjacent R-R intervals (represented by three circles within the dashed outline labeled 205) immediately preceding the 1500ms undersensing R-R interval are 700ms, and 750ms, respectively. The duration of three adjacent R-R intervals (represented by three circles within the dashed outline labeled 207) immediately following the 1500ms undersensing R-R interval are 760ms, 740ms, and 750ms, respectively. The ratio of the undersensing R-R interval (having a value of 1500ms) to the three adjacent R-R intervals on either side is as follows: [1500/700, 1500/700, 1500/750, 1500/760, 1500/740, 1500/750] ═ 2.14, 2.14, 2.00, 1.97, 2.03, 2.00 ]. These ratios correspond to 0% differences of [ 7%, 7%, 0%, 1.5%, 1.5%, 0% ]. A minimum% difference of 0% indicates that the current interval (1500ms) "is close" to an integer multiple of the adjacent R-R interval (in this case, the 0% difference is from 2 times the adjacent R-R interval).

According to some embodiments, two criteria are ultimately applied in order to determine whether the R-R interval being analyzed (also referred to as the R-R interval being analyzed) should be classified as a false R-R interval associated with R-wave undersensing or AV conduction block (which may be collectively referred to as R-wave undersensing/blocking), and thus may be more generally classified as a false R-R interval.

One criterion is that the minimum percentage difference relative to the ratio of all its six (or some other number) neighbors is less than a specified difference threshold, e.g., less than 10%. This criterion ensures that the interval in question is reasonably close to an integer multiple of at least one of its adjacent R-R intervals, where the integer multiple is at least 2. Note that the minimum percentage difference threshold may also be programmed according to clinical needs. For example, if AF sensitivity is important, it can be designated as less than 10%, but if reduction of false positive AF detection (aka AF specificity) is preferred, it can alternatively be designated as greater than 10% (e.g., 15%).

Another criterion is that the interval value is greater than a specified duration threshold, e.g., greater than 600ms (i.e., corresponding to an HR of less than 100 bpm). This criterion ensures that a P-wave or T-wave oversensing halfway between R-R intervals does not result in a true R-R interval being marked as a false R-R interval because the true R-R interval is twice the duration of an adjacent R-R interval.

Once false R-R intervals (due to R-wave undersensing and/or AV block) within a 30-second window have been identified (resulting in potential AF detection or other types of potential arrhythmia detection), it can be determined what percentage of R-R intervals are identified as false R-R intervals (due to R-wave undersensing and/or AV block). This percentage of false R-R intervals (which may also be more specifically referred to as the "undersensing/AV block percentage") quantifies the incidence of R-wave undersensing and/or AV block within the window.

Furthermore, the identified false R-R intervals (due to R-wave undersensing and/or AV conduction block) are removed from the ordered list of R-R intervals (included in the window leading to potential AF detection), thereby producing a corrected list of R-R intervals. Based on the corrected list of R-R intervals, the median interval-interval% difference (using the equation% difference 100 × | R-round (R) |/round (R)) is calculated, thereby yielding "corrected interval variability. "

Finally, the entire window is classified (also referred to as labeled) as a false positive AF detection (due to R-wave undersensing and/or AV conduction block) if the following criteria are met: (1) the "undersensing/AV conduction block percentage" is greater than a specified false detection threshold (e.g., greater than 5%), the criterion ensuring that there are a sufficient number of false R-R intervals associated with detecting undersensing/AV conduction block so that they may have affected AF detection; and (2) "corrected interval variability" is less than a specified variability threshold (e.g., < 5%). Note that during actual AF, if some intervals are randomly similar to integer multiples of adjacent R-R intervals, they may still be labeled as false R-R intervals (due to R-wave undersensing and/or AV conduction block). This second criterion is used to identify when the tempo is stable after the false R-R interval (due to R-wave undersensing and/or AV conduction block) is removed.

The example window described above with reference to fig. 1-3 that results in potential AF detection is associated with a "undersensing/AV block percentage" of 20.0% and a "corrected interval variability" of 3.4%, and thus meeting the above criteria can be flagged as false AF detection.

Additional details of the embodiments outlined above are described below with reference to the high level flow diagrams in fig. 4A and 4B, which may be collectively referred to as fig. 4. More specifically, fig. 4 is used to summarize certain methods of the present technology for improving R-R interval detection specificity and arrhythmia episode (e.g., AF episode) detection specificity. Such a method may be triggered in response to the detection of a potential arrhythmia episode (e.g., a potential AF episode). In other words, the method summarized with reference to the high level flow diagram in fig. 4 may be used to identify false R-R intervals due to R-wave undersensing and/or AV block and to detect false positive arrhythmia detections.

Referring to fig. 4A, step 402 involves obtaining an ordered list of R-R intervals, each R-R interval having a respective duration, within a window that results in detection of a potential arrhythmia episode (e.g., a potential AF episode). The ordered list of R-R intervals can be obtained, for example, by identifying R-waves within an EGM or ECG segment and determining the intervals between successive R-waves, thereby producing an ordered list of R-R intervals. Such R-waves may be identified within an EGM or ECG segment by comparing the EGM or ECG segment or samples thereof to an R-wave sensing threshold and identifying an R-wave when the R-wave sensing threshold is reached or exceeded. Other variations are also possible and are within the scope of the embodiments described herein. For example, R-waves or QRS complex morphology templates may alternatively or additionally be used to identify R-waves.

The ordered list of R-R intervals obtained at step 402 will preferably only include true R-R intervals. However, the ordered list of intervals obtained at step 402 may also include one or more false R-R intervals due to insufficient R-wave sensing and/or AV conduction block. In other words, in addition to including true R-R intervals, the ordered list of R-R intervals included in the window that causes detection of a potential arrhythmia episode (also referred to as an "arrhythmia trigger") (e.g., a potential AF episode (also referred to as an "AF trigger")) may also include one or more false R-R intervals that may be present, e.g., if the R-wave is undersensing (i.e., present but not detected) and/or if the patient experiences AV conduction blocks that result in one or more missed R-waves. To maximize the specificity of the method summarized with reference to fig. 4A, one or more techniques for identifying and removing or otherwise compensating for other types of false R-R intervals may be performed prior to step 402, as part of step 402, or between step 402 and next step 404.

Step 404 involves selecting an R-R interval (from the ordered list of R-R intervals obtained in step 402) for analysis. The first time step 404 is performed (for an ordered list of intervals), the first R-R interval in the ordered list may be selected. The second time step 404 is performed (for the ordered list of intervals), the second R-R interval in the ordered list may be selected, and so on.

At step 406, it is determined that the R-R interval (selected for analysis in step 404) is one of the first M or last M R-R intervals in the ordered list of intervals (e.g., M-3). If the selected interval is one of the top M or last M R-R intervals in the list (i.e., if the answer to the determination at step 406 is yes), then flow proceeds to step 420 (thereby skipping steps 408-418). If the selected interval is not one of the top M or last M R-R intervals in the list (i.e., if the answer to the determination of step 406 is "NO"), then flow proceeds to step 408.

At step 408, it is determined whether the duration of the R-R interval (selected for analysis in step 404) is greater than a specified duration threshold, e.g., greater than 600ms (i.e., corresponding to an HR of less than 100 bpm). As described above, this criterion ensures that P-wave or T-wave oversensing halfway between R-R intervals does not result in a true R-R interval being flagged as a false R-R interval because the true R-R interval is twice the duration of an adjacent R-R interval. The particular duration threshold used at step 408 may be patient-specific and/or may be arrhythmia-specific. More specifically, different duration thresholds may be used for different types of arrhythmias. For example, a first duration threshold may be used where the detected arrhythmia is bradycardia, a second duration threshold may be used where the detected arrhythmia is tachycardia, a third duration threshold may be used where the detected arrhythmia is AF, a fourth duration threshold may be used where the detected arrhythmia is VF, and so on.

At step 410, for the R-R intervals being analyzed, a ratio ("R") is calculated with respect to each of the N adjacent R-R intervals (e.g., the immediately preceding M intervals and the immediately succeeding M intervals), or more generally, with respect to each R-R interval in the set of N adjacent R-R intervals, where N is at least 6 and M is at least 3. The result of step 410 is a ratio set.

Step 412 involves removing from the ratio set any ratios rounded to less than two when rounded to their nearest integer. In other words, any ratio (in the set of ratios) having a value less than 1.5 is removed from the set because it is rounded to one when rounded to the nearest integer, which is less than two.

Step 414 involves determining an indicator of the difference between the duration of the R-R interval (selected for analysis in step 404) and the duration of the N adjacent R-R intervals that it did not remove at step 412. In certain embodiments, the indicator of the difference between the R-R interval being analyzed and its neighboring R-R interval (not removed at step 412) is a percentage difference calculated using the following equation:

% difference (100 × | r-round (r) |/round (r)

Wherein the content of the first and second substances,

r is the ratio of the analyzed R-R interval to the adjacent R-R interval, and

round (r) is the calculated ratio rounded to the nearest integer.

Step 416 involves determining whether at least a specified number X of the ratios of the% difference (or more generally, an indicator of the difference) in the set is less than a specified difference threshold (e.g., < 10%). This criterion ensures that the interval in question is reasonably close to an integer multiple of at least X of its adjacent R-R intervals, where the integer multiple is at least 2, and where X is a specified integer of at least 1. If the determination at step 416 is "yes," then the flow proceeds to step 418 and the analyzed R-R interval is classified as a false R-R interval associated with R-wave undersensing or AV conduction block. If the answer to the determination at step 416 is no, then flow proceeds to step 420. Still referring to step 416, as described above, the minimum percentage difference threshold may be programmable depending on the clinical needs. Similarly, the value of X may be programmable depending on clinical needs. For example, if arrhythmia (e.g., AF) sensitivity is important, the specified difference threshold may be 10%, and the value of X may be 1; alternatively, if specificity is more important than sensitivity, the specified difference threshold may be 15% and the value of X may be 2. The particular difference threshold and/or value of X used at step 416 may be patient specific, and/or may be arrhythmia specific. More specifically, different difference thresholds and/or values of X may be used for different types of arrhythmias. For example, a first difference threshold and a first X value may be used in the case where the detected arrhythmia is bradycardia, a second difference threshold and a second X value may be used in the case where the detected arrhythmia is tachycardia, a third difference threshold and a third X value may be used in the case where the detected arrhythmia is AF, and so on.

At step 420, it is determined whether there are any additional R-R intervals to analyze in the ordered list of R-R intervals (obtained at step 402). If the answer to step 420 is "yes," then the flow returns to step 404 and the next R-R interval in the list (obtained at step 402) is selected for analysis. In this manner, steps 404 through 420 are repeated until the answer to the determination of step 420 is "no," at which point the flow passes to step 422 in fig. 4B.

Referring to fig. 4B, at step 422, it is determined what percentage of R-R intervals in the window that cause detection of a potential arrhythmia episode are classified as associated with at least one of R-wave undersensing or AV conduction block. For example, if there are 40R-R intervals in the window of detection that cause a potential arrhythmia episode and 10 of those R-R intervals are classified as associated with at least one of R-wave undersensing or AV block, then the result of step 422 would be 25%. The percentage determined at step 422 may also be referred to as the R-wave undersensing/retardation percentage.

At step 424, median R-R intervals are determined to be a percentage difference from the R-R intervals for those R-R intervals that are not classified as associated with at least one of R-wave undersensing or AV block (in the window of detection that caused the potential arrhythmia episode (e.g., potential AF episode)). Continuing with the above example, where 10 of the 40R-R intervals are classified as associated with at least one of R-wave undersensing or AV conduction block, a median R-R interval and R-R interval percentage difference is determined at step 424 for the remaining 30R-R intervals (not classified as associated with R-wave undersensing/blocking). This would involve determining the% difference between the first and second R-R intervals, the second and third R-R intervals, the third and fourth R-R intervals, … …, the 29 th and 30 th R-R intervals, thereby producing 29 individual% differences, or more generally Z-1 individual% differences (where Z is how many R-R intervals within the window are not classified as associated with R-wave undersensing/blocking). To find the median of Z-1 individual% differences (e.g., 29 individual% differences), the% differences may be arranged in order from smallest to largest, and the median is the value midway through the set, i.e., the most intermediate value. According to a specific embodiment, if there are even numbers in the data set, the median may be determined by determining the mean (average) of the two most intermediate numbers or selecting one of the two most intermediate numbers. The idea here is that the R-R intervals associated with "true" R-waves should be relatively consistent and should not change dramatically when the patient has not experienced an actual arrhythmia episode (e.g., an actual AF episode). If the remaining R-R intervals (i.e., intervals not associated with R-wave undersensing/blocking) are not relatively consistent and vary dramatically, then it is an indication that the patient may have experienced an actual arrhythmia episode (e.g., an actual AF episode).

At step 426, median R-R intervals (in a window of detection that causes a potential arrhythmia episode (e.g., a potential AF episode) are determined that are not classified as those R-R intervals associated with at least one of R-wave undersensing or AV conduction block (also referred to as R-wave undersensing/blocking).

At step 428, it is determined whether the median R-R interval (determined at step 426) is greater than or equal to a specified duration threshold, such as 0.5 seconds. This is equivalent to determining that the patient's median Heart Rate (HR) (corresponding to R-R intervals in the window of detection that lead to the potential arrhythmia episode that are not classified as associated with R-wave undersensing/blocking) is less than or equal to a specified HR threshold, e.g., 120 beats per minute (bpm). If the answer to the determination at step 428 is YES, then flow proceeds to step 430. If the answer to the determination at step 430 is no, then flow proceeds to step 434.

At step 430, it is determined whether the R-wave undersensing/retardation percentage (determined at step 422) is greater than a first specified percentage threshold, e.g., > 5%. This criterion is used to determine whether enough R-waves are classified as being associated with R-wave undersensing/blocking, such that they may affect initial arrhythmia detection/triggering (e.g., initial AF detection/triggering). If the answer to the determination of step 430 is yes, then flow proceeds to step 432.

At step 432, it is determined whether the median R-R interval and R-R interval% difference (determined at step 424) is less than a first median percentage difference threshold, e.g., < 7.5%. This criterion is used to determine whether the R-R interval associated with a "true" R-wave (i.e., not associated with R-wave undersensing/conduction block) is relatively consistent and not drastically changing, indicating that the patient has not experienced an actual episode of AF or VF. Explained another way, during actual AF or VF, some R-R intervals may still be classified as associated with R-wave undersensing/blocking if they are randomly similar to integer multiples of adjacent R-R intervals. This criterion checks whether the tempo is stable without these R-wave undersensing/blocking related R-R intervals. If the answer to the determination at step 432 is YES, then the flow proceeds to step 438. At step 438, the potential AF or VF episode is classified as a false positive detection. Explained another way, at step 438 AF or VF triggering or detection of a potential AF or VF episode is rejected. The order of steps 430 and 432 may be reversed. Similarly, the order of steps 422, 424, and 426 may be rearranged.

If the answer to either of steps 430 or 432 is "no," then flow proceeds to step 440. At step 440, the potential arrhythmia episode may be classified as a true arrhythmia episode, or a confidence level or probability that the potential arrhythmia episode is in fact a true arrhythmia episode may be increased, or one or more additional arrhythmia discriminators (discriminators) may be used to determine whether the potential arrhythmia detection should be classified as a true positive or false positive arrhythmia detection.

Referring back to step 428, if the answer to the determination at step 428 is no, then flow proceeds to step 434. At step 434, it is determined whether the R-wave undersensing/retardation percentage (determined at step 422) is greater than a second specified percentage threshold, e.g., > 2.5%, which is less than the first specified percentage threshold used at step 430. If the answer to the determination at step 434 is yes, then flow proceeds to step 436.

At step 436, it is determined whether the median R-R interval and R-R interval% difference (determined at step 424) is less than a second median percentage difference threshold, e.g., < 5%, which is less than the first median percentage difference threshold used at step 432. If the answer to the determination at step 436 is "yes," then flow proceeds to step 438 where the potential arrhythmia (e.g., AF or VF) episode is classified as a false positive detection. The order of steps 434 and 436 may be reversed.

If the answer to either of steps 434 or 436 is "no," then flow proceeds to step 440. As described above, at step 440, the potential arrhythmia episode may be classified as a true arrhythmia episode, or the confidence level or probability that the potential arrhythmia episode is in fact a true arrhythmia episode may be increased, or one or more additional arrhythmia discriminators may be used to determine whether the potential arrhythmia detection should be classified as a true positive or false positive arrhythmia detection.

The threshold used in the right branch of fig. 4B (including steps 434 and 436) is lower than the corresponding threshold used in the left branch of fig. 4B (including steps 430 and 432). This is to counter that if the answer to the determination at step 428 is no, then the potential arrhythmia detection is less likely to be a false positive. More specifically, the second specified percentage threshold (e.g., 2.5%) used at step 434 is less than the first specified percentage threshold (e.g., 5%) used at step 430 to account for the fact that: AF or VF detection algorithms (used first to detect potential AF or VF episodes) may have higher sensitivity at higher heart rates and can be easily triggered by a few undersensing/blocking R-waves. Further, the second median percentage difference threshold (e.g., 5%) used at step 436 is less than the first median percentage difference threshold (e.g., 7.5%) used at step 432 in order to be more conservative in flagging faster cadence as being associated with R-wave undersensing/conduction block because the fast cadence is more likely to be truly AF or VF.

As can be appreciated from the flowchart, step 428 and the right branch (including steps 434 and 436) are such that a different threshold may be used for higher Heart Rates (HRs) than for lower HRs (i.e., longer R-R intervals). In an alternative embodiment, step 428 and the right hand branch (including steps 434 and 436) are eliminated, in which case flow would proceed directly from step 426 to step 430. In such an alternative embodiment, the same threshold would be used for both low and high HR (i.e., for both long and short R-R intervals).

Various values and thresholds are used in the various steps summarized above with reference to fig. 4, and these values and/or thresholds may be adjusted to increase or decrease the sensitivity of R-wave undersensing identification and/or to increase or decrease the sensitivity of arrhythmia episode detection rejection (i.e., when determining whether the detection of an arrhythmia episode is a false positive detection). An increase in sensitivity generally results in a decrease in specificity, while a decrease in sensitivity generally results in an increase in specificity. The desired balance between sensitivity and specificity may be patient-specific and/or arrhythmia-specific. According to some embodiments, there are different respective sets of values and thresholds specified for use with each of a plurality of different types of arrhythmias. In situations where a cardiac arrhythmia may be life threatening (such as VF), the set of values and thresholds may be defined to have low sensitivity, thereby avoiding rejection or ignoring the potentially life threatening episode and retaining the appropriate therapy (such as defibrillation shock). The value of X used at step 416 may be increased to reduce the sensitivity of R-wave undersensing or the value of X used at step 416 may be decreased to increase the sensitivity of R-wave undersensing. For another example, the difference threshold used at step 416 may be increased to increase the sensitivity of the R-wave undersensing identification (thereby allowing a percentage difference with a greater margin of error), or the difference threshold used at step 416 may be decreased to decrease the sensitivity of the R-wave undersensing identification. The percentage threshold(s) used at steps 430 and/or 434 may be increased to decrease the sensitivity of arrhythmia episode rejection, or the percentage threshold(s) used at steps 430 and/or 434 may be decreased to increase the sensitivity of arrhythmia episode rejection. Note that the terms "reduce" and "decrease" are used interchangeably herein.

According to some embodiments, the IMD may perform the method described above with reference to fig. 4 in response to detecting an AF episode (or some other type of arrhythmia episode). Where the steps summarized above with reference to fig. 4 (including fig. 4A and 4B) are performed in response to an arrhythmia trigger (e.g., AF trigger), some of the steps may be skipped depending on the particular type of potential arrhythmia detected. For example, steps 424, 426 and 428 (and the right branch including steps 434 and 436) may be very helpful when the type of potential arrhythmia episode detected is AF or VF, in which case there should be relatively high variability in the R-R interval if the arrhythmia detection is a true positive detection. When used with other types of arrhythmias, such as bradycardia or tachycardia, flow may skip from step 422 to step 430 (i.e., steps 424, 426 and 428 may be skipped and steps 434 and 436 are not required). Thus, there may be a determination step (not shown) between steps 422 and 424 that determines whether the arrhythmia trigger is an AF or VF trigger. If the answer to this determination is yes, the flow proceeds to step 424, whereas if the answer to this determination is no, the flow jumps to step 430.

According to some embodiments, the IMD may perform the method described above with reference to fig. 4 in response to detecting an AF episode (or some other type of arrhythmia episode). The detection of an arrhythmia episode may also be referred to as an arrhythmia trigger, for example, the detection of an AF episode may also be referred to as an AF trigger. Such IMDs may be configured to transmit data corresponding to AF episodes (or other types of arrhythmia episodes) detected by the IMDs to an external device communicatively coupled to a patient care network. In certain such embodiments, the IMD does not (is prevented from) transmitting (to an external device communicatively coupled to the patient care network) data corresponding to AF episodes (or other types of arrhythmia episodes) that are detected by the IMD but are later determined by the IMD to be false positive detections. The IMD may also be configured to allow data corresponding to potential arrhythmia episodes (e.g., potential AF episodes) detected by the IMD but later determined by the IMD to be false positive detection to be overwritten in memory. Alternatively, the IMD may prevent data corresponding to potential arrhythmia episodes (e.g., potential AF episodes) that are detected by the IMD but later determined by the IMD to be false positive detections from being stored in memory.

According to certain embodiments, a medical device (e.g., IMD) performing the method described above with reference to fig. 4 may monitor the HR of a patient based on R-R intervals identified from segments of an EGM or ECG, and the medical device may determine whether the monitored HR is inaccurate due to oversensing based on the results of the method, and therefore should ignore or recalculate the HR. For example, if at least a specified number of R-R intervals classified as associated with R-wave undersensing/AV conduction block exceed corresponding thresholds, the medical device may conclude that: the HR determined based on the sensed interval is inaccurate and should not be used, or should be recalculated.

Implementations of the above-described embodiments of the present technology were tested to determine whether the present technology can be used and extended to what extent to reduce the reporting of false positive AF detection. And (by Confirm Rx)^TMICM detected) a number of detected AF episodes were manually determined as "true" or "false" positive AF detections. Of the large number of episodes, about 25 percent are judged as true AF episodes (i.e., as true positives), while the remaining about 75 percent are judged as non-AF episodes (i.e., as false positives). Using the embodiments of the present technique summarized above with reference to FIG. 4, less than 1 percent is incorrectly attributed to a true AF episodeClassification (also referred to as "labeled") is false positive detection. Using the embodiments of the present technology summarized above with reference to fig. 4, almost 50 percent of false AF episodes were correctly classified (also referred to as "labeled") as false positive detections.

The example thresholds described herein are conservatively selected to limit the number of true AF episodes that are incorrectly classified as false detections due to R-wave sensing/blocking. However, the underlying logic of the embodiments described herein may be extended beyond the above limitations. The specific values for each threshold may be optimized more systematically for narrow patient populations, broader patient populations, or for individual patients. Thus, embodiments of the present technology described herein should not be limited to use with the example thresholds described herein. As explained above, according to some embodiments, there may be different respective sets of values and thresholds specified for use with each of a plurality of different types of arrhythmias.

The high-level flow chart of fig. 5 is used to summarize certain methods used by a device or system that monitors cardiac activity, where such methods may be used to identify false R-R intervals and/or false arrhythmia detection (e.g., false AF detection). The embodiment summarized above with reference to fig. 4 is a specific implementation of the method summarized with reference to fig. 5.

Referring to FIG. 5, step 502 involves obtaining information for a set of R-R intervals, where each R-R interval has a respective duration, and each R-R interval may be a true R-R interval or a false R-R interval. For example, such a set of R-R intervals may be, but is not limited to, R-R intervals within a window (e.g., a 30 second window) that results in detection of a potential arrhythmia episode (e.g., a potential AF episode). This set should include at least three R-R intervals, but will likely include more R-R intervals, for example, at least twenty R-R intervals, but is not so limited.

Step 504 involves selecting an R-R interval for analysis. Step 506 involves determining whether the duration of the R-R interval is greater than a first specified threshold (e.g., 600ms), and step 508 involves determining whether the duration of the R-R interval is within a second specified threshold (e.g., 10%) as an integer multiple of at least X other R-R intervals for which information is obtained, where the integer multiple is at least 2, and where X is a specified integer of 1 or greater. Step 510 involves classifying one of the R-R intervals as a false R-R interval in response to the duration of the R-R interval being greater than a first specified threshold (e.g., 600ms) and the duration of the R-R interval being within a second specified threshold (e.g., 10%) as an integer multiple of at least X other R-R intervals for which information is obtained. At step 512, it is determined whether there are additional R-R intervals to analyze. If the answer to the determination at step 512 is YES, the flow returns to step 504. For example, if at least a specified percentage or number of R-R intervals are classified as false R-R intervals, and/or if, after removing false R-R intervals, the variability and/or other characteristics of the remaining R-R intervals indicate that the potential arrhythmia episode (e.g., potential AF episode) is actually a true arrhythmia episode (e.g., a true AF episode), at optional step 514, a determination is made as to whether the potential AF episode (or other type of arrhythmia episode) is classified as a false detection.

According to certain embodiments, between steps 502 and 504, the R-R intervals in the set are grouped into two or more groups based on the duration of the R-R intervals, such that R-R intervals within a third specified threshold of each other (e.g., within 15%) are grouped into the same group, and the group that includes the greatest number of R-R intervals is classified as the dominant group. In such an embodiment, the other R-R intervals in the group used at the instance of step 508 are the R-R intervals within the dominant group that are most likely to be true R-R intervals. Such grouping may produce a histogram, such as the histogram shown in fig. 6. Referring to fig. 6, the example histogram 602 shown therein includes a plurality of bins 604a, 604b, 604c, 604d, each corresponding to an R-R interval within a third specified threshold (e.g., 15% or 20%) of each other. Using such a histogram, the dominant group 606 may be identified by identifying one of the bins in which there is a maximum number of R-R intervals. It can be assumed that the R-R intervals within the dominant group are true R-R intervals. Thus, in certain embodiments, under the instance of step 504 (of FIG. 5), only R-R intervals that are not in the dominant group may be selected for analysis. Unless otherwise noted, when selecting R-R intervals at the instance of step 504, the R-R intervals need not be selected in any particular order.

Various values and thresholds are used in the various steps summarized above with reference to fig. 5, and these values and/or thresholds may be adjusted to increase or decrease the sensitivity of R-wave undersensing identification and/or to increase or decrease the sensitivity of arrhythmia episode detection rejection (i.e., when determining whether the detection of an arrhythmia episode is a false positive detection).

Embodiments of the present technology described herein may be used with various types of IMDs, including but not limited to an Insertable Cardiac Monitor (ICM), a pacemaker having one or more leads attached thereto, a Leadless Cardiac Pacemaker (LCP), or an Implantable Cardioverter Defibrillator (ICD). Such an ICD may be a transvascular ICD, or may be a non-vascular ICD, where the non-vascular ICD may be a subcutaneous (SubQ) ICD. Where embodiments of the present technology are implemented by an ICM, for example, such embodiments may be used to reduce the number of false positive AF detections transmitted from the ICM to the patient care network for review by the clinician. This is beneficial because false positive AF detection is highly undesirable, as the burden of classifying by a large number of clinically irrelevant AF episodes can be both time consuming and expensive. Where an ICD or IMD in communication with the ICD uses embodiments of the present technology, such embodiments may reduce the frequency of delivering defibrillation shocks in response to false positive AF detection. This is beneficial because defibrillation shocks are often painful, and delivering such shocks in response to false positive AF detection exposes the patient to unnecessary shocks and can prematurely deplete the stored energy in the battery.

In accordance with certain embodiments of the present technique, in response to detecting a potential bradycardia episode or a potential cardiac arrest episode, one of the techniques summarized above with reference to fig. 4 and 5 is performed to determine whether the potential arrhythmia episode detection is potentially caused by an AV conduction block. In other words, embodiments of the present technology described herein may be used to identify potential AV conduction blocks. When used to detect potential AV conduction blocks, steps 424, 426 and 428 (and the right branch including steps 434 and 436) should be skipped. Such an embodiment alone would not be able to distinguish R-wave undersensing from AV conduction block, but such an embodiment could be used as a first stage screen to identify potential AV conduction blocks, and then another known or future developed technique (such as an EGM-based technique) could be used to determine whether AV conduction block actually occurred. Such EGM-based techniques used to determine whether AV conduction block has actually occurred may look for abnormalities in PR intervals and/or analyze the relationship between the P-wave and QRS complex, but are not limited thereto.

The embodiments of the present technology summarized above with reference to fig. 4 and 5 may be used to confirm or reject detection of potential arrhythmia episodes. In other words, such embodiments may be used to distinguish false positive arrhythmia detection from true positive arrhythmia detection. Additionally, or alternatively, embodiments of the present technology described herein may be used first to help more accurately detect arrhythmia episodes. More specifically, one of the techniques described herein may be performed continuously in conjunction with one or more arrhythmia detection techniques. In other words, rather than waiting until an arrhythmia trigger (e.g., AF trigger) to perform one of the techniques described herein with reference to fig. 4 and 5, one of the techniques described herein may interact with one or more arrhythmia detection techniques in real time or near real time. For example, assume that an arrhythmia detection algorithm is triggering AF detection, and one of the techniques described herein identifies substantial R-wave undersensing or AV conduction block. In response thereto, the AF triggering criteria in the arrhythmia detection technique may be appropriately adjusted, or the arrhythmia detection technique may be stopped from being performed in response to determining that the R-R interval being analyzed is incorrect due to R-wave oversensing or AV conduction block. Other variations are also possible and are within the scope of the embodiments described herein. Fig. 7 illustrates a block diagram of one embodiment of an IMD implanted within a patient, in accordance with certain embodiments of the present technique. IMD 701 may be implemented as a fully functional biventricular pacemaker and defibrillator, equipped with both atrial and ventricular sensing and pacing circuitry for four-chamber sensing and stimulation therapies (including both pacing and shock therapies). Alternatively, IMD 701 may provide a fully functional cardiac resynchronization therapy. Alternatively, IMD 701 may be implemented with a reduced set of functions and components. For example, if the IMD is an ICM, the IMD may be implemented without pacing. IMD 701 may be coupled to one or more leads for single or multi-chamber pacing and/or sensing. Alternatively, IMD 701 may be an LCP that includes electrodes located on housing 700 of IMD 701 or in close proximity to housing 700.

IMD 701 has a housing 700 to house electronic/computing components. The housing 700 (which is often referred to as a "can," "case," "housing," or "housing electrode") may be programmably selected to serve as a return electrode for certain stimulation modes. Housing 700 may also include a connector (not shown) having a plurality of terminals 702, 704, 706, 708, and 710. The terminals may be connected to electrodes (also represented by reference numerals 702, 704, 706, 708, and 710) located at various locations on the housing 700, or to electrodes located on leads. IMD 701 includes a programmable microcontroller 720, which programmable microcontroller 720 controls various operations of IMD 701, including cardiac monitoring and/or stimulation therapies. Microcontroller 720 includes a microprocessor (or equivalent control circuitry), RAM and/or ROM memory, logic and timing circuitry, state machine circuitry, and I/O circuitry.

IMD 701 also includes a pulse generator 722, which pulse generator 722 generates stimulation pulses and communication pulses for delivery through one or more electrodes coupled thereto. Pulse generator 722 is controlled by microcontroller 720 via control signal 724. The pulse generator 722 may be coupled to the select electrode(s) via an electrode configuration switch 726, the electrode configuration switch 726 including a plurality of switches for connecting the desired electrode to appropriate I/O circuitry, thereby facilitating electrode programmability. Switch 726 is controlled by a control signal 728 from microcontroller 720.

In the embodiment of fig. 7, a single pulse generator 722 is illustrated. Optionally, the IMD may include a plurality of pulse generators similar to pulse generator 722, where each pulse generator is coupled to one or more electrodes and controlled by microcontroller 720 to deliver the selected stimulation pulse(s) to the corresponding electrode(s).

Microcontroller 720 is shown to include timing control circuit 732 to control the timing of the stimulation pulses (e.g., pacing rate, Atrioventricular (AV) delay, atrial-to-atrial (a-a) delay, or ventricular-to-ventricular (V-V) delay, etc.). The timing control circuit 732 may also be used for timing of refractory periods, blanking intervals, noise detection windows, evoked response windows, alarm intervals, mark channel timing, and the like. Microcontroller 720 also has arrhythmia detector 734 and morphology detector 736 for detecting arrhythmia conditions. Although not shown, microcontroller 720 may also include other specialized circuitry and/or firmware/software components that facilitate monitoring various conditions of the patient's heart and managing pacing therapies. Microcontroller 720 is also shown to include a false R-R interval detector 740 that may be used to perform embodiments of the present technique described above with reference to fig. 1-6. The false R-R interval detector 740 may be more generally implemented using hardware, software, firmware, and/or combinations thereof. The microcontroller may include a processor. The microcontroller and/or its processor may be used to perform the methods of the present technology described herein.

IMD 701 may also be equipped with a communication modem (modulator/demodulator) to enable wireless communication with a remote slave (slave) pacing unit. A modem may include one or more transmitters and two or more receivers. In one embodiment, the modem may use low or high frequency modulation. As one example, the modem may transmit implant (i2i) messages and other signals through conductive communication between a pair of electrodes. Such a modem may be implemented in hardware as part of microcontroller 720 or as software/firmware instructions programmed into and executed by microcontroller 720. Alternatively, the modem may be placed separately from the microcontroller as a stand-alone component.

IMD 701 includes sensing circuitry 744, which sensing circuitry 744 is selectively coupled to one or more electrodes performing sensing operations through switches 726 to detect the presence of cardiac activity in the right ventricle of the heart. The sense circuit 744 may include dedicated sense amplifiers, multiplexed amplifiers, or shared amplifiers. It may also employ one or more low power precision amplifiers with programmable gain and/or automatic gain control, band pass filtering, and threshold detection circuitry to selectively sense cardiac signals of interest. Automatic gain control enables the unit to sense low amplitude signal characteristics of atrial fibrillation. The switches 726 determine the sensed polarity of the cardiac signal by selectively closing the appropriate switches. In this way, the clinician can program the sensing polarity independently of the stimulation polarity.

The output of sensing circuit 744 is connected to microcontroller 720, which microcontroller 720 in turn triggers or deactivates pulse generator 722 in response to the presence or absence of cardiac activity. Sensing circuit 744 receives control signals 746 from microcontroller 720 for the purpose of controlling the timing of gain, threshold, polarization charge removal circuits (not shown), and any partitioning circuits (not shown) coupled to the inputs of the sensing circuit.

In the embodiment of fig. 7, a single sensing circuit 744 is illustrated. Optionally, the IMD may include a plurality of sensing circuits similar to sensing circuit 744, where each sensing circuit is coupled to one or more electrodes and controlled by microcontroller 720 to sense electrical activity detected at the corresponding one or more electrodes. The sensing circuit 744 may operate in a unipolar sensing configuration or in a bipolar sensing configuration.

IMD 701 also includes a analog-to-digital (a/D) Data Acquisition System (DAS)750, which DAS 750 is coupled to one or more electrodes via switches 726 to sample cardiac signals across any pair of desired electrode pairs. The data acquisition system 750 is configured to acquire intracardiac electrogram signals, convert the raw analog data to digital data, and store the digital data for later processing and/or telemetry transmission to an external device 754 (e.g., a programmer, local transceiver, or diagnostic system analyzer). Data acquisition system 750 is controlled by control signal 756 from microcontroller 720.

Microcontroller 720 is coupled to memory 760 by a suitable data/address bus. Programmable operating parameters used by microcontroller 720 are stored in memory 760 and used to customize the operation of IMD 701 to suit the needs of a particular patient. Such operating parameters define, for example, pacing pulse amplitude, pulse duration, electrode polarity, rate, sensitivity, automation characteristics, arrhythmia detection criteria, and the amplitude, waveform, and vector of each shock pulse to be delivered to the patient's heart within each respective layer of therapy.

Operating parameters of IMD 701 may be non-invasively programmed into memory 760 by telemetry circuit 764 in telemetry communication with external device 754 via communication link 766. Telemetry circuit 764 allows intracardiac electrograms and status information (contained in microcontroller 720 or memory 760) related to the operation of IMD 701 to be transmitted to external device 754 via communication link 766.

IMD 701 may also include a magnetic detection circuit (not shown) coupled to microcontroller 720 to detect when a magnet is placed over the unit. The magnet may be used by a clinician to perform various testing functions of IMD 701 and/or to signal to microcontroller 720 that external device 754 is in place to receive data from microcontroller 720 or transmit data to microcontroller 720 through telemetry circuit 764.

IMD 701 may also include one or more physiological sensors 770. Such sensors are commonly referred to as "rate-response" sensors because they are typically used to adjust the pacing stimulation rate according to the patient's exercise state. However, the physiological sensor(s) 770 may also be used to detect changes in cardiac output, changes in the physiological condition of the heart, or diurnal changes in activity (e.g., to detect sleep and wake states). The signal generated by the physiological sensor(s) 770 is passed to microcontroller 720 for analysis. Microcontroller 720 responds by adjusting various pacing parameters (such as rate, AV delay, V-V delay, etc.) that are delivered to the atrial and ventricular pacing pulses. Although shown as being included within IMD 701, one or more physiological sensors 770 may be external to IMD 701, yet implanted within or carried by the patient. Examples of physiological sensors include, for example, sensors that sense respiration rate, pH of blood, ventricular gradients, activity, position/posture, Minute Ventilation (MV), and the like.

A battery 772 provides operating power for all components in IMD 701. The battery 772 is preferably capable of operating at low current drain for long periods of time and capable of providing high current pulses (for capacitor charging) when the patient requires a shock pulse (e.g., over 2A at voltages above 2V for 10 seconds or longer). The battery 772 also desirably has predictable discharge characteristics so that selective replacement times can be detected. As one example, IMD 701 uses a lithium/silver vanadium oxide battery.

IMD 701 also includes impedance measurement circuitry 774, which may be used in a number of ways, including: lead impedance monitoring during acute and chronic phases to correctly position the lead or dislodgement; detecting an operable electrode and automatically switching to an operable pair when the displacement occurs; measuring respiratory or minute ventilation; measuring thoracic impedance to determine a shock threshold; detecting when a device is implanted; measuring stroke volume; and detecting opening of the heart valve; and so on. Impedance measurement circuit 774 is coupled to switch 726 so that any desired electrode may be used. In this embodiment, IMD 701 further includes a shock circuit 780 coupled to microcontroller 720 via data/address bus 782.

The embodiments of the present technology described above have been primarily described for use with an implantable medical device or system that monitors the HR and/or one or more types of arrhythmia episodes based on R-R intervals, which, as described above, may be, for example, true R-R intervals or false (e.g., oversensing) R-R intervals. Alternatively, such embodiments of the present technology may be used with a non-implantable device or system (also referred to as an external device or system) that includes at least two electrodes in contact with the skin of a person and is used to monitor HR and/or monitor one or more types of arrhythmia episodes based on R-R intervals. More specifically, such embodiments may alternatively be used with or implemented by, but not limited to, user-wearable devices, such as wrist-worn devices, or user-wearable devices designed to be wearable on one or more other portions of a person's body other than the wrist (e.g., on the ankle, upper arm, or chest). Such a user-wearable device may include: an electrode configured to contact a person's skin; sensing circuitry coupled to the electrodes and configured to obtain a signal indicative of electrical activity of the patient's heart; and at least one of a processor or a controller configured to execute one or more of the algorithms described above. Such user-wearable devices (or more generally, external devices or systems) may monitor AF and/or other type(s) of arrhythmia and determine when a false positive detection is present. Additionally, or alternatively, such user-wearable devices (or more generally, external devices or systems) may monitor a person's HR and determine when measurements of HR may be inaccurate due to oversensing. The user-wearable device may both obtain a signal indicative of the electrical activity of the patient's heart and monitor the person's HR and/or arrhythmia(s) based on the R-R interval obtained from the obtained signal. Alternatively, the user-wearable device may be communicatively coupled to another external device (such as a smartphone or tablet), and the other external device may obtain a signal from the user-wearable device and monitor the person's HR and/or arrhythmia(s) based on the R-R interval. A user-wearable device or other external device or system may determine when false positives may be present and/or when measured HR is inaccurate due to oversensing. Other implementations of such external devices or systems are possible and within the scope of the embodiments described herein.

It is to be understood that the subject matter described herein is not limited in its application to the details of construction and the arrangement of components set forth in the description or illustrated in the drawings. The subject matter described herein is capable of other embodiments and of being practiced or of being carried out in various ways. Also, it is to be understood that the phraseology and terminology used herein is for the purpose of description and should not be regarded as limiting. The use of "including," "comprising," or "having" and variations thereof is meant to encompass the items listed thereafter and equivalents thereof as well as additional items. In addition, it should be noted that, unless otherwise noted, the term "based on," as used herein, should be interpreted to mean based, at least in part, on what implies that there may be one or more additional factors from which a decision may be made. For example, if the decision is based on the result of the comparison, the decision may be based on one or more other factors in addition to the result of the comparison.

Embodiments of the present technology have been described above with the aid of functional building blocks illustrating the performance of specified functions and relationships thereof. For ease of description, boundaries of these functional building blocks have often been defined herein. Alternate boundaries can be defined so long as the specified functions and relationships thereof are appropriately performed. Accordingly, any such alternate boundaries are within the scope and spirit of the claimed invention. For example, it would be possible to combine or separate some of the steps shown in fig. 4 and 5. It would also be possible to perform only a subset of the steps, such as only step 404 and 420, in order to determine whether one or more R-R intervals within a group or set of R-R intervals are false R-R interval(s), or more specifically, R-R interval(s) associated with R-wave undersensing or AV conduction block. For another example, it is possible to change the boundaries of some of the blocks shown in FIG. 7.

It is to be understood that the above description is intended to be illustrative, and not restrictive. For example, the above-described embodiments (and/or aspects thereof) may be used in combination with each other. In addition, many modifications may be made to adapt a particular situation or material to the teachings of the embodiments of the present technology without departing from the scope thereof. While the dimensions, types of materials, and coatings described herein are intended to define the parameters of embodiments of the present technology, they are by no means limiting and are exemplary embodiments. Many other embodiments will be apparent to those of skill in the art upon reviewing the above description. The scope of embodiments of the technology should, therefore, be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled. In the appended claims, the terms "including" and "in which" are used as the plain-english equivalents of the respective terms "comprising" and "in which". Also, in the following claims, the terms "first," "second," and "third," etc. are used merely as labels, and are not intended to impose numerical requirements on their objects. Additionally, the limitations of the following claims are not written in component-plus-function form, and are not intended to be interpreted based on 35u.s.c. § 112(f), unless such claim limitations explicitly use the phrase "component for … …," followed by a functional statement without further structure.