WO2025257637A1

WO2025257637A1 - Frequency-based determination of cardiac oversensing in medical devices

Info

Publication number: WO2025257637A1
Application number: PCT/IB2025/055226
Authority: WO
Inventors: Subham GHOSH
Original assignee: Medtronic Inc
Current assignee: Medtronic Inc
Priority date: 2024-06-14
Filing date: 2025-05-20
Publication date: 2025-12-18
Anticipated expiration: 2026-12-14

Abstract

Example systems, devices, and techniques are disclosed for frequency-based determination of oversensing. An example system includes an implantable medical device (IMD) including sensing circuitry configured to sense a cardiac electrogram (EGM) of a patient. The IMD includes processing circuitry configured to obtain the cardiac EGM of the patient. The processing circuitry is configured to determine a suspected arrhythmia episode based on the cardiac EGM. The processing circuitry is configured to apply a high pass filter to the cardiac EGM to generate a high pass filtered EGM. The processing circuitry is configured to classify, based on the cardiac EGM and the high pass filtered EGM, the suspected arrhythmia episode as a true arrhythmia episode or a false arrhythmia episode due to oversensing.

Description

FREQUENCY-BASED DETERMINATION OF CARDIAC OVERSENSING IN MEDICAL DEVICES

[0001] This application claims the benefit of U.S. Provisional Patent Application Serial No. 63/660,041, filed June 14, 2024, the entire content of which is incorporated herein by reference.

TECHNICAL FIELD

[0002] The disclosure relates generally to medical device systems and, more particularly, cardiac monitoring by medical devices.

BACKGROUND

[0003] Some types of implantable medical devices, such as cardiac pacemakers or implantable cardioverter defibrillators, provide electrical therapy to a heart of a patient via electrodes of one or more implantable leads. The electrical therapy may be delivered to the heart in the form of pulses for pacing or shocks for cardioversion or defibrillation. In some cases, an implantable medical device may sense the presence arrhythmias of the heart and control the delivery of electrical therapy to the heart based on the sensing. Other medical devices may detect arrhythmias, but do not themselves deliver responsive therapy.

SUMMARY

[0003] In general, this disclosure describes example techniques related to determining whether a sensed arrhythmia episode is a true arrhythmia episode or a false arrhythmia episode due to oversensing and, in some examples, controlling the delivery of therapy based on the determination. Oversensing can be a problem with implantable cardiac devices like ICDs. For example, ICDs that use integrated bipolar electrodes, which are more widely separated than traditional short bipole sensing electrodes, are more vulnerable to receiving far-field electrical activity (e.g., P-waves) which may lead to oversensing and possible overdetection of arrhythmia episodes. Implantable or external defibrillators and or monitors including cutaneous, subcutaneous, substernal, and/or extravascular electrodes may be similarly vulnerable to receiving far-field electrical activity. Therefore, it may be desirable to detect oversensing in a detected tachyarrhythmia episode in such devices, especially when detecting on-device (e.g., on the ICD), to avoid delivery of inappropriate therapy.

[0004] In one example, this disclosure describes a system comprising: sensing circuitry configured to sense a cardiac electrogram (EGM) of a patient; and processing circuitry configured to: obtain the cardiac EGM of the patient; determine a suspected arrhythmia episode based on the cardiac EGM; apply a high pass filter to the cardiac EGM to generate a high pass filtered EGM; and classify, based on the cardiac EGM and the high pass filtered EGM, the suspected arrhythmia episode as a true arrhythmia episode or a false arrhythmia episode due to oversensing.

[0005] In another example, this disclosure describes a method comprising: sensing, by sensing circuitry, a cardiac electrogram (EGM) of a patient; and obtaining, by processing circuitry, the cardiac EGM of the patient; determining, by the processing circuitry, a suspected arrhythmia episode based on the cardiac EGM; applying, by the processing circuitry, a high pass filter to the cardiac EGM to generate a high pass filtered EGM; and classifying, by the processing circuitry and based on the cardiac EGM and the high pass filtered EGM, the suspected arrhythmia episode as a true arrhythmia episode or a false arrhythmia episode due to oversensing.

[0006] In another example, this disclosure describes an implantable medical device comprising: sensing circuitry configured to sense a cardiac electrogram (EGM) of a patient; and processing circuitry configured to: obtain the cardiac EGM of the patient; determine a suspected arrhythmia episode based on the cardiac EGM; apply a high pass filter to the cardiac EGM to generate a high pass filtered EGM; and classify, based on the cardiac EGM and the high pass filtered EGM, the suspected arrhythmia episode as a true arrhythmia episode or a false arrhythmia episode due to oversensing.

[0007] This summary is intended to provide an overview of the subject matter described in this disclosure. It is not intended to provide an exclusive or exhaustive explanation of the methods and systems described in detail within the accompanying drawings and description below. The details of one or more aspects of the disclosure are set forth in the accompanying drawings and the description below. BRIEF DESCRIPTION OF DRAWINGS

[0008] The details of one or more examples of this disclosure are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of this disclosure will be apparent from the description and drawings, and from the claims. [0009] FIG. 1 is conceptual diagram illustrating an example medical device system, in accordance with some examples of the current disclosure.

[0010] FIG. 2 is a conceptual diagram further illustrating the implantable medical device (IMD) of FIG. 1, in accordance with some examples of the current disclosure.

[0011] FIG. 3 is a functional block diagram illustrating an example configuration of implantable medical device of FIGS. 1 and 2, in accordance with some examples of the current disclosure.

[0012] FIG. 4 is a functional block diagram illustrating an example configuration of the external device of the medical system of FIG. 1, in accordance with some examples of the current disclosure.

[0013] FIG. 5 is a block diagram illustrating an example system that includes an external device, such as a server, and one or more computing devices that are coupled to the IMD and external device shown in FIG. 1 via a network, in accordance with some examples of the current disclosure.

[0014] FIGS. 6A-6B are conceptual diagrams illustrating example EGM signals and high pass filtered EGM signals according to one or more aspects of this disclosure.

[0015] FIGS. 7A-7B are conceptual diagrams illustrating graphs of example ratios of high pass filtered EGMs to EGMs in accordance with one or more aspects of this disclosure. [0016] FIG. 8 is a flow diagram illustrating an example technique for frequency-based determination of oversensing according to one or more aspects of this disclosure.

[0017] Like reference characters denote like elements throughout the description and figures.

DETAILED DESCRIPTION

[0018] An implantable medical system includes an implantable medical device (IMD), such as a pacemaker, implantable cardioverter defibrillator (ICD), or implantable cardiac resynchronization therapy (CRT) device, that may provide therapies for maintaining and restoring normal cardiac rhythms by pacing and/or by delivering electrical shock therapy for cardioverting or defibrillating the heart. One or more electrical leads connected to the IMD may be inserted into or in proximity to the heart of the patient. The leads carry therapeutic current from the IMD to the heart tissue to either stimulate the heart using low energy pacing pulses or cardiovert/defibrillate the heart using relatively higher energy shocks. The IMD also uses the leads for sensing electrical activity, such as electrogram (EGM) signals, from the heart. Using the EGM signals, the IMD may detect cardiac depolarizations, repolarizations, or other activity, and detect arrhythmias responsive to which the IMD may deliver the electrical therapy. In some examples, within the IMD, sense amplifiers may amplify EGM signals from electrodes on the leads, and the amplified EGM signals may be used by the IMD to sense intrinsic depolarizations of the atria (referred to as P-waves) and the ventricles (referred to as R-waves).

[0019] The implantable medical systems may also include one or more leads that are wholly or partially implanted within the patient and are configured to couple to the IMDs. In some examples, the implantable leads include an integrated bipolar lead, in which an electrode used to deliver relatively higher energy shock therapy, e.g., a coil electrode, serves as either an anode or cathode of a sensing vector, such as a sensing bipole. The sensing bipole of an integrated bipolar lead may have larger (e.g., wider) spacing than a traditional bipolar lead that includes, for example, two relatively more closely spaced electrodes, such as a tip electrode and a ring electrode or two closely spaced ring electrodes. Because of the larger interelectrode spacing, the integrated bipolar lead may capture more of far-field signals. In some examples, an integrated bipolar lead may include a defibrillator coil electrode connected to a ring electrode with the combination of the defibrillator coil electrode and the ring electrode acting as an anode or cathode of a sensing bipole of the integrated bipolar lead. In some examples, integrated bipolar leads may include any lead configured to provide an integrated bipole for sensing, e.g., whether or not the lead is also configured to provide or more traditional bipoles, e.g., includes more closely spaced ring and tip electrodes.

[0020] Integrated bipolar leads that are implanted ventricularly consequently may have a higher chance of atrial oversensing, particularly for integrated bipolar leads that are implanted in the left bundle branch area, septal area, or other location higher up / closer to the atrium than conventional apical implantation. In some examples, a position of an integrated bipolar lead may be adjusted, such as by an implanter, at implant to reduce the chance of a ventricularly -implanted integrated bipolar lead oversensing atrial far-field activity. However, in some cases over time, the ventricularly-implanted integrated bipolar lead may sense atrial far-field activity which may lead to atrial oversensing. For example, after the leads are implanted, a position of the leads may change, such as due to patient movement, which may cause an increase in sensed atrial far-field activity by an integrated bipolar lead implanted in a ventricle, which can lead to atrial oversensing, e.g., misidentification of features in the EGM associated with atrial depolarizations as ventricular depolarizations. Atrial oversensing may lead to a variety of undesired outcomes, such as over-detection of tachyarrhythmias, inhibition of cardiac resynchronization therapy (CRT) and/or loss of optimal AV interval for CRT or other synchronous ventricular pacing.

[0021] Oversensing can occur with implantable cardiac devices like ICDs. For example, ICDs with integrated bipolar electrodes more widely separated from each other than traditional short bipole sensing electrodes are more vulnerable to receiving far-field electrical activity (e.g., P-waves) which may lead to oversensing and possible over-detection of arrhythmia episodes. Therefore, it may be desirable to detect oversensing in a detected tachyarrhythmia episode, especially when detecting on-device (e.g., on the ICD), to avoid delivery of inappropriate therapy.

[0022] In general, this disclosure describes example techniques related to frequencybased discrimination of oversensing. Oversensing may cause a medical device or system to detect a false arrhythmia episode. For example, a detected arrhythmia episode may be a true arrhythmia episode or a false arrhythmia episode due to oversensing. This disclosure describes example medical systems, devices, and techniques for determining whether a potential arrhythmia is a true tachyarrhythmia episode or an over-sensed episode.

[0023] For example, the medical device or system may obtain an original sensed signal and apply a high pass fdter to the original sensed signal. The medical device or system may determine a characteristic, such as a peak-to-peak amplitude, of the original sensed signal within a predetermined time window and determine the characteristic of the high pass fdtered signal within the predetermined time window. The medical device or system may determine a ratio of the characteristics.

[0024] The medical device or system may determine whether an episode is a true tachyarrhythmia or a false tachyarrhythmia based on one or more determined ratios. For example, the medical device or system may compare the ratios to a threshold and look for patterns in results of the comparisons to determine whether an episode is a true tachyarrhythmia or a false tachyarrhythmia.

[0025] FIG. 1 illustrates example medical device system 10 in conjunction with patient 14. Medical device system 10 is an example of a medical device system that is configured to implement the example techniques described herein for frequency-based determination of oversensing. In some examples, medical device system 10 includes an implantable medical device (IMD) 16 in communication with external device 24. In the illustrated example, IMD 16 may be coupled to leads 18, 20, and 22. IMD 16 may be, for example, an implantable cardioverter, an implantable defibrillator, an implantable pacemaker, and/or other implantable medical device that provides electrical signals to heart 12 and senses electrical activity of heart 12 via electrodes coupled to one or more of leads 18, 20, and 22. In some examples, the techniques described herein may be implemented in medical devices that do not deliver therapy, medical devices that are not coupled to their electrodes via leads, and/or medical devices that are not implanted.

[0026] Leads 18, 20, 22 extend into heart 12 of patient 14 to sense electrical activity of heart 12 and to deliver electrical therapy to heart 12. In the example shown in FIG. 1, right ventricular (RV) lead 18 extends through one or more veins (not shown), the superior vena cava (not shown), and right atrium (RA) 26, and into RV 28. Left ventricular (LV) coronary sinus lead 20 extends through one or more veins, the vena cava, right atrium 26, and into the coronary sinus 30 to a region adjacent to the free wall of LV 32 of heart 12. Right atrial (RA) lead 22 extends through one or more veins and the vena cava, and into the RA 26 of heart 12. In some examples, IMD 16 may have a different number of leads. For example, IMD 16 may only have lead 18, or may have lead 18 and lead 22.

[0027] In some examples, lead 18 may be referred to as a ventricularly-implanted integrated bipolar lead. In some examples, lead 22 may be referred to as an atrial lead. Although an apical implantation location of lead 18 is illustrated in FIG. 1, ventricularly- implanted integrated bipolar lead 18 may be implanted in other locations in some examples, such as proximate the left bundle branch, ventricular septum, or more generally closer to the right atrium.

[0028] IMD 16 may sense electrical signals attendant to the depolarization and repolarization of heart 12 via electrodes (not shown in FIG. 1) coupled to at least one of the leads 18, 20, 22. In some examples, IMD 16 may also sense electrical signals attendant to the depolarization and repolarization of heart 12 via extravascular electrodes (e.g., electrodes positioned outside the vasculature of patient 14), such as epicardial electrodes, external surface electrodes, subcutaneous electrodes, and the like. The configurations of electrodes used by IMD 16 for sensing and pacing may be unipolar or bipolar.

[0029] The natural electrical activation system of a human heart 12 involves several sequential conduction pathways starting with the sino-atrial (SA) node, and continuing through the atrial conduction pathways of Bachmann's bundle and intemodal tracts at the atrial level, followed by the atrio-ventricular (AV) node, Common Bundle of His, right and left bundle branches, and a final distribution to the distal myocardial terminals via the Purkinje fiber network. In a normal electrical activation sequence, the cardiac cycle commences with the generation of a depolarization wave at the SA Node in the wall of RA 26. The depolarization wave is transmitted through the atrial conduction pathways of Bachmann's Bundle and the Internodal Tracts at the atrial level into the LA 33 septum. When the atrial depolarization wave has reached the AV node, the atrial septum, and the furthest walls of the right and left atria 26, 33, respectively, the atria 26, 33 may contract as a result of the electrical activation. The aggregate right atrial and left atrial depolarization wave appears as the P-wave of the PQRST complex of a cardiac EGM. When the amplitude of the atrial depolarization wave passing between a pair of unipolar or bipolar pace/sense electrodes located on or adjacent RA 26 and/or LA 33 exceeds a threshold, it is detected as a sensed P-wave. The sensed P-wave may also be referred to as an atrial intrinsic event.

[0030] During or after the atrial contractions, the AV node distributes the depolarization wave inferiorly down the Bundle of His in the intraventricular septum. The depolarization wave may travel to the apical region of heart 12 and then superiorly though the Purkinje Fiber network. The aggregate right ventricular and left ventricular depolarization wave and the subsequent T-wave accompanying re-polarization of the depolarized myocardium may appear as the QRST portion of the PQRST cardiac cycle complex. When the amplitude of the QRS ventricular depolarization wave passing between a bipolar or unipolar pace/sense electrode pair located on or adjacent RV 28 and/or LV 32 exceeds a threshold, it is detected as a sensed R-wave. The sensed R-wave may also be referred to as a ventricular intrinsic event, an RV sensing event (RVs), or an LV sensing event (LVs) depending upon the ventricle in which the electrodes of one or more of leads 18, 20, 22 are configured to sense in a particular case. [0031] In some examples, IMD 16 provides defibrillation therapy and/or cardioversion therapy via electrodes located on at least one of the leads 18, 20, 22. Based on signals sensed via one or more of leads 18, 20, 22, e.g., the detection of R-waves, IMD 16 may detect arrhythmia of heart 12, such as fibrillation or other tachyarrhythmia of ventricles 28 and 32, and deliver antitachyarrhythmia therapy to heart 12 in the form of electrical shocks. In some examples, IMD 16 is programmed to deliver a progression of therapies, e.g., shocks with increasing energy levels, until a tachyarrhythmia of heart 12 is stopped. In examples in which IMD 16 provides antitachyarrhythmia shock therapy, IMD 16 may detect tachyarrhythmia by employing any one or more tachyarrhythmia detection techniques known in the art.

[0032] In some examples, external device 24 may be a handheld computing device or a computer workstation. External device 24 may include a user interface that receives input from a user. The user interface may include, for example, a keypad and a display, which may for example, be a liquid crystal display (LCD) or light emitting diode (LED) display. The keypad may take the form of an alphanumeric keypad or a reduced set of keys associated with particular functions. External device 24 can additionally or alternatively include a peripheral pointing device, such as a mouse, via which a user may interact with the user interface. In some examples, a display of external device 24 may include a touch screen display, and a user may interact with external device 24 via the display.

[0033] A user, such as a physician, technician, or other clinician, may interact with external device 24 to communicate with IMD 16. For example, the user may interact with external device 24 to retrieve physiological or diagnostic information from IMD 16. A user may also interact with external device 24 to program IMD 16, e.g., to select values for operational parameters of the IMD 16.

[0034] For example, the user may use external device 24 to retrieve information from IMD 16 regarding the rhythm of heart 12, trends therein over time, or arrhythmia episodes. As another example, the user may use external device 24 to retrieve information from IMD 16 regarding other sensed physiological parameters of patient 14, such as sensed electrical activity, activity, posture, respiration, or thoracic impedance. As another example, the user may use external device 24 to retrieve information from IMD 16 regarding the performance or integrity of IMD 16 or other components of system 10, such as leads 18, 20, and 22, or a power source of IMD 16. In such examples, physiological parameters of patient 14 and data regarding IMD 16 may be stored in a memory of IMD 16 for retrieval by the user. The user may use external device 24 to program parameters of therapy delivery by IMD 16 and/or parameters used for depolarization and/or arrhythmia detection by IMD 16. In some examples, the user may activate certain features of IMD 16 by entering a single command via external device 24, such as depression of a single key or combination of keys of a keypad or a single point- and- select action with a pointing device.

[0035] IMD 16 and external device 24 may communicate via wireless communication using any techniques known in the art. Examples of communication techniques may include, for example, include radiofrequency (RF) telemetry, which may be an RF link established via an antenna according to Bluetooth®, WiFi, or medical implant communication service (MICS), though other techniques are also contemplated. In some examples, external device 24 may include a programming head that may be placed proximate to the patient’s body near the IMD 16 implant site in order to improve the quality or security of communication between IMD 16 and external device 24.

[0036] FIG. 2 is a conceptual diagram further illustrating an example configuration of IMD 16 in conjunction with heart 12. In the example of FIG. 2, IMD 16 is coupled to leads 18 and 22. IMD 16 may be coupled to two leads as illustrated in FIG. 2, three leads as illustrated in FIG. 1, or any other numbers of leads. Furthermore, the leads coupled to IMD 16 may be configured differently than those illustrated herein, but IMD 16 may nevertheless implement the techniques of this disclosure. While IMD 16 is shown, it should be understood that the some or all of the techniques described herein may be implemented in other medical devices or other IMDs.

[0037] As shown in FIG. 2, the proximal ends of leads 18 and 22 are connected to a connector block 34 of IMD 16 to electrically couple the electrodes on the leads to circuitry within the housing 60 of IMD 16. In some examples, proximal ends of leads 18 and 22 may include electrical contacts that electrically couple to respective electrical contacts within connector block 34 of IMD 16. Each of the leads 18 and 22 includes an elongated insulative lead body, which may carry a number of conductors, e.g., a conductor for each electrode on the lead, each of which may be connected to a respective contact at the proximal end of the lead. Bipolar electrode 42 is located adjacent to a distal end of lead 18 in right ventricle 28. In addition, bipolar electrodes 48 and 50 are located adjacent to a distal end of lead 22 in right atrium 26. [0038] In some examples, lead 18 may be referred to as a ventricularly-implanted integrated bipolar lead 18 or a ventricular integrated bipolar lead 18. Lead 18 may be configured to facilitate sensing of a ventricular EGM by IMD 16 via an integrated bipolar pair including tip electrode 42 and elongated electrode 62. In some examples, lead 22 may be referred to as an atrial lead 22.

[0039] Electrode 48 may take the form of ring electrodes, and electrodes 42 and 50 may take the form of helix tip electrodes mounted, e.g., with a fixed screw, within insulative electrode heads 52 and 56, respectively. Some helix tip electrodes can include a mechanism for an extendable/retractable helix. In other examples, one or more of electrodes 42 and 50 may take the form of small circular electrodes at the tip of a tined lead or other fixation element. Leads 18 and 22 also include elongated electrodes 62 and 66, respectively, each of which may take the form of a coil, and may be configured for delivery of relatively high energy therapeutic shocks. Each of the electrodes 42, 48, 50, 62 and 66 may be electrically coupled to a respective one of the conductors within the lead body of its associated lead 18 and 22, and thereby coupled to respective ones of the electrical contacts on the proximal end of leads 18 and 22.

[0040] In the example of FIG. 2, IMD 16 includes a housing electrode 58, which may be formed integrally with an outer surface of hermetically-sealed housing 60 of IMD 16, or otherwise coupled to housing 60. In some examples, housing electrode 58 is defined by an uninsulated portion of an outward facing portion of housing 60 of IMD 16. Other division between insulated and uninsulated portions of housing 60 may be employed to define two or more housing electrodes. In some examples, housing electrode 58 comprises substantially all of housing 60.

[0041] IMD 16 may sense electrical signals attendant to the depolarization and repolarization of heart 12 via electrodes 42, 48, 50, 62, and 66. The electrical signals are conducted to IMD 16 from the electrodes via the respective leads 18 and 22. IMD 16 may sense such electrical signals via any bipolar combination of electrodes 40, 42, 48, 50, 62, and 66. For example, IMD 16 may sense a ventricular EGM via an integrated bipolar pair including tip electrode 42 and elongated electrode 62. Furthermore, any of the electrodes 42, 48, 50, 62, and 66 may be used for unipolar sensing in combination with housing electrode 58. The combination of electrodes used for sensing may be referred to as a sensing configuration or electrode vector. [0042] In some examples, IMD 16 delivers pacing pulses via bipolar combinations of electrodes 42, 48, 50, 62, and 66 to produce depolarization of cardiac tissue of heart 12. In some examples, IMD 16 delivers pacing pulses via any of electrodes 42, 48 and 50 in combination with housing electrode 58 in a unipolar configuration. Furthermore, IMD 16 may deliver antitachyarrhythmia shocks, e.g., defibrillation shocks, to heart 12 via any combination of elongated electrodes 62 and 66, and housing electrode 58. IMD 16 may also use electrodes 58, 62, and 66 to deliver cardioversion shocks to heart 12. Electrodes 62 and 66 may be fabricated from any suitable electrically conductive material, such as, but not limited to, platinum, platinum alloy or other materials known to be usable in implantable defibrillation electrodes.

[0043] The configurations of system 10 illustrated in FIGS. 1 and 2 are merely examples. In other examples, a system may include extravascular leads and electrodes instead of or in addition to the illustrated transvenous leads 18 and 22. Further, IMD 16 need not be implanted within the patient. In examples in which IMD 16 is not implanted in the patient, IMD 16 may sense electrical signals and/or deliver antitachy arrhythmia shocks and other therapies to heart 12 via percutaneous leads that extend through the skin of a patient to a variety of positions within or outside of heart 12.

[0044] FIG. 3 is a functional block diagram of one example configuration of IMD 16 of FIGS. 1 and 2. In the illustrated example, IMD 16 includes memory 70, processing circuitry 80, sensing circuitry 82, one or more accelerometers 84, therapy delivery circuitry 86, telemetry circuitry 88, and power source 90, one or more of which may be disposed within housing 60 of IMD 16. In some examples, memory 70 includes computer-readable instructions that, when executed by processing circuitry 80, cause IMD 16 and processing circuitry 80 to perform various functions attributed to IMD 16 and processing circuitry 80 herein. Memory 70 may include any volatile, non-volatile, magnetic, optical, or electrical media, such as a random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), electrically-erasable programmable ROM (EEPROM), flash memory, or any other digital media. Sensed physiological parameters of patient 14 (e.g., EGM or ECG signals or atrial events) may be stored by memory 70. While the example of FIG. 3 may include therapy delivery circuitry 86, in some examples, IMD 16 may not include such circuitry. [0045] Processing circuitry 80 may include one or more of a microprocessor, a controller, digital signal processing circuitry (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or equivalent discrete or integrated logic circuitry. In some examples, processing circuitry 80 may include multiple components, such as any combination of one or more microprocessors, one or more controllers, one or more DSPs, one or more ASICs, or one or more FPGAs, as well as other discrete or integrated logic circuitry. The functions attributed to processing circuitry 80 herein may be embodied as software, firmware, hardware or any combination thereof. In some examples, processing circuitry 80 may include a high pass filter 81. According to the techniques described herein, processing circuitry 80 may be configured to obtain the cardiac EGM of the patient; determine a suspected arrhythmia episode based on the cardiac EGM; apply a high pass filter to the cardiac EGM to generate a high pass filtered EGM; and classify, based on the cardiac EGM and the high pass filtered EGM, the suspected arrhythmia episode as a true arrhythmia episode or a false arrhythmia episode due to oversensing.

[0046] Sensing circuitry 82 is configured to monitor signals from at least one of electrodes 42, 48, 50, 58, 62, or 66 in order to monitor electrical activity of heart 12, e.g., via EGM signals. For example, sensing circuitry 82 may sense atrial intrinsic events (e.g., a P-wave) with electrodes 48, 50, 66 within RA 26. In some examples, sensing circuitry 82 includes switching circuitry to select which of the available electrodes are used to sense the electrical activity of heart 12. For example, processing circuitry 80 may select the electrodes that function as sense electrodes via the switching circuitry within sensing circuitry 82, e.g., by providing signals via a data/address bus. In some examples, sensing circuitry 82 includes one or more sensing channels, each of which may comprise an amplifier. In some examples, sensing circuitry 82 may include one or more filters, for example, for smoothing sensed signals. However, any such filters are not to be confused with high pass filter 81. In response to the signals from processing circuitry 80, the switching circuitry of sensing circuitry 82 may couple the outputs from the selected electrodes to one of the sensing channels.

[0047] In some examples, one channel of sensing circuitry 82 may include an R-wave amplifier that receives signals from selected pairs of electrodes 42, 62, and 60, which are used for pacing and sensing in RV 28 of heart 12. In accordance with the techniques of this disclosure, sensing circuitry 82 may include an R-wave amplifier that receives a signal from an integrated bipolar pair of electrodes 42 and 62, i.e., an integrated bipolar ventricular EGM signal, and detects R- waves within the signal. In some examples, the R-wave amplifiers may take the form of an automatic gain controlled amplifier that provides an adjustable sensing threshold as a function of the measured R-wave amplitude of the heart rhythm.

[0048] In addition, in some examples, one channel of sensing circuitry 82 may include a P-wave amplifier that receives signals from electrodes 48 and 50, which are used for pacing and sensing in RA 26 of heart 12. In some examples, the P-wave amplifier may take the form of an automatic gain controlled amplifier that provides an adjustable sensing threshold as a function of the measured P-wave amplitude of the heart rhythm. Examples of R-wave and P-wave amplifiers are described in U.S. Patent No. 5,117,824 to Keimel et al., which issued on June 2, 1992 and is entitled, “APPARATUS FOR MONITORING ELECTRICAL PHYSIOLOGIC SIGNALS,” and is incorporated herein by reference in its entirety. Other amplifiers may also be used. Furthermore, in some examples, one or more of the sensing channels of sensing circuitry 82 may be selectively coupled to housing electrode 58, or elongated electrodes 62, or 66, with or instead of one or more of electrodes 42, 48 or 50, e.g., for unipolar or integrated bipolar sensing of R-waves or P-waves in any of chambers 26, 28, or 32 of heart 12.

[0049] In some examples, sensing circuitry 82 includes a channel that comprises an amplifier with a relatively wider pass band than the R-wave or P-wave amplifiers. Signals from the selected sensing electrodes that are selected for coupling to this wide-band amplifier may be provided to a multiplexer, and thereafter converted to multi-bit digital signals by an analog-to-digital converter for storage in memory 70 as an EGM. In some examples, the storage of such EGMs in memory 70 may be under the control of a direct memory access circuit. Processing circuitry 80 may employ digital signal analysis techniques to characterize the digitized signals stored in memory 70 to detect and classify the patient's heart rhythm from the electrical signals. Processing circuitry 80 may detect and classify the heart rhythm of patient 14 by employing any of the numerous signal processing methodologies known in the art. In some examples, sensing 82 stores the integrated bipolar EGM, e.g., the ventricular integrated bipolar EGM, in memory 70 for windowing and further processing by processing circuitry 80 in accordance with the techniques of this disclosure.

[0050] Signals generated by sensing circuitry 82 may include, for example: an RA-event signal, which indicates a detection of a P-wave via electrodes implanted within RA 26 (FIG. 1); an LA-event signal, which indicates a detection of a P-wave via electrodes implanted within LA 33 (FIG. 1); an RV-event signal, which indicates a detection of an R-wave via electrodes implanted within RV 28; or an LV-event signal, which indicates a detection of an R-wave via electrodes implanted within LV 32.

[0051] In some examples, IMD 16 may include one or more additional sensors, such as accelerometers 84. In some examples, accelerometers 84 may comprise one or more three- axis accelerometers. Signals generated by accelerometers 84 may be indicative of, for example, gross body movement of patient 14, such as a patient posture or activity level. Regardless of the configuration of accelerometers 84, processing circuitry 80 may determine patient parameter values based on the signals obtained therefrom. Accelerometers 84 may produce and provide signals to processing circuitry 80 for a determination as to the posture and activity level of patient 14 at a given time. Processing circuitry 80 may then use the determined posture and activity level to further determine whether patient 14 is awake or asleep, and, if patient 14 is determined to be awake, to further determine whether patient 14 is at rest or exercising.

[0052] Therapy delivery circuitry 86 is electrically coupled to electrodes 42, 48, 50, 58, 62, and 66, e.g., via conductors of the respective lead 18, 20, 22, or, in the case of housing electrode 58, via an electrical conductor disposed within housing 60 of IMD 16. Therapy delivery circuitry 86 is configured to generate and deliver electrical therapy.

[0053] In some examples, therapy delivery circuitry 86 is configured to deliver cardioversion or defibrillation shocks to heart 12. The pacing stimuli, cardioversion shocks, and defibrillation shocks may be in the form of pulses. In other examples, therapy delivery circuitry 86 may deliver one or more of these types of therapy in the form of other signals, such as sine waves, square waves, or other substantially continuous time signals.

[0054] Therapy delivery circuitry 86 may include a switching circuitry, and processing circuitry 80 may use the switching circuitry to select, e.g., via a data/address bus, which of the available electrodes are used to deliver shock pulses or pacing pulses. The switching circuitry may include a switch array, switch matrix, multiplexer, or any other type of switching device suitable to selectively couple therapeutic energy to selected electrodes. In other examples, processing circuitry 80 may select a subset of electrodes 42, 48, 50, 58, 62, and 66 with which therapy is delivered to heart 12 without a switching circuitry.

[0055] Processing circuitry 80 may include pacer timing and control circuitry, which may be embodied as hardware, firmware, software, or any combination thereof. Pacer timing and control circuitry may comprise a dedicated hardware circuit, such as an ASIC, separate from other processing circuitry 80 components, such as one or more microprocessors, or a software module executed by a component of processing circuitry 80 (e.g., one or more microprocessors and/or ASICs).

[0056] In some examples, an arrhythmia detection method may include any suitable tachyarrhythmia detection algorithms. In one example, processing circuitry 80 may utilize all or a subset of the rule-based detection methods described in U.S. Patent No. 5,545,182 to Olson et al., entitled, “PRIORITIZED RULE BASED METHOD AND APPARATUS FOR DIAGNOSIS AND TREATMENT OF ARRHYTHMIAS,” which issued on August 13, 1996, or in U.S. PatentNo. 5,755,736 to Gillberg et al., entitled, “PRIORITIZED RULE BASED METHOD AND APPARATUS FOR DIAGNOSIS AND TREATMENT OF ARRHYTHMIAS,” which issued on May 26, 1998. U.S. Patent No. 5,545,182 to Olson et al. and U.S. Patent No. 5,755,736 to Gillberg et al. are incorporated herein by reference in their entireties. However, other arrhythmia detection methodologies may also be employed by processing circuitry 80 in other examples.

[0057] In some examples, processing circuitry 80 may employ an M of N rule based technique for determining a suspected arrhythmia. For example, if processing circuitry 80 detects at least M fast beats within N consecutive beats, processing circuitry 80 may determine that there is a suspected arrhythmia episode within the N consecutive beats. A fast beat may be a beat having a sensed interval from a last beat (e.g., a sensed ventricular event from a last sensed ventricular event) of a period less than (or less than or equal to) a threshold time, for example, less than 140ms.

[0058] Each fast beat within the N consecutive beats may be considered an event, such that all of the fast beats within the N consecutive beats make up or are part of the suspected arrhythmia episode. When determining whether a suspected arrhythmia episode is a true arrhythmia episode or a false arrhythmia episode due to oversensing as described herein, in some examples, processing circuitry 80 may ignore the non-fast beats occurring within the suspected arrhythmia episode. The values of M and/or N may be programmable. In some examples, M may equal 20 and N may equal 30.

[0059] If IMD 16 is configured to generate and deliver defibrillation shocks to heart 12, therapy delivery circuitry 86 may include a high voltage charge circuit and a high voltage output circuit. In the event that processing circuitry 80 determines that generation of a cardioversion or defibrillation shock is required, processing circuitry 80 may employ the escape interval counter to control timing of such cardioversion and defibrillation shocks, as well as associated refractory periods. In response to the detection of atrial or ventricular fibrillation or tachyarrhythmia requiring a cardioversion pulse, processing circuitry 80 may activate a cardioversion/defibrillation control circuitry (not shown), which may be a hardware component of processing circuitry 80 and/or a firmware or software module executed by one or more hardware components of processing circuitry 80. The cardioversion/defibrillation control circuitry may initiate charging of the high voltage capacitors of the high voltage charge circuit of therapy delivery circuitry 86 under control of a high voltage charging control line.

[0060] Processing circuitry 80 may monitor the voltage on the high voltage capacitor, e.g., via a voltage charging and potential (VCAP) line. In response to the voltage on the high voltage capacitor reaching a predetermined value set by processing circuitry 80, processing circuitry 80 may generate a logic signal that terminates charging. Thereafter, timing of the delivery of the defibrillation or cardioversion pulse by therapy delivery circuitry 86 is controlled by a cardioversion/defibrillation control circuitry (not shown) of processing circuitry 80. Following delivery of the fibrillation or tachycardia therapy, processing circuitry 80 may return therapy delivery circuitry 86 to a cardiac pacing function and await the next successive interrupt due to pacing or the occurrence of a sensed atrial or ventricular depolarization.

[0061] Therapy delivery circuitry 86 may deliver cardioversion or defibrillation shock with the aid of an output circuit that determines whether a monophasic or biphasic pulse is delivered, whether housing electrode 58 serves as cathode or anode, and which electrodes are involved in delivery of the cardioversion or defibrillation pulses. Such functionality may be provided by one or more switches or a switching circuitry of therapy delivery circuitry 86.

[0062] Telemetry circuitry 88 includes any suitable hardware, firmware, software or any combination thereof for communicating with another device, such as external device 24 (FIG. 1). Under the control of processing circuitry 80, telemetry circuitry 88 may receive downlink telemetry from and send uplink telemetry to external device 24 with the aid of an antenna, which may be internal and/or external. Processing circuitry 80 may provide the data to be uplinked to external device 24 and the control signals for the telemetry circuit within telemetry circuitry 88, e.g., via an address/data bus. In some examples, telemetry circuitry 88 may provide received data to processing circuitry 80 via a multiplexer.

[0063] In some examples, processing circuitry 80 may transmit atrial and ventricular heart signals (e.g., EGM signals) produced by atrial and ventricular sense amplifier circuits within sensing circuitry 82 to external device 24. Other types of information may also be transmitted to external device 24, such as indications of satisfaction of the far-field activity threshold and/or adjustment of the sensitivity threshold. External device 24 may interrogate IMD 16 to receive the heart signals. As used herein something may satisfy a threshold by a value or property of the something being one of greater than, greater than or equal to, less than, or less than or equal to, depending on the circumstances or use case. Processing circuitry 80 may store heart signals within memory 70, and retrieve stored heart signals from memory 70.

[0064] Telemetry circuitry 88 includes any suitable hardware, firmware, software or any combination thereof for communicating with another device, such as external device 24 (FIG. 1). Under the control of processing circuitry 80, telemetry circuitry 88 may receive downlink telemetry from and send uplink telemetry to external device 24 with the aid of an antenna, which may be internal and/or external. Processing circuitry 80 may provide the data to be uplinked to external device 24 and the control signals for the telemetry circuit within telemetry circuitry 88, e.g., via an address/data bus. In some examples, telemetry circuitry 88 may provide received data to processing circuitry 80 via a multiplexer.

[0065] The various components of IMD 16 are coupled to power source 90, which may include a rechargeable or non-rechargeable battery. A non-rechargeable battery may be selected to last for several years, while a rechargeable battery may be inductively charged from an external device, e.g., on a daily or weekly basis.

[0066] As discussed above, oversensing can occur with implantable cardiac devices like ICDs which may lead to possible over-detection of arrhythmia episodes. It may be desirable to discriminate between a true arrhythmia episode and a false, oversensed arrhythmia episode, to avoid delivery of inappropriate therapy.

[0067] In some examples, processing circuitry 80 may employ frequency-based discrimination of oversensing. Oversensing may cause a device or system to detect a false arrhythmia episode. For example, a detected arrhythmia episode may be a true arrhythmia episode or a false arrhythmia episode due to oversensing. For example, processing circuitry 80 may detect a potential arrhythmia, such as a fast cardiac episode. Processing circuitry 80 may classify the episode as a true tachyarrhythmia episode or an over-sensed episode (e.g., a false arrhythmia).

[0068] For example, processing circuitry 80 may obtain an original sensed signal, such as an EGM of heart 12 of patient 14 via any electrodes of leads 18, 20, and/or 22. Processing circuitry 80 may store the EGM in EGM 72 of memory 70. Processing circuitry 80 may apply high pass filter 81 to the obtained sensed signal to generate a high pass filtered signal, such as a high pass filtered EGM. Processing circuitry 80 may store the high pass filtered EGM in HPF EGM 74 of memory 70. In some examples, high pass filter 81 may have a cut off frequency in the range of 20Hz - 40Hz, inclusive.

[0069] Processing circuitry 80 may compare EGM 72 to HPF EGM 74 to classify, whether the suspected arrhythmia episode is a true arrhythmia episode or a false arrhythmia episode due to oversensing. For example, processing circuitry 80 may determine a peak-to- peak amplitude of the original sensed signal (e.g., EGM 72) within a predetermined time window. Processing circuitry 80 may also determine a peak-to-peak amplitude of the high pass filtered signal (e.g., 74) within the predetermined time window. An example of such signals is shown in FIGS. 6A and 6B described later in this disclosure. In some examples, the predetermined time- window may be of a length in the range of 150ms - 250ms.

[0070] In some examples, processing circuitry 80 may determine a ratio of the peak-to- peak amplitude of the original signal (e.g., EGM 72) and the peak-to-peak amplitude of the high pass filtered signal (e.g., HPF EGM 74). Processing circuitry 80 may determine such ratios for all sensed events associated with a particular episode. For example, if processing circuitry 80 determines a suspected arrhythmia episode based on M of N sensed events being fast beats, then processing circuitry 80 may determine the ratios for each event classified as a fast beat of the suspected episode. For example, processing circuitry 80 may determine the ratio as a peak-to-peak amplitude EGM 72 divided by the peak-to-peak amplitude of HPF EGM 74 for a particular event (e.g., a particular window). Alternatively, processing circuitry 80 may determine the ratio as a peak-to-peak amplitude of HPF EGM 74 divided by the peak-to-peak amplitude of EGM 72 for a particular event (e.g., a particular window).

[0071] Processing circuitry 80 may determine whether the ratios for the suspected episode follow a pattern or, alternatively, show a uniform attenuation. For example, if the ratios are relatively consistent, processing circuitry 80 may classify the suspected episode as a true tachyarrhythmia and control therapy delivery circuitry 86 to deliver appropriate therapy. If the ratios show a pattern where the attenuation is distinctly greater for some events of the suspected episode and lesser for others, processing circuitry 80 may classify the episode as being a result of oversensing, and therefore, a false arrhythmia episode. In such a case, processing circuitry 80 may control therapy delivery circuitry 86 to withhold therapy or refrain from delivering therapy. For example, high pass filter 81 may generally reduce over-sensed P-wave or T-wave amplitude and cause a far greater attenuation than for a true-sensed QRS. Whereas for an episode with only true sensed QRSs, the attenuation would be more uniform across the different sensed events in the episode.

[0072] For example, processing circuitry 80 may determine whether the ratio is higher than or lower than a predetermined threshold. If the ratio is higher than the threshold, the ratio may be referred to as High. If the ratio is lower than the threshold, the ratio may be referred to as Low. In some examples, if the patterns of attenuation are High-Low-High- Low or Low-High-Low-High consistently, then processing circuitry 80 may classify such episodes as being the result of P-wave oversensing or T-wave oversensing. The patterns may be utilized because certain episodes of true ventricular fibrillation may be attenuated as well, but the attenuation generally is more uniform and does not have such distinctive patterns.

[0073] FIG. 4 is functional block diagram of an example external device 24. As shown in FIG. 4, external device 24 includes processing circuitry 100, a memory 102, a user interface 104, telemetry circuitry 106, and a power source 108. External device 24 may be a dedicated hardware device with dedicated software for interacting with IMD 16. Alternatively, external device 24 may be an off-the-shelf computing device running an application that enables external device 24 to interact with IMD 16.

[0074] A user may use external device 24 to select programmable parameters that control the monitoring and delivery of therapy by IMD 16, and to retrieve information collected by IMD regarding the condition of patient 14 or the performance of IMD 16. The user may interact with external device 24 via user interface 104, which may include display to present graphical user interface to a user, and a keypad or another mechanism for receiving input from a user.

[0075] Processing circuitry 100 can take the form one or more microprocessors, DSPs, ASICs, FPGAs, programmable logic circuitry, or the like, and the functions attributed to processing circuitry 100 herein may be embodied as hardware, firmware, software or any combination thereof. Memory 102 may store instructions that cause processing circuitry 100 to provide the functionality ascribed to external device 24 herein, and information used by processing circuitry 100 to provide the functionality ascribed to external device 24 herein. Memory 102 may include one or more of any fixed or removable magnetic, optical, or electrical media, such as RAM, ROM, CD-ROM, hard or floppy magnetic disks, EEPROM, or the like. Memory 102 may also include one or more removable memory portions that may be used to provide memory updates or increases in memory capacities. A removable memory may also allow patient data to be easily transferred to another computing device, or to be removed before external device 24 is used to program therapy for another patient. Memory 102 may also store information that controls therapy delivery by IMD 16, such as stimulation parameter values.

[0076] External device 24 may communicate wirelessly with IMD 16, such as using RF communication or proximal inductive interaction. This wireless communication is possible through the use of telemetry circuitry 106, which may be coupled to an internal antenna or an external antenna. An external antenna that is coupled to external device 24 may correspond to the programming head that may be placed over heart 12, as described above with reference to FIG. 1.

[0077] Telemetry circuitry 106 may be similar to telemetry circuitry 88 of IMD 16 (FIG. 3). Telemetry circuitry 106 may also be configured to communicate with another computing device via wireless communication techniques, or direct communication through a wired connection. Examples of local wireless communication techniques that may be employed to facilitate communication between external device 24 and another computing device include RF communication according to the 802.11 or Bluetooth specification sets, infrared communication, e.g., according to the IrDA standard, or other standard or proprietary telemetry protocols. In this manner, other external devices may be capable of communicating with external device 24 without needing to establish a secure wireless connection.

[0078] Power source 108 is configured to deliver operating power to the components of external device 24. Power source 108 may include a battery and a power generation circuit to produce the operating power. In some embodiments, the battery may be rechargeable to allow extended operation. Recharging may be accomplished by electrically coupling power source 108 to a cradle or plug that is connected to an alternating current (AC) outlet. In addition or alternatively, recharging may be accomplished through proximal inductive interaction between an external charger and an inductive charging coil within external device 24. In other embodiments, traditional batteries (e.g., nickel cadmium or lithium ion batteries) may be used. In addition, external device 24 may be directly coupled to an alternating current outlet to power external device 24. Power source 108 may include circuitry to monitor power remaining within a battery. In this manner, user interface 104 may provide a current battery level indicator or low battery level indicator when the battery needs to be replaced or recharged. In some cases, power source 108 may be capable of estimating the remaining time of operation using the current battery.

[0079] In some examples, processing circuitry 100 and memory 102 of external device 24 may be configured to provide some or all of the functionality ascribed to processing circuitry 80 and memory 70 of IMD 16.

[0080] FIG. 5 is a block diagram illustrating a system 110 that includes an external device 112, such as a server, and one or more computing devices 114A-114N that are coupled to IMD 16 and external device 24 shown in FIG. 1 via a network 120, according to one example. In this example, IMD 16 uses telemetry circuitry 88 (FIG. 3) to communicate with external device 24 via a first wireless connection, and to communicate with an access point 122 via a second wireless connection. In the example of FIG. 5, access point 122, external device 24, external device 112, and computing devices 114A-114N are interconnected, and able to communicate with each other, through network 120. In some cases, one or more of access point 122, external device 24, external device 112, and computing devices 114A-114N may be coupled to network 120 through one or more wireless connections. IMD 16, external device 24, external device 112, and computing devices 114A-114N may each comprise one or more processing circuitries, such as one or more microprocessors, DSPs, ASICs, FPGAs, programmable logic circuitry, or the like, that may perform various functions and operations, such as those described herein.

[0081] Access point 122 may comprise a device that connects to network 120 via any of a variety of connections, such as telephone dial-up, digital subscriber line (DSL), or cable modem connections. In other examples, access point 122 may be coupled to network 120 through different forms of connections, including wired or wireless connections. In some examples, access point 122 may communicate with external device 24 and/or IMD 16. Access point 122 may be co-located with patient 14 (e.g., within the same room or within the same site as patient 14) or may be remotely located from patient 14. For example, access point 122 may be a home monitor that is located in the patient’s home or is portable for carrying with patient 14.

[0082] During operation, IMD 16 may collect, measure, and store various forms of diagnostic data. For example, as described previously, IMD 16 may collect EGM signals, generate a time window of an integrated bipolar EGM signal, determine values of one or more features of the integrated bipolar EGM signal during the time window, and adjust a sensitivity threshold used to detect R-waves or other near field depolarizations. In certain cases, IMD 16 may directly analyze collected diagnostic data and generate any corresponding reports or alerts. In some cases, however, IMD 16 may send diagnostic data to external device 24, access point 122, and/or external device 112, either wirelessly or via access point 122 and network 110, for remote processing and analysis.

[0083] IMD 16 may provide external device 112 with collected EGM data, system integrity indications, and any other relevant physiological or system data via access point 122 and network 120. External device 112 includes one or more processing circuitries 118. In some cases, external device 112 may request such data, and in some cases, IMD 16 may automatically or periodically provide such data to external device 112. Upon receipt of the diagnostic data via input/output device 116, external device 112 is capable of analyzing the data and generating reports or alerts upon determination that there may be a possible condition with one or more of leads 18, 20, and 22, or with patient 14.

[0084] In one example, external device 112 may comprise a secure storage site for information that has been collected from IMD 16 and/or external device 24. In this example, network 120 may comprise an Internet network; and trained professionals, such as clinicians, may use computing devices 114A-114N to securely access stored data on external device 112. For example, the trained professionals may need to enter usernames and passwords to access the stored information on external device 112. In one embodiment, external device 112 may be a CareLink™ server provided by Medtronic, Inc., of Minneapolis, Minnesota.

[0085] In some examples, processing circuitry and memory of one or more of access point 122, server 112, or computing devices 114, e.g., processing circuitry 118 and memory of server 112, may be configured to provide some or all of the functionality ascribed to processing circuitry 80 and memory 70 of IMD 16.

[0086] FIGS. 6A-6B are conceptual diagrams illustrating example EGM signals and high pass filtered EGM signals according to one or more aspects of this disclosure. The example of FIG. 6A represents a false arrhythmia episode caused by oversensing and the example of FIG. 6B represents a true arrhythmia episode. FIG. 6A shows EGM 200 and high pass filtered EGM 202. It should be noted that in some examples, EGM 200 may be a filtered signal, but may not have a same high pass filter applied to EGM 200 as high pass filtered EGM 202. As can be seen for each fast sensed event (FS) the difference between EGM 200 and high pass filtered EGM 202 varies between being relatively large and relatively small. In the example of FIG. 6B, the difference between EGM 210 and high pass filtered EGM 212 remains relatively small at each fast sensed event, which is indicative of a true arrhythmia episode.

[0087] FIGS. 7A-7B are conceptual diagrams illustrating graphs of example ratios of high pass filtered EGMs to EGMs in accordance with one or more aspects of this disclosure. It should be noted that the examples of FIGS. 7A-7B do not necessarily correspond to the examples of FIGS. 6A-6B. Graph 220 depicts an example of ratios indicative of a false arrhythmia episode due to oversensing. As can be seen in the example of FIG. 7A, each consecutive ratio (222A-222N) of fast sense events corresponding with a suspected episode alternates between being above threshold 224 (e.g., high) and being below threshold 224 (e.g., low). In some examples, threshold 224 may be at least 1.2. For example, threshold 224 may be 1.2, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, etc. When determining ratios as shown in FIGS. 7A-7B, IMD 16 may ignore non-fast beats and only determine such ratios for fast senses.

[0088] For example, every other ratio of ratios 222A-222N is high and the other ratios are low. In this example, all odd numbered ratios (e.g., the first ratio, the third ratio, the fifth ratio, and so on) is high and all even numbered ratios (e.g., the second ratio, the fourth ratio, the sixth ratio, and so on) are low. For example, the first ratio (ratio 222A) may be referred to as an odd numbered ratio correspond to the ratio of the maximum peak-to-peak amplitude of EGM 72 to HPF EGM 74 during a first predetermined window around a first event, such as a first fast beat of a suspected arrhythmia episode. The first event may be referred to as an odd numbered event. The second ratio (ratio 222B) may be referred to as an even numbered ratio correspond to the ratio of the maximum peak-to-peak amplitude of EGM 72 to HPF EGM 74 during a second predetermined window around a second event, such as a second fast beat of a suspected arrhythmia episode. The second event may be referred to as an even numbered event. The third ratio (ratio 222C) may similarly be an odd numbered ratio and correspond to the ratio of the maximum peak-to-peak amplitude of EGM 72 to HPF EGM 74 during a third predetermined window around a third event, which may be an odd numbered event and so on. This pattern of high, low, high, low, high, low ... (or low, high, low, high, low, high ...) may be indicative of the suspected arrhythmia being an oversensed event and therefore a false arrhythmia.

[0089] While in the example of FIG. 7 A, each odd numbered ratio is high and each even numbered ratio is low, it should be understood that, in some instances, there may be one or more ratios that may not fit the pattern. In some examples, IMD 16 may require all ratios to fit this pattern in order to determine the suspected arrhythmia episode to be a false arrhythmia episode. In some examples, IMD 16 may still determine the suspected arrhythmia episode to be a false arrhythmia episode if there are a limited number of such ratios that do not fit this pattern. For example, IMD 16 may apply an M of N criterion such that IMD 16 may determine the suspected arrhythmia episode to be a false arrhythmia episode if there are at least M of N ratios that fit this alternating highs and lows pattern. Some examples of M of N for ratios fitting the pattern of alternating highs and lows include 36 of 40, 32 of 40, 26 of 32, 28 of 32, etc.

[0090] Graph 230 depicts an example of ratios indicative of a true arrhythmia episode. As can be seen in the example of FIG. 7B, each consecutive ratio (232A-232N) of fast sense events corresponding with a suspected episode does not alternate between high and low, but instead remains below (alternatively above) threshold 224. While in the example of FIG. 7B, all of the odd numbered ratios and even numbered ratios are low, it should be understood that, in some instances, there may be one or more ratios that may not fit this pattern. In some examples, IMD 16 may require all ratios to fit this pattern in order to determine the suspected arrhythmia episode to be a true arrhythmia episode. In some examples, IMD 16 may still determine the suspected arrhythmia episode to be a true arrhythmia episode if there are a limited number of such ratios that do not fit this pattern. For example, IMD 16 may determine the suspected arrhythmia episode to be a true arrhythmia episode if IMD 16 does not determine the suspected arrhythmia episode to be a false arrhythmia episode. For example, the ratios may not follow the alternating high and low ratios pattern or not satisfying the M of N criteria.

[0091] While the example of FIGS. 7A-7B is directed to ratios of maximum peak-to- peak amplitude of EGM 72 to HPF EGM 74 during corresponding predetermined windows around each sensed event (e.g., each sensed fast beat), other measures may be used. For example, IMD 16 may compare a difference between the maximum peak-to-peak amplitude of EGM 72 to HPF EGM 74 to a threshold rather than a ratio of between the maximum peak-to-peak amplitude of EGM 72 to HPF EGM 74. In some examples, in lieu of, or in addition to, maximum peak-to-peak amplitude, IMD 16 may use another characteristic(s) of EGM 72 and HPF EGM 74. For example, IMD 16 determine an area under the curve for each of EGM 72 to HPF EGM 74 during each of the predetermined windows. IMD 16 may use the areas under the curve to determine a ratio or difference, and compare these determined ratios or differences to determine whether the suspected arrhythmia event is a true arrhythmia event or a false arrhythmia event based on potential patterns in the resulting comparisons. It should be understood that IMD 16 may use other ways of comparing EGM 72 and HPF EGM 74 and/or other characteristics of EGM 72 and HPF EGM 74 to compare EGM 72 and HPF EGM 74.

[0092] FIG. 8 is a flow diagram illustrating an example technique for frequency-based determination of oversensing according to one or more aspects of this disclosure. IMD 16 may obtain the cardiac EGM of the patient (300). For example, IMD 16 may capture a cardiac EGM of patient 14 via electrodes of any of leads 18, 20, and/or 22.

[0093] IMD 16 may determine a suspected arrhythmia episode based on the cardiac EGM (302). For example, IMD 16 may apply a M of N arrhythmia detection algorithm to see if M of N detected beats are fast beats.

[0094] IMD 16 may apply a high pass filter to the cardiac EGM to generate a high pass filtered EGM (304). For example, IMD 16 may apply high pass filter 81 to EGM 72 to generate HPF EGM 74.

[0095] IMD 16 may classify, based on the cardiac EGM and the high pass filtered EGM, the suspected arrhythmia episode as a true arrhythmia episode or a false arrhythmia episode due to oversensing (306). For example, IMD 16 may compare one or more features of EGM 72 to one or more features of HPF EGM 74 to determine whether the suspected arrhythmia episode is a true arrhythmia episode or a false arrhythmia episode. [0096] In some examples, high pass filter 81 has a cut off frequency of between 20Hz and 40Hz inclusive. In some examples, to determine the suspected arrhythmia episode, IMD 16 determines a plurality of events associated with the episode. For example, IMD 16 may determine the fast sense events associated with the suspected arrhythmia episode. In some examples, to classify the suspected arrhythmia episode for each of the plurality of events, IMD 16 may determine a corresponding time window associated with an event. IMD 16 may determine a first peak-to-peak amplitude of the cardiac EGM within the corresponding time window. IMD 16 may determine a second peak-to-peak amplitude of the high pass filtered EGM within the corresponding time window. IMD 16 may determine a ratio of the first peak-to-peak amplitude of the cardiac EGM to the respective second peak-to-peak amplitude of the high pass filtered EGM. In some examples, the corresponding time window has a length of between 150ms to 250ms inclusive.

[0097] In some examples, to classify the suspected arrhythmia episode, IMD 16 may determine whether each ratio satisfies a predetermined attenuation threshold. IMD 16 may classify the suspected arrhythmia episode based on the determination of whether each ratio satisfies the predetermined attenuation threshold. In some examples, when each ratio satisfies the predetermined attenuation threshold, the classification includes a true arrhythmia, and IMD 16, based on the classification comprising a true arrhythmia, controls therapy delivery circuitry to deliver therapy.

[0098] In some examples, each event is an odd numbered event or an even numbered event. In some examples, each ratio corresponding to an odd numbered event is an odd numbered ratio and each ratio corresponding to an even numbered event is an even numbered ratio. In some examples, even numbered ratios satisfy the threshold and odd numbered ratios do not satisfy the threshold. In some examples, the odd numbered ratios satisfy the threshold and the even numbered ratios do not satisfy the threshold. In such examples, the classification includes a false arrhythmia due to oversensing, and IMD 16, based on the classification comprising a false arrhythmia, controls therapy delivery circuitry to refrain from delivering therapy.

[0099] It should be understood that one or more of the techniques set forth in this disclosure may be implemented in systems or devices that do not include an IMD and/or that do not include therapy delivery circuitry. [0100] In one or more examples, the functions described in this disclosure may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored on, as one or more instructions or code, a computer- readable medium and executed by a hardware-based processing unit. Computer-readable media may include computer-readable storage media forming a tangible, non-transitory medium. Instructions may be executed by one or more processing circuitries, such as one or more DSPs, ASICs, FPGAs, general purpose microprocessors, or other equivalent integrated or discrete logic circuitry. Accordingly, the term “processing circuitry,” as used herein may refer to one or more of any of the foregoing structure or any other structure suitable for implementation of the techniques described herein.

[0101] The techniques described in this disclosure may be implemented, at least in part, in hardware, software, firmware, or any combination thereof. For example, various aspects of the techniques may be implemented within one or more microprocessors, DSPs, ASICs, FPGAs, or any other equivalent integrated or discrete logic QRS circuitry, as well as any combinations of such components, embodied in external devices, such as physician or patient programmers, stimulators, or other devices. The terms “processor” and “processing circuitry” may generally refer to any of the foregoing logic circuitry, alone or in combination with other logic circuitry, or any other equivalent circuitry, and alone or in combination with other digital or analog circuitry.

[0102] For aspects implemented in software, at least some of the functionality ascribed to the systems and devices described in this disclosure may be embodied as instructions on a computer-readable storage medium such as RAM, DRAM, SRAM, magnetic discs, optical discs, flash memories, or forms of EPROM or EEPROM. The instructions may be executed to support one or more aspects of the functionality described in this disclosure.

[0103] In addition, in some aspects, the functionality described herein may be provided within dedicated hardware and/or software modules. Depiction of different features as modules or units is intended to highlight different functional aspects and does not necessarily imply that such modules or units must be realized by separate hardware or software components. Rather, functionality associated with one or more modules or units may be performed by separate hardware or software components, or integrated within common or separate hardware or software components. Also, the techniques could be fully implemented in one or more circuits or logic elements. The techniques of this disclosure may be implemented in a wide variety of devices or apparatuses, including an IMD, an external programmer, a combination of an IMD and external programmer, an integrated circuit (IC) or a set of ICs, and/or discrete electrical circuitry, residing in an IMD and/or external programmer.

[0104] Various aspects of the techniques may enable the following examples.

[0105] Example 1. A system comprising: sensing circuitry configured to sense a cardiac electrogram (EGM) of a patient; and processing circuitry configured to: obtain the cardiac EGM of the patient; determine a suspected arrhythmia episode based on the cardiac EGM; apply a high pass filter to the cardiac EGM to generate a high pass filtered EGM; and classify, based on the cardiac EGM and the high pass filtered EGM, the suspected arrhythmia episode as a true arrhythmia episode or a false arrhythmia episode due to oversensing.

[0106] Example 2. The system of Example 1, wherein the high pass filter has a cut off frequency of between 20 Hertz (Hz) and 40Hz inclusive.

[0107] Example 3. The system of Example 1 or Example 2, wherein to determine the suspected arrhythmia episode, the processing circuitry is configured to determine a plurality of events associated with the episode.

[0108] Example 4. The system of Example 3, wherein to classify the suspected arrhythmia episode, the processing circuitry is further configured to, for each of the plurality of events: determine a corresponding time window associated with an event; determine a first peak-to-peak amplitude of the cardiac EGM within the corresponding time window; determine a second peak-to-peak amplitude of the high pass filtered EGM within the corresponding time window; and determine a ratio of the first peak-to-peak amplitude of the cardiac EGM to the respective second peak-to-peak amplitude of the high pass filtered EGM.

[0109] Example 5. The system of Example 4, wherein the corresponding time window has a length of between 150 milliseconds (ms) to 250ms inclusive.

[0110] Example 6. The system of Example 4 or Example 5, wherein to classify the suspected arrhythmia episode, the processing circuitry is further configured to: determine whether each ratio satisfies a predetermined attenuation threshold; and classify the suspected arrhythmia episode based on the determination of whether each ratio satisfies the predetermined attenuation threshold. [0111] Example 7. The system of Example 6, wherein when each ratio satisfies the predetermined attenuation threshold, the classification comprises a true arrhythmia.

[0112] Example 8. The system of Example 7, wherein the processing circuitry is further configured to, based on the classification comprising a true arrhythmia, control therapy delivery circuitry to deliver therapy.

[0113] Example 9. The system of Example 6, wherein each event is an odd numbered event or an even numbered event, wherein each ratio corresponding to an odd numbered event is an odd numbered ratio, wherein each ratio corresponding to an even numbered event is an even numbered ratio, wherein a) even numbered ratios satisfy the threshold and odd numbered ratios do not satisfy the threshold, or b) the odd numbered ratios satisfy the threshold and the even numbered ratios do not satisfy the threshold, wherein the classification comprises a false arrhythmia due to oversensing, and wherein the processing circuitry is further configured to, based on the classification comprising a false arrhythmia, control therapy delivery circuitry to refrain from delivering therapy.

[0114] Example 10. The system of any of Examples 1-9, wherein the system comprises an implantable medical device comprising the sensing circuitry.

[0115] Example 11. The system of Example 10, wherein the implantable medical device comprises an implantable cardioverter defibrillator.

[0116] Example 12. The system of Example 11, further comprising an integrated bipolar lead, wherein the sensing circuitry is configured to sense the EGM via the integrated bipolar lead.

[0117] Example 13. A method comprising: sensing, by sensing circuitry, a cardiac electrogram (EGM) of a patient; and obtaining, by processing circuitry, the cardiac EGM of the patient; determining, by the processing circuitry, a suspected arrhythmia episode based on the cardiac EGM; applying, by the processing circuitry, a high pass filter to the cardiac EGM to generate a high pass filtered EGM; and classifying, by the processing circuitry and based on the cardiac EGM and the high pass filtered EGM, the suspected arrhythmia episode as a true arrhythmia episode or a false arrhythmia episode due to oversensing.

[0118] Example 14. The method of claim 13, wherein the high pass filter has a cut off frequency of between 20 Herz (Hz) and 40Hz inclusive. [0119] Example 15. The method of Example 13 or Example 14, wherein determining the suspected arrhythmia episode comprises determining a plurality of events associated with the episode.

[0120] Example 16. The method of Example 15, wherein classifying the suspected arrhythmia episode comprises, for each of the plurality of events: determining a corresponding time window associated with an event; determining a first peak-to-peak amplitude of the cardiac EGM within the corresponding time window; determining a second peak-to-peak amplitude of the high pass filtered EGM within the corresponding time window; and determining a ratio of the first peak-to-peak amplitude of the cardiac EGM to the respective second peak-to-peak amplitude of the high pass filtered EGM.

[0121] Example 17. The method of Example 16, wherein classifying the suspected arrhythmia episode comprises: determining whether each ratio satisfies a predetermined attenuation threshold; and classifying the suspected arrhythmia episode based on the determination of whether each ratio satisfies the predetermined attenuation threshold.

[0122] Example 18. The method of Example 17, wherein when each ratio satisfies the predetermined attenuation threshold, the classification comprises a true arrhythmia.

[0123] Example 19. The method of Example 17, wherein each event is an odd numbered event or an even numbered event, wherein each ratio corresponding to an odd numbered event is an odd numbered ratio, wherein each ratio corresponding to an even numbered event is an even numbered ratio, wherein a) even numbered ratios satisfy the threshold and odd numbered ratios do not satisfy the threshold, or b) the odd numbered ratios satisfy the threshold and the even numbered ratios do not satisfy the threshold, wherein the classification comprises a false arrhythmia due to oversensing, and wherein the method further comprises controlling, by the processing circuitry and based on the classification comprising a false arrhythmia, therapy delivery circuitry to refrain from delivering therapy.

[0124] Example 20. An implantable medical device comprising: sensing circuitry configured to sense a cardiac electrogram (EGM) of a patient; and processing circuitry configured to: obtain the cardiac EGM of the patient; determine a suspected arrhythmia episode based on the cardiac EGM; apply a high pass filter to the cardiac EGM to generate a high pass filtered EGM; and classify, based on the cardiac EGM and the high pass filtered EGM, the suspected arrhythmia episode as a true arrhythmia episode or a false arrhythmia episode due to oversensing.

[0125] Various examples have been described. These and other examples are within the scope of the following claims.

Claims

CLAIMS:

1. A system comprising: sensing circuitry configured to sense a cardiac electrogram (EGM) of a patient; and processing circuitry configured to: obtain the cardiac EGM of the patient; determine a suspected arrhythmia episode based on the cardiac EGM; apply a high pass filter to the cardiac EGM to generate a high pass filtered EGM; and classify, based on the cardiac EGM and the high pass filtered EGM, the suspected arrhythmia episode as a true arrhythmia episode or a false arrhythmia episode due to oversensing.

2. The system of claim 1, wherein the high pass filter has a cut off frequency of between 20 Hertz (Hz) and 40Hz inclusive.

3. The system of claim 1 or claim 2, wherein to determine the suspected arrhythmia episode, the processing circuitry is configured to determine a plurality of events associated with the episode.

4. The system of claim 3, wherein to classify the suspected arrhythmia episode, the processing circuitry is further configured to, for each of the plurality of events: determine a corresponding time window associated with an event; determine a first peak-to-peak amplitude of the cardiac EGM within the corresponding time window; determine a second peak-to-peak amplitude of the high pass filtered EGM within the corresponding time window; and determine a ratio of the first peak-to-peak amplitude of the cardiac EGM to the respective second peak-to-peak amplitude of the high pass filtered EGM.

5. The system of claim 4, wherein the corresponding time window has a length of between 150 milliseconds (ms) to 250ms inclusive.

6. The system of claim 4 or claim 5, wherein to classify the suspected arrhythmia episode, the processing circuitry is further configured to: determine whether each ratio satisfies a predetermined attenuation threshold; and classify the suspected arrhythmia episode based on the determination of whether each ratio satisfies the predetermined attenuation threshold.

7. The system of claim 6, wherein when each ratio satisfies the predetermined attenuation threshold, the classification comprises a true arrhythmia.

8. The system of claim 7, wherein the processing circuitry is further configured to, based on the classification comprising a true arrhythmia, control therapy delivery circuitry to deliver therapy.

9. The system of claim 6, wherein each event is an odd numbered event or an even numbered event, wherein each ratio corresponding to an odd numbered event is an odd numbered ratio, wherein each ratio corresponding to an even numbered event is an even numbered ratio, wherein a) even numbered ratios satisfy the threshold and odd numbered ratios do not satisfy the threshold, or b) the odd numbered ratios satisfy the threshold and the even numbered ratios do not satisfy the threshold, wherein the classification comprises a false arrhythmia due to oversensing, and wherein the processing circuitry is further configured to, based on the classification comprising a false arrhythmia, control therapy delivery circuitry to refrain from delivering therapy.

10. The system of any of claims 1-9, wherein the system comprises an implantable medical device comprising the sensing circuitry.

11. The system of claim 10, wherein the implantable medical device comprises an implantable cardioverter defibrillator.

12. The system of claim 11, further comprising an integrated bipolar lead, wherein the sensing circuitry is configured to sense the EGM via the integrated bipolar lead.

13. A method comprising: sensing, by sensing circuitry, a cardiac electrogram (EGM) of a patient; and obtaining, by processing circuitry, the cardiac EGM of the patient; determining, by the processing circuitry, a suspected arrhythmia episode based on the cardiac EGM; applying, by the processing circuitry, a high pass filter to the cardiac EGM to generate a high pass filtered EGM; and classifying, by the processing circuitry and based on the cardiac EGM and the high pass filtered EGM, the suspected arrhythmia episode as a true arrhythmia episode or a false arrhythmia episode due to oversensing.

14. The method of claim 13, wherein the high pass filter has a cut off frequency of between 20 Herz (Hz) and 40Hz inclusive.

15. An implantable medical device comprising: sensing circuitry configured to sense a cardiac electrogram (EGM) of a patient; and processing circuitry configured to: obtain the cardiac EGM of the patient; determine a suspected arrhythmia episode based on the cardiac EGM; apply a high pass filter to the cardiac EGM to generate a high pass filtered EGM; and classify, based on the cardiac EGM and the high pass filtered EGM, the suspected arrhythmia episode as a true arrhythmia episode or a false arrhythmia episode due to oversensing.