Respirophasic pacing based on tracking respiration with electrograms

Abstract

A therapy delivery device configured to deliver cardiac pacing pulses to a heart of a patient via a plurality of electrodes can sense an electrogram (EGM) signal of a patient; identify a prior inspiration phase based on the EGM signal; determine a heart rate of the patient based on the EGM signal; predict a beginning of a subsequent inspiration phase based on the prior inspiration phase; and adjust a rate of the cardiac pacing during the subsequent inspiration phase based on the heart rate and the prior inspiration phase.

Description

RESPIROPHASIC PACING BASED ON TRACKING RESPIRATION WITH ELECTROGRAMSCROSS-RELATED APPLICATIONS

[0001] This application claims the benefit of U.S. Provisional Patent Application Serial No. 63 / 568,269, filed March 21, 2024, the entire content of which is incorporated herein by reference.FIELD

[0002] This disclosure generally relates to medical devices and, more particularly, to medical devices that deliver cardiac therapy.BACKGROUND

[0003] In healthy humans, heart rate naturally increases during inspiration and decreases during expiration. This phenomenon, known as respiratory sinus arrhythmia (RSA), supports ventilation / perfusion matching as blood enters the lungs, i.e., increases pulmonary blood flow when the lungs are inflated.SUMMARY

[0004] In general, this disclosure describes techniques for delivering cardiac pacing to restore RSA, e.g., by increasing the cardiac pacing pulse rate during inspiration, and, in some examples, decreasing the pulse rate during expiration. Many current pacemakers pace monotonically in view of pulmonary inspiration / expiration, and the monotonic pacing rate increases with increased pulmonary activity (e.g., increases with respiration rate but does not vary within the respiratory cycle).

[0005] Cardiac pacing to restore RSA, i.e., respirophasic pacing, can provide therapeutic benefit, e.g., by increasing cardiac output and helping to reverse remodel the heart of heart failure (HF) patients. However, current processes of restoring RSA are based on several averaged prior-detected inspiration and expiration phases based on identified prior respiration cycles, which may mimic RSA when the patient is breathing at a stable rate, e.g., while the patient is sleeping, but may not accurately mimic RSA when the patient is breathing at a more variable rate, e.g., when the patient is active.

[0006] The techniques of this disclosure may be implemented by a cardiac therapy device, e.g., a pacemaker, that can continuously sense signals indicative of inspiration phases and expiration phases and detect inspiration phases and expiration phases independently. In other words, the pacemaker may identify inspiration and expiration phases without first identifying a respiration cycle. The pacemaker may be configured to predict subsequent, e.g., immediately following, inspiration and / or expiration phases of the patient based on the detected inspiration and / or expiration and control therapy delivery circuitry to adjust cardiac pacing pulses. By continuously monitoring for inspiration phases and / or expiration phases and predicting subsequent inspiration and / or expiration phases based on the previous inspiration phase and / or expiration phase, the techniques of this disclosure may improve RSA pacing. In some examples, the pacemaker may continuously update predicted subsequent inspiration and expiration based on the accuracy of previous predictions.

[0007] In some examples, RSA pacing may be unnecessary, ineffective, or counterproductive under certain conditions, e.g., when the patient is already achieving RSA or when the patient’s heart rate exceeds a threshold. The techniques of this disclosure may avoid delivering RSA pacing under such conditions by determining whether one or more criteria for adjusting cardiac pacing to mimic are satisfied based on one or more sensed patient parameters.

[0008] In some examples, the techniques of this disclosure may additionally include further adjusting cardiac pacing based on a patient state, e.g., the pacemaker may increase, or overdrive, cardiac pacing pulses to a lesser extent for patients in one category based on patient state than patients in a different category.

[0009] In one example, a device comprises: therapy delivery circuitry configured to deliver cardiac pacing pulses to a heart of a patient via a plurality of electrodes; sensing circuitry configured to sense an electrogram (EGM) signal of a patient; and processing circuitry configured to: identify a prior inspiration phase based on the EGM signal; determine a heart rate of the patient based on the EGM signal; predict a beginning of a subsequent inspiration phase based on the prior inspiration phase; and control the therapy delivery circuitry to adjust a rate of the cardiac pacing during the subsequent inspiration phase based on the heart rate and the prior inspiration phase.

[0010] In another example, a method comprises: sensing, by sensing circuitry of a medical device of a medical device system, an electrogram (EGM) signal of a patient; and identifying, by processing circuitry of the system, a prior inspiration phase based on the EGM signal; determining, by the processing circuitry, a heart rate of the patient based on the EGMsignal; predicting, by the processing circuitry, a beginning of a subsequent inspiration phase based on the prior inspiration phase; and controlling, by the processing circuitry, therapy delivery circuitry of the medical device to adjust a rate of cardiac pacing pulses to a heart of the patient during the subsequent inspiration phase based on the heart rate and the prior inspiration phase.

[0011] In another example, a non-transitory computer-readable storage medium stores instructions that, when executed by processing circuitry, cause the processing circuitry to: control sensing circuitry to sense an electrogram (EGM) signal of a patient; identify a prior inspiration phase based on the EGM signal; determine a heart rate of the patient based on the EGM signal; predict a beginning of a subsequent inspiration phase based on the prior inspiration phase; and control therapy delivery circuitry to adjust a rate of cardiac pacing during the subsequent inspiration phase based on the heart rate and the prior inspiration phase.

[0012] In another example, a device comprises: therapy delivery circuitry configured to deliver cardiac pacing pulses to a heart of a patient via a plurality of electrodes; sensing circuitry configured to sense an electrogram (EGM) signal of a patient; and processing circuitry configured to: identify a prior expiration phase based on the EGM signal; determine a heart rate of the patient based on the EGM signal; predict a beginning of a subsequent expiration phase based on the prior expiration phase; and control the therapy delivery circuitry to adjust a rate of the cardiac pacing during the subsequent expiration phase based on the heart rate and the prior expiration phase.

[0013] In another example, a method comprises: sensing, by sensing circuitry of a medical device of a medical device system, an electrogram (EGM) signal of a patient; and identifying, by processing circuitry of the system, a prior expiration phase based on the EGM signal; determining, by the processing circuitry, a heart rate of the patient based on the EGM signal; predicting, by the processing circuitry, a beginning of a subsequent expiration phase based on the prior expiration phase; and controlling, by the processing circuitry, therapy delivery circuitry of the medical device to adjust a rate of cardiac pacing pulses to a heart of the patient during the subsequent expiration phase based on the heart rate and the prior expiration phase.

[0014] In another example, a non-transitory computer-readable storage medium stores instructions that, when executed by processing circuitry, cause the processing circuitry to: control sensing circuitry to sense an electrogram (EGM) signal of a patient; identify a prior expiration phase based on the EGM signal; determine a heart rate of the patient based on theEGM signal; predict a beginning of a subsequent expiration phase based on the prior expiration phase; and control therapy delivery circuitry to adjust a rate of cardiac pacing during the subsequent expiration phase based on the heart rate and the prior expiration phase.

[0015] 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 apparatus and methods described in detail within the accompanying drawings and description below. Further details of one or more examples are set forth in the accompanying drawings and the description below.BRIEF DESCRIPTION OF DRAWINGS

[0016] FIG. l is a conceptual diagram illustrating an example system configured to deliver cardiac pacing to mimic respiratory sinus arrhythmia (RSA), the system including an implantable medical device (IMD) coupled to implantable medical leads, in accordance with one or more techniques of this disclosure.

[0017] FIG. 2 is a conceptual drawing illustrating the example IMD and leads of FIG. 1 in conjunction with a heart, in accordance with one or more techniques of this disclosure.

[0018] FIG. 3 is a functional block diagram illustrating an example configuration of the IMD of FIG. 1, in accordance with one or more techniques of this disclosure.

[0019] FIG. 4 is a flow diagram illustrating an example operation of a device to adjust a rate of cardiac pacing to mimic RSA, in accordance with one or more techniques of this disclosure.

[0020] FIG. 5 is a flow diagram illustrating an example operation of a device to determine whether to adjust a rate of cardiac pacing to mimic RSA, in accordance with one or more techniques of this disclosure.

[0021] FIG. 6 is a flow diagram illustrating an example operation for determining whether to adjust cardiac pacing to mimic RSA based on patient heart rate information, in accordance with one or more techniques of this disclosure.

[0022] FIG. 7 is a graph illustrating an example EGM signal with inspiration phase and expiration phase information, which may be identified in accordance with one or more techniques of this disclosure.

[0023] FIG. 8 is a flow diagram illustrating an example operation for adjusting cardiac pacing based on a patient state, in accordance with one or more techniques of this disclosure.

[0024] Like reference characters refer to like elements throughout the figures and description.DETAILED DESCRIPTION

[0025] A variety of types of implantable and external devices are configured to monitor health based on sensed physiological signals. External devices that may be used to non- invasively sense and monitor physiological signals include wearable devices with electrodes configured to contact the skin of the patient, such as patches, watches, rings, necklaces, hearing aids, a wearable cardiac monitor or automated external defibrillator (AED), clothing, car seats, or bed linens. Such external devices may facilitate relatively longer-term monitoring of patient health during normal daily activities.

[0026] Implantable medical devices (IMDs) also sense and monitor physiological signals and detect health events such as episodes of arrhythmia, cardiac arrest, myocardial infarction, stroke, and seizure. Example IMDs include pacemakers and implantable cardioverterdefibrillators, which may be coupled to intravascular or extravascular leads, as well as pacemakers with housings configured for implantation within the heart, which may be leadless, such as the Mi era™ leadless pacing device of Medtronic, Inc. Pacemakers provide cardiac pacing pulses to patients based on monitored physiological signals.

[0027] Many current pacemakers pace monotonically in view of pulmonary inspiration / expiration, and the monotonic pacing rate increases with increased activity level (e.g., many current pacemakers provide pacing that does not vary within the respiratory cycle). Cardiac pacing to mimic RSA, i.e., respirophasic pacing, can provide therapeutic benefit, e.g., by increasing cardiac output and helping to reverse remodel the heart of heart failure (HF) patients and / or improve quality of life / functional capacity. However, existing processes for restoring RSA are based on several averaged prior-detected inspiration and expiration phases based on identified respiration cycles, which may mimic RSA when the patient is breathing at a stable rate, e.g., while the patient is sleeping, but may not accurately mimic RSA when the patient is breathing at a more variable rate, e.g., when the patient is active.

[0028] The techniques of this disclosure may be implemented by a cardiac therapy device, e.g., a pacemaker, that can continuously sense physiological signals, e.g., electrogram (EGM) signals, indicative of inspiration phases and expiration phases and detect inspiration phases and expiration phases independently. In other words, the pacemaker may identify inspiration and expiration phases without first identifying a respiration cycle. In some examples, the pacemaker may control therapy delivery circuitry to adjust cardiac pacingpulses based on the inspiration and / or expiration phases. By continuously monitoring for inspiration phases and / or expiration phases and adjusting cardiac pacing pulses phase-to- phase based on the inspiration phases and / or expiration phases immediately following the inspiration and / or expiration phases, the techniques of this disclosure may improve RSA pacing accuracy. As such, patients may receive cardiac pacing that more closely mimics RSA, which may improve patient outcomes.

[0029] RSA pacing may be unnecessary, ineffective, or counterproductive under certain conditions, e.g., when the patient is already achieving RSA or when the patient’s heart rate exceeds a threshold. The techniques of this disclosure may avoid delivering RSA pacing under such conditions by determining whether one or more criteria for adjusting cardiac pacing to mimic are satisfied based on one or more sensed patient parameters. In this manner, the techniques described herein may advantageously improve the operation of a device that delivers cardiac pacing to mimic RSA, e.g., to deliver such pacing when likely to be effective and avoid delivery of counterproductive therapy, thereby benefitting the patient.

[0030] In some examples, the techniques of this disclosure may additionally include further adjusting cardiac pacing based on a patient state, e.g., the pacemaker may increase, or overdrive, cardiac pacing pulses to a lesser extent for patients in one category based on patient state than patients in a different category. By adjusting cardiac pacing based on the patient state, the techniques of this disclosure may improve the accuracy of respirophasic pacing, which may improve patient outcomes.

[0031] The techniques of this disclosure additionally include predicting subsequent, e.g., immediately following, inspiration and / or expiration phases of the patient based on prior detected inspiration and / or expiration and control therapy delivery circuitry to adjust cardiac pacing pulses. As such, patients may receive cardiac pacing that more closely mimics RSA, which may improve patient outcomes.

[0032] FIG. 1 is a conceptual diagram illustrating an example system 10 configured to deliver cardiac pacing to mimic respiratory sinus arrhythmia (RSA) in a patient 14 in accordance with the techniques of this disclosure. In the example of FIG. 1, system 10 includes an implantable medical device (IMD) 16, which is coupled to leads 18, 20, and 22, and an external device 24. IMD 16 may be, for example, an implantable pacemaker, cardioverter, and / or defibrillator that provides electrical signals to heart 12 via electrodes coupled to one or more of leads 18, 20, and 22. Patient 14 is ordinarily, but not necessarily a human patient.

[0033] In the example of FIG. 1, leads 18, 20, 22 extend into the heart 12 of patient 14 to sense electrical activity of heart 12, e.g., one or more cardiac electrogram (EGM) signals, and / or deliver electrical stimulation to heart 12. Leads 18, 20, and 22 may also be used to detect impedance indicative of fluid volume in patient 14 and respiration of patient 14. In addition to impedance, a respiration signal may also be present as a component of a cardiac EGM signal.

[0034] 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 26, and into right ventricle 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 left ventricle 32 of heart 12. Right atrial (RA) lead 22 extends through one or more veins and the vena cava, and into the right atrium 26 of heart 12.

[0035] The illustrated number and positions of leads 18, 20, and 22 are examples. In other examples, IMD 16 may be coupled to one, two, or more than three leads that extend to a variety of positions. In some examples, system 10 may additionally or alternatively include one or more leads or lead segments (not shown in FIG. 1) that deploy one or more electrodes within the vena cava, or other veins. Furthermore, in some examples, system 10 may additionally or alternatively include extravascular leads with electrodes implanted outside of heart 12, instead of or in addition to transvenous, intracardiac leads 18, 20 and 22. Such leads may be used for one or more of cardiac sensing, pacing, or cardioversion / defibrillation. Additionally, in some examples, system 10 may include one or more leadless cardiac pacing devices, such as the Micra™ pacemakers commercially available from Medtronic, Inc., instead of or in addition to IMD 16. One or more leadless pacemakers may be configured to deliver cardiac pacing according to an RSA mode in the manner described herein with respect to IMD 16. Furthermore, an external medical device may be configured to deliver cardiac pacing according to an RSA mode in the manner described herein with respect to IMD 16. In some examples, the techniques of this disclosure may be performed by a system that includes two or more devices in communication with one another. For example, a first device, such as an implantable monitoring device, e.g., a Reveal LINQ™ insertable cardiac monitor, commercially available from Medtronic, Inc., may monitor the inspiration and / or expiration of patient 14 and based on the monitoring, adjust pacing therapy being delivered by a second device.

[0036] 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 theleads 18, 20, 22. In some examples, IMD 16 provides pacing pulses to heart 12 based on the electrical signals sensed within heart 12. The configurations of electrodes used by IMD 16 for sensing and pacing may be unipolar or bipolar. In some examples, IMD 16 may deliver cardiac pacing to provide cardiac resynchronization therapy (CRT). In some examples, IMD 16 may additionally or alternatively be configured to provide conduction system pacing, which may provide a more physiologic activation of heart 12 than conventional pacing. In such examples, leads 18, 20, 22 may be configured / positioned such that their electrode(s) access (are capable of stimulating) the heart’s conduction system, e.g., the His bundle, left bundle branch, or right bundle branch.

[0037] IMD 16 may detect arrhythmia of heart 12, such as tachycardia or fibrillation of the atria 26 and 36 and / or ventricles 28 and 32, and may also provide defibrillation therapy and / or cardioversion therapy via electrodes located on at least one of the leads 18, 20, 22. In some examples, IMD 16 may be programmed to deliver a progression of therapies, e.g., pulses with increasing energy levels, until a fibrillation of heart 12 is stopped. IMD 16 may detect fibrillation employing one or more fibrillation detection techniques known in the art.

[0038] IMD 16 may utilize two of any electrodes carried on leads 18, 20, 22 to generate EGM signals. In some examples, IMD 16 may also use a housing electrode of IMD 16 (not shown) to generate EGM signals and monitor cardiac activity. Although these EGM signals may be used to monitor heart 12 for potential arrhythmias and other disorders for therapy, the EGM signals may also be used to monitor the condition of heart 12. For example, IMD 16 may monitor heart rate, heart rate variability, indicators of blood flow, or other indicators of the ability of heart 12 to pump blood or the progression of heart failure (HF).

[0039] In some examples, IMD 16 may also use any two electrodes of leads 18, 20, and 22 or the housing electrode to sense an impedance of patient 14. As the tissues within the thoracic cavity of patient 14 increase in fluid content, the impedance between two electrodes may also change. IMD 16 may use this impedance to create a fluid index. As the fluid index increases, more fluid may be more likely to be retained within patient 14 and heart 12 may be stressed to keep up with moving the greater amount of fluid.

[0040] IMD 16 may communicate with external device 24. In some examples, external device 24 comprises a handheld computing device, computer workstation, or networked computing device. External device 24 may be configured to retrieve data from IMD 16, e.g., for presentation to a clinician or other user, such as sensed parameter data of patient 14 and data regarding the operation of IMD 16. In some examples, external device 24 may provide the retrieved data to a cloud computing system, such as the CareLink™ system availablefrom Medtronic, Inc., which may analyze the data and provide reports of the analysis and / or the data to clinicians or other users. In some examples, a clinician or other user may also interact with external device 24 to program IMD 16, e.g., select values for operational parameters of IMD 16. Although the user is typically a clinician, the user may be patient 14 in some examples.

[0041] In some examples, IMD 16, external device 24, or a cloud computing system may determine HF metrics or other patient state information based on patient parameter data collected by IMD 16. In some examples, IMD 16, external device 24, or a cloud computing system may determine, for example, a HF risk level based on the HF risk metrics. For example, the risk level may be determined based on a predetermined number of metrics exceeding their representative thresholds or a weighted score for each of the patient metrics for exceeding one or more thresholds. Additionally, or alternatively, the risk level may be determined by a Bayesian Belief Network, or other probability technique, using the values or stratified states of each automatically detected patient metric. For example, a Bayesian Belief Network may be applied to the values of the patient metrics to determine the risk level, e.g., the probability, that patient 14 will be admitted to the hospital for HF.

[0042] IMD 16 may determine each of the HF metrics and store them within the IMD for later transmission. For example, the patient metrics may include two or more of a thoracic fluid index, an atrial fibrillation duration, a ventricular contraction rate during atrial fibrillation, a patient activity, a nighttime heart rate, a heart rate variability, a CRT percentage (e.g., the percentage of cardiac cycles for which CRT pacing was provided), or the occurrence of or number of therapeutic electrical shocks.

[0043] 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, radiofrequency (RF) telemetry or communication according to a Bluetooth® protocol, but other communication techniques such as magnetic coupling are also contemplated.

[0044] IMD 16 is an example of a device configured to deliver cardiac pacing pulses to a heart of a patient via a plurality of electrodes, sense an EGM of the patient, determine a patient heart rate, identify an inspiration phase and / or an expiration phase, predict a subsequent beginning of an inspiration and / or expiration phase, and adjust cardiac pacing pulses based on the heart rate and inspiration and / or expiration phase during the subsequent inspiration and / or expiration phase.

[0045] FIG. 2 is a conceptual drawing illustrating IMD 16 and leads 18, 20, and 22 of system 10 in greater detail. As shown in FIG. 2, IMD 16 is coupled to leads 18, 20, and 22. Leads 18, 20, 22 may be electrically coupled to therapy delivery circuitry and sensing circuitry of IMD 16 via connector block 34. In some examples, proximal ends of leads 18, 20, 22 may include electrical contacts that electrically couple to respective electrical contacts within connector block 34 of IMD 16. In addition, in some examples, leads 18, 20, 22 may be mechanically coupled to connector block 34 with the aid of set screws, connection pins, snap connectors, or another suitable mechanical coupling mechanism.

[0046] Each of the leads 18, 20, 22 includes an elongated insulative lead body, which may carry a number of concentric coiled conductors separated from one another by tubular insulative sheaths. Bipolar electrodes 40 and 42 are located adjacent to a distal end of lead 18 in right ventricle 28. In addition, bipolar electrodes 44 and 46 are located adjacent to a distal end of lead 20 in coronary sinus 30 and bipolar electrodes 48 and 50 are located adjacent to a distal end of lead 22 in right atrium 26. In the illustrated example, there are no electrodes located in left atrium 33. However, other examples may include electrodes in left atrium 33. Furthermore, in examples in which IMD 16 is configured to deliver conduction system pacing, lead 18 may configured / positioned differently than illustrated in FIG. 2 so that electrode 42 may stimulate the conduction system, e.g., His bundle, left bundle branch, or right bundle branch. For example, electrode 42 may be positioned on or in the ventricular septum.

[0047] Electrodes 40, 44, and 48 may take the form of ring electrodes, and electrodes 42, 46 and 50 may take the form of fixed or extendable helix tip electrodes mounted to insulative electrode heads 52, 54 and 56, respectively. In other examples, one or more of electrodes 42, 46 and 50 may take the form of small circular electrodes at the tip of a tined lead or other fixation element. Leads 18, 20, 22 also include elongated electrodes 62, 64, 66, respectively, which may take the form of a coil. Each of the electrodes 40, 42, 44, 46, 48, 50, 62, 64 and 66 may be electrically coupled to a respective one of the coiled conductors within the lead body of its associated lead 18, 20, 22, and thereby coupled to respective ones of the electrical contacts on the proximal end of leads 18, 20 and 22.

[0048] In some examples, as illustrated in FIG. 2, IMD 16 includes one or more housing electrodes, such as 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 uninsulatedportions 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. As described in further detail with reference to FIG. 3, housing 60 may enclose therapy delivery circuitry configured to generate therapeutic signals, such as cardiac pacing pulses and defibrillation shocks, as well as sensing circuitry for sensing the rhythm of heart 12 and other patient parameters.

[0049] IMD 16 may sense electrical signals attendant to the depolarization and repolarization of heart 12 via electrodes 40, 42, 44, 46, 48, 50, 62, 64 and 66. The electrical signals are conducted to IMD 16 from the electrodes via the respective leads 18, 20, 22. IMD 16 may sense such electrical signals via any bipolar combination of electrodes 40, 42, 44, 46, 48, 50, 62, 64 and 66. Furthermore, any of the electrodes 40, 42, 44, 46, 48, 50, 62, 64 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.

[0050] In some examples, IMD 16 delivers pacing pulses via bipolar combinations of electrodes 40, 42, 44, 46, 48 and 50 to produce depolarization of cardiac tissue of heart 12.In some examples, IMD 16 delivers pacing pulses via any of electrodes 40, 42, 44, 46, 48 and 50 in combination with housing electrode 58 in a unipolar configuration. Furthermore, IMD 16 may deliver defibrillation pulses to heart 12 via any combination of elongated electrodes 62, 64, 66, and housing electrode 58. Electrodes 58, 62, 64, 66 may also be used to deliver cardioversion pulses to heart 12. Electrodes 62, 64, 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. The combination of electrodes used for delivery of therapy or sensing, their associated conductors and connectors, and any tissue or fluid between the electrodes, may define an electrical path.

[0051] In some examples, IMD 16 may sense a far-field EGM signal via coil electrode 62 positioned in RV 28 and housing electrode 58. Additionally, or alternatively, IMD 16 may sense the EGM signal via tip electrode 42 and housing electrode 58. Other EGM signal sensing configurations are also possible.

[0052] In addition to EGM signals, any of electrodes 40, 42, 44, 46, 48, 50, 62, 64, 66, and 58 may be used to sense non-cardiac signals. For example, two or more electrodes may be used to measure an impedance, e.g., within the thoracic cavity of patient 14. This impedance may be used to generate a fluid index patient metric that indicates the amount of fluid building up within patient 14. Since a greater amount of fluid may indicate increasedpumping loads on heart 12, the fluid index may be used as an indicator of HF risk level. IMD 16 may periodically measure the intrathoracic impedance to identify a trend in the fluid index over days, weeks, months, and even years of patient monitoring.

[0053] In some examples, the two electrodes used to measure the intrathoracic impedance may be located at two different positions within the chest of patient 14. For example, coil electrode 62 and housing electrode 58 may be used as the sensing vector for intrathoracic impedance because electrode 62 is located within RV 28 and housing electrode 58 is located at the IMD 16 implant site generally in the upper chest region. However, other electrodes spanning multiple organs or tissues of patient 14 may also be used, e.g., an additional implanted electrode used only for measuring thoracic impedance.

[0054] FIG. 3 is a functional block diagram illustrating an example configuration of IMD 16. In the illustrated example, IMD 16 includes processing circuitry 80, sensing circuitry 82, one or more sensors 84, therapy delivery circuitry 86, communication circuitry 88, and memory 90. Memory 90 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 90 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 or analog media.

[0055] Processing circuitry 80 may include any one or more of a microprocessor, a controller, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or equivalent discrete or analog 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, e.g., may be embodied as software or firmware executed on processing circuitry.

[0056] Processing circuitry 80 controls therapy delivery circuitry 86 to deliver therapy to heart 12 according to a therapy parameters and programs which may be stored in memory 90. An example of therapy parameters stored in memory 90 are RSA pacing parameters 96 for delivery of cardiac pacing. RSA pacing parameters 96 may include timing and duration parameters, such as an amount of time to increase and / or decrease a rate of cardiac pacingpulses to mimic RSA. Therapy delivery circuitry 86 is electrically coupled to electrodes 40, 42, 44, 46, 48, 50, 58, 62, 64, 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. In the illustrated example, therapy delivery circuitry 86 is configured to generate and deliver electrical therapy to heart 12. For example, therapy delivery circuitry 86 may deliver defibrillation shocks to heart 12 via at least two electrodes 58, 62, 64, 66. Therapy delivery circuitry 86 may deliver pacing pulses via ring electrodes 40, 44, 48 coupled to leads 18, 20, and 22, respectively, and / or helical electrodes 42, 46, and 50 of leads 18, 20, and 22, respectively. In some examples, therapy delivery circuitry 86 delivers pacing, cardioversion, or defibrillation stimulation in the form of electrical pulses. In other examples, therapy delivery circuitry 86 may deliver one or more of these types of stimulation in the form of other signals, such as sine waves, square waves, or other substantially continuous time signals.

[0057] Therapy delivery circuitry 86 includes circuitry, such as charge pumps, capacitors, current mirrors, or other signal generation circuitry for generating a pulse or other signal. Therapy delivery circuitry 86 may include a switch module and processing circuitry 80 may use the switch module to select, e.g., via a data / address bus, which of the available electrodes are used to deliver antitachyarrhythmia shocks or pacing pulses. The switch module may include a switch array, switch matrix, multiplexer, or any other type of switching device suitable to selectively couple stimulation energy to selected electrodes.

[0058] Sensing circuitry 82 monitors signals from at least one of electrodes 40, 42, 44, 46, 48, 50, 58, 62, 64 or 66 in order to monitor EGM signals of the heart and / or electrical activity of heart 12, impedance, respiration of patient 14, or other patient parameters, values of which may be stored as patient parameter data 92 in memory 90. Sensing may be done to detect intrinsic cardiac depolarizations, determine heart rates or heart rate variability, or to detect arrhythmias or other electrical signals. Sensing circuitry 82 may include one or more filters, amplifiers, analog-to-digital converters, or other sensing circuitry.

[0059] Sensing circuitry 82 may also include a switch module to select which of the available electrodes are used to sense the heart activity, depending upon which electrode combination, or electrode vector, is used in the current sensing configuration. In some examples, processing circuitry 80 may select the electrodes that function as sense electrodes, i.e., select the sensing configuration, via the switch module within sensing circuitry 82. Sensing circuitry 82 may include one or more detection channels, each of which may be coupled to a selected electrode configuration for detection of cardiac signals via thatelectrode configuration. Some detection channels may be configured to detect cardiac events, such as P- or R-waves, and provide indications of the occurrences of such events to processing circuitry 80.

[0060] Processing circuitry 80 may be configured to identify inspiration and / or expiration phases of a patient based on the EGM signal. To identify inspiration and / or expiration phases, processing circuitry 80 may detect peaks and troughs in a respiration signature of the EGM signal, e.g., identifying maximal or minimal values of the signal, by identifying zero slope points (zero crossings in a derivative or differential of the signal), points where slope of the respiration signature of the EGM reverses sign (e.g., from negative to positive for troughs and positive to negative for peaks) or using any other peak / trough detection techniques. Processing circuitry 80 may determine an expiration phase as an interval or window from an identified peak to a subsequent trough, and an inspiration phase as an interval or window from an identified trough to a subsequent peak. Processing circuitry 80 may determine respiration effort based on one or more of a peak-to-trough amplitude or a slope of the signal within the inspiration phase. Processing circuitry 80 may determine tidal volume based on an area under the curve during the respiration cycle. In some examples, processing circuitry 80 may determine tidal volume based on a peak-to-trough amplitude, which may vary with tidal volume.

[0061] One or more sensor(s) 84 may include, as examples, one or more accelerometers, microphones, temperature sensors, or optical sensors that are configured to provide signals or data representing one or more patient parameters to processing circuitry 80 via sensing circuitry 82. In some examples, based on a signal from one or more accelerometers, processing circuitry 80 may determine postures and / or activity levels of patient 14. In some examples, processing circuitry 80 may determine respiratory information based on signals from one or more sensor(s) 84. For example, processing circuitry 80 may determine respiratory information based on an accelerometer signal. In some examples, processing circuitry 80 may determine respiratory information based on the accelerometer signal and the EGM. In other examples, processing circuitry 80 may use the accelerometer signal instead of the EGM.

[0062] Processing circuitry 80 may implement programmable counters that control the basic time intervals associated with DDD, VVI, DVI, VDD, AAI, DDI, DDDR, VVIR, DVIR, VDDR, AAIR, DDIR, CRT, and other modes of pacing. Intervals defined by processing circuitry 80 may include atrial and ventricular pacing escape intervals, A-V intervals, V-V intervals, and refractory periods during which sensed P-waves and R-wavesare ineffective to restart timing of the intervals. The durations of these intervals may be determined by processing circuitry 80 in response to stored data in memory 90.

[0063] In some examples, processing circuitry 80 may modify escape intervals based on a rate responsive pacing mode. Processing circuitry 80 may determine a sensor indicated pacing rate based on sensed parameters of patient 14, such as one or more of activity level or respiration rate, and thereby modify the escape interval and pacing rate to provide cardiac pacing that supports the activity of patient 14. In some examples, processing circuitry 80 may additionally modify the pacing mode based on a patient disease state or other patient data. In some examples, processing circuitry 80 may control IMD 16 to provide CRT by controlling delivery of pacing pulses to one or both of RV 28 and LV 32 based on atrioventricular timing and interventricular timing specified by one or more A-V intervals and V-V intervals.

[0064] Interval counters implemented by processing circuitry 80 may be reset upon sensing of R-waves and P-waves with detection channels of sensing circuitry 82. In examples in which IMD 16 provides pacing, therapy delivery circuitry 86 may include pacer output circuits that are coupled, e.g., selectively by a switching module, to any combination of electrodes 40, 42, 44, 46, 48, 50, 58, 62, or 66 appropriate for delivery of a bipolar or unipolar pacing pulse to one of the chambers of heart 12. In such examples, processing circuitry 80 may reset the interval counters upon the generation of pacing pulses by therapy delivery circuitry 86, and thereby control the basic timing of cardiac pacing functions, including anti-tachyarrhythmia pacing.

[0065] The value of the count present in the interval counters when reset by sensed R-waves and P-waves may be used by processing circuitry 80 to measure the durations of R-R intervals, P-P intervals, P-R intervals and R-P intervals, which are measurements that may be stored in memory 90. Processing circuitry 80 may use the count in the interval counters to detect a tachyarrhythmia event, such as atrial fibrillation (AF), atrial tachycardia (AT), ventricular fibrillation (VF), or ventricular tachycardia (VT). These intervals may also be used to detect the overall heart rate, ventricular contraction rate, and heart rate variability. A portion of memory 90 may be configured as a plurality of recirculating buffers, capable of holding series of measured intervals, which may be analyzed by processing circuitry 80 in response to the occurrence of a pace or sense interrupt to determine whether the patient's heart 12 is presently exhibiting atrial or ventricular tachyarrhythmia.

[0066] In some examples, processing circuitry 80 may determine that tachyarrhythmia has occurred by identification of shortened R-R (or P-P) interval lengths. Generally, processing circuitry 80 detects tachycardia when the interval length falls below 220milliseconds (ms) and fibrillation when the interval length falls below 180 ms. These interval lengths are merely examples, and a user may define the interval lengths as desired, which may then be stored within memory 90. This interval length may need to be detected for a certain number of consecutive cycles, for a certain percentage of cycles within a running window, or a running average for a certain number of cardiac cycles, as examples.

[0067] In the event that processing circuitry 80 detects an atrial or ventricular tachyarrhythmia based on signals from sensing circuitry 82, and an anti -tachyarrhythmia pacing regimen is desired, timing intervals for controlling the generation of anti-tachyarrhythmia pacing therapies by therapy delivery circuitry 86 may be loaded by processing circuitry 80 to control the operation of the escape interval counters therein and to define refractory periods during which detection of R-waves and P-waves is ineffective to restart the escape interval counters for the an anti-tachyarrhythmia pacing. In the event that processing circuitry 80 detects an atrial or ventricular tachyarrhythmia based on signals from sensing circuitry 82, and a cardioversion or defibrillation shock is desired, processing circuitry 80 may control the amplitude, form and timing of the shock delivered by therapy delivery circuitry 86.

[0068] Memory 90 may be configured to store a variety of operational parameters, therapy parameters, sensed and detected data, and any other information related to the therapy and treatment of patient 14. In the example of FIG. 3, memory 90 includes patient parameter data 92, RSA activation criteria 94, and RSA pacing parameters. Patient parameter data 92 may store all of the data generated from the sensing and detecting of patient parameters described herein, such as heart rates, inspiration phases and / or expiration phases, activity, posture, fluid index, an atrial tachycardia or fibrillation burden, a ventricular contraction rate during atrial fibrillation, a nighttime heart rate, a difference between night and day heart rate, a heart rate variability, a cardiac resynchronization therapy percentage, a bradyarrhythmia pacing therapy percentage (in a ventricle and / or atrium), and number or frequency of electrical shock events, blood pressure, right ventricular pressure, pulmonary artery pressure, patient temperature, or biomarkers such as a brain natriuretic peptide (BNP), troponin, or related surrogates. In some examples, processing circuitry 80 may determine HF metrics based on sensed parameter data 92 and determine a HF risk level based on the HF metrics.

[0069] RSA activation criteria 94 includes one or more criteria that processing circuitry 80 may apply to patient parameter data 92 to determine whether to adjust cardiac pacing to mimic RSA. Processing circuitry 80 may adjust pacing to mimic RSA if patient parameterdata 92 satisfies RSA activation criteria 94. RSA activation criteria 94 may be fixed, programmable by a user, or variable based on conditions determined by processing circuitry 80. To adjust cardiac pacing to mimic RSA, processing circuitry 80 control therapy delivery circuitry 86 to deliver pacing pulses, according to RSA pacing parameters 96, with increasing rates during an inspiration phase of a respiratory cycle, and, in some examples, decreasing rates during an expiration phase of the cardiac cycle, as described herein. The increasing and decreasing of pacing rates may be sequential, on a beat-to-beat or other basis.

[0070] Communication 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, communication circuitry 88 may communicate with external device 24 with the aid of an antenna, which may be internal and / or external.

[0071] FIG. 4 is a flow diagram illustrating an example operation of a device to adjust a rate of cardiac pacing to mimic RSA. Although described in the context of IMD 16, the example operation of FIG. 4 may be additionally or alternatively performed by other devices, as described herein.

[0072] In some examples, processing circuitry 80 of IMD 16 controls therapy delivery circuitry 86 to deliver cardiac pacing according to a base mode, such as a demand mode, rate responsive mode, CRT mode, or conduction system pacing mode. Sensing circuitry 82 and / or sensor(s) 84 sense an EGM of the patient, e.g., a far-field EGM, which is indicative of respiration information, i.e., inspiration phase and expiration phase information. Processing circuitry 80 identifies a prior inspiration phase of the patient (402). In some examples, identifying a prior inspiration phase comprises identifying a beginning of the prior inspiration phase, e.g., by identifying a trough, or local minimum, in a respiratory signature based on an EGM signal. Processing circuitry 80 additionally determines heart rate of the patient continuously (404). In some examples, processing circuitry 80 determines the heart rate based on the EGM signal. Processing circuitry 80 predicts a beginning of a subsequent inspiration phase based on at least the prior inspiration phase (406). In some examples, processing circuitry 80 may utilize more than one prior inspiration phase to predict the beginning of the subsequent inspiration phase. For example, processing circuitry 80 may predict the beginning of the subsequent inspiration phase based on the immediate prior inspiration phase, as well as one or more additional prior inspiration phases, e.g., inspiration phases that occurred prior to the immediate prior inspiration phase. In some examples, processing circuitry 80 may determine that the immediate prior inspiration phase should not be used to predict thesubsequent inspiration phase. For example, processing circuitry 80 may determine the immediate prior inspiration phase is indicative of a premature beat. In response to determining the immediate prior inspiration phase is indicative of the premature beat, processing circuitry 80 may use inspiration phase information corresponding to the inspiration phases that occurred prior to the immediate prior inspiration phase to predict the beginning of the subsequent inspiration phase.

[0073] In some examples, processing circuitry 80 may be configured to predict the beginning of the subsequent inspiration phase based on a duration and / or timing of the prior inspiration phase. In some examples, an algorithm may predict the beginning of the subsequent inspiration phase based on a running average or a moving average of a plurality of prior inspiration phases. In some examples, processing circuitry 80 may implement one or more machine learning models to predict the beginning of the subsequent inspiration phase. Based on the heart rate and the prior inspiration phase(s), processing circuitry 80 controls therapy delivery circuitry 86 to adjust a rate of the cardiac pacing pulses during the subsequent inspiration phase (408). In some examples, processing circuitry 80 may continuously update the algorithm for subsequent predictions based on the accuracy of one or more previous predictions relative to one or more previous inspiration phases. For example, if a previous prediction of an inspiration phase is relatively accurate to the detected inspiration phase, processing circuitry 80 may maintain the algorithm, and if the previous prediction of an inspiration phase is relatively inaccurate, processing circuitry 80 may update the algorithm to address the inaccuracy.

[0074] FIG. 5 is a flow diagram illustrating an example operation of a device to determine whether to adjust a rate of cardiac pacing to mimic RSA. Although described in the context of IMD 16, the example operation of FIG. 5 may be additionally or alternatively performed by other devices, as described herein. In some examples, processing circuitry 80 of IMD 16 controls therapy delivery circuitry 86 to deliver cardiac pacing according to a base mode, such as a demand mode, rate responsive mode, CRT mode, or conduction system pacing mode. Sensing circuitry 82 and / or sensor(s) 84 sense an EGM of the patient, which is indicative of respiration information, i.e., inspiration phase and expiration phase information. Processing circuitry 80 identifies a prior inspiration phase of the patient (502). In some examples, identifying a prior inspiration phase comprises identifying a beginning of the prior inspiration phase, e.g., by identifying a trough, or local minimum, in the EGM signal. Processing circuitry 80 continuously determines the heart rate of the patient (504). In some examples, processing circuitry 80 additionally identifies a prior expiration phase, e.g., toimprove an accuracy of subsequent predictions (506). In some examples, processing circuitry 80 may utilize more than one prior inspiration phase and / or expiration phase to predict the beginning of the subsequent inspiration phase and / or expiration phase. For example, processing circuitry 80 may predict the beginning of the subsequent inspiration phase and / or subsequent expiration phase based on the immediate prior inspiration phase and / or expiration phase, as well as one or more additional prior inspiration phases and / or expiration phases, e.g., inspiration phases and / or expiration phases that occurred prior to the immediate prior inspiration phase and / or expiration phase. In some examples, processing circuitry 80 may determine that the immediate prior inspiration phase and / or expiration phase should not be used to predict the subsequent inspiration phase and / or expiration phase. For example, processing circuitry 80 may determine the immediate prior inspiration phase and / or expiration phase is indicative of a premature beat. In response to determining the immediate prior inspiration phase and / or expiration phase is indicative of the premature beat, processing circuitry 80 may use inspiration phase and / or expiration phase information corresponding to the inspiration phases and / or expiration phases that occurred prior to the immediate prior inspiration phase and / or expiration phase to predict the beginning of the subsequent inspiration phase and / or expiration phase. Based on the prior inspiration phase(s) and / or the prior expiration phase(s), processing circuitry 80 predicts a beginning of a subsequent inspiration phase (508). Optionally, based on the prior expiration phase and / or the prior inspiration phase, processing circuitry 80 predicts a beginning of a subsequent expiration phase (510). Based on the heart rate and one or more of the prior inspiration phase(s) and / or prior expiration phase(s), processing circuitry determines whether to adjust cardiac pacing to mimic RSA during the subsequent inspiration phase and, optionally, during the subsequent expiration phase (512). If processing circuitry 80 determines to adjust cardiac pacing (“YES” of 512), processing circuitry 80 controls therapy delivery circuitry 86 to adjust cardiac pacing pulses to mimic RSA, e.g., based on RSA pacing parameters 96 (514). Processing circuitry 80 continues the example operation. If processing circuitry 80 determines not to adjust cardiac pacing (“NO” of 512), the process continues. In some examples, processing circuitry 80 determines whether to adjust cardiac pacing pulses to mimic RSA based on a comparison between patient parameter data 92 and RSA activation criteria 94. For example, processing circuitry 80 may determine whether to adjust cardiac pacing based on whether patient 14 is already achieving RSA intrinsically. If patient 14 is achieving RSA, e.g., if patient 14’ s heart rate is intrinsically increasing during inspiration and decreasing during expiration, e.g., by at least 1 beat per minute, processing circuitry 80 may determine not to adjust cardiac pacing. Ifpatient 14 is not achieving RSA, processing circuitry 80 may determine to adjust cardiac pacing to mimic RSA.

[0075] In some examples, patient 14 may be fully paced, i.e., IMD 16 may initiate every depolarization. In examples in which patient 14 is fully paced, processing circuitry may increase a rate of, or overdrive, pacing during inspiration phases relative to a baseline heart rate and may decrease the rate of pacing during expiration phases, e.g., decrease the rate of pacing relative to the baseline heart rate or decrease the rate of pacing relative to the pacing rate during inspiration phases. In other examples, patient 14 may not be fully paced, i.e., IMD 16 initiates some depolarizations, e.g., when the heart rate drops below a threshold or when patient 14 experiences a cardiac event, but patient 14’s intrinsic pacing system initiates other depolarizations. In examples in which patient 14 is not fully paced, processing circuitry may increase the rate of pacing during inspiration phases and may allow patient 14’ s intrinsic pacing system to drive pacing at a relatively lower heart rate, e.g., an intrinsic baseline heart rate, during expiration phases.

[0076] The example of FIG. 5 described the identification of the prior expiration phase and the prediction of the expiration phase as optional. However, in other examples, processing circuitry 80 may be configured to identify the prior expiration phase to predict the subsequent expiration phase and / or the subsequent inspiration phase and may optionally identify the prior inspiration phase, e.g., to improve accuracy of the predictions.

[0077] FIG. 6 is a flow diagram illustrating an example operation for determining whether to adjust cardiac pacing to mimic RSA based on patient heart rate information, in accordance with one or more techniques of this disclosure. In some examples, the example operation of FIG. 6 may be part of the determination of whether to adjust cardiac pacing in step 512 of FIG. 5. Processing circuitry 80 determines an average heart rate of the patient (602). In some examples, the average heart rate comprises a running average of the heart rate or a moving average of the heart rate. Processing circuitry 80 compares the average heart rate to a threshold heart rate value (604). In some examples, memory 90 stores the threshold heart rate value in RSA activation criteria 94 and the average heart rate in patient parameter data 92. In some examples, the threshold heart rate value is not patient specific. In other examples, processing circuitry 80 determines a threshold heart rate value based on patient parameter data 92. In some examples, processing circuitry 80 may implement a machine learning model to determine the threshold heart rate value. In other examples, the clinician may determine the threshold heart rate value. In some examples, overdrive RSA pacing may not be desiredwhere pacing burden is already relatively high, and / or the patient is experiencing an elevated heart rate.

[0078] If the average heart rate exceeds the threshold heart rate value (“YES” of 604), processing circuitry 80 determines not to control therapy delivery circuitry 86 to adjust cardiac pacing pulses to mimic RSA (608). If the average heart rate does not exceed the threshold heart rate value (“NO” of 604), processing circuitry 80 controls therapy 86 to adjust cardiac pacing pulses to mimic RSA (606).

[0079] FIG. 7 is a graph illustrating an example EGM signal comprising inspiration phase and expiration phase information. Two of any electrodes carried on leads 18, 20, 22 and / or housing electrode 58 sense EGM signal 702, such as coil electrode 62 in RV 28 and housing electrode 58. Peaks of EGM signal 702 are indicative of respiratory signature 704. Troughs 708, or local minima, of respiratory signature 704 are indicative of beginnings of inspiration phases. Peaks 706, or local maxima, of respiratory signature 704 are indicative of beginnings of expiration phases. In some examples, processing circuitry 80 is configured to identify inspiration phases and / or expiration phases. In examples in which processing circuitry 80 is configured to identify inspiration phases and expiration phases, processing circuitry 80 may detect a peak of peaks 706 or a trough of troughs 708 by continuously comparing successive samples of respiratory signature 704. . In some examples, if a slope associated with successive samples of respiratory signature 704 changes from negative to positive, processing circuitry 80 detects a trough, i.e., a local minimum of respiratory signature 704, and logs the trough as a start of inspiration to be stored in patient parameter data 92 (FIG. 3). If a slope associated with successive samples changes from positive to negative, processing circuitry 80 detects a peak, i.e., a local maximum of respiratory signature 704, and logs the peak as a start of expiration to be stored in patient parameter data 92. In some examples, processing circuitry 80 may apply one or more thresholds during the peak and trough detections processes to prevent false peak and trough detections caused by noise or other sensing issues.

[0080] FIG. 8 is a flow diagram illustrating an example operation for adjusting cardiac pacing based on a patient state. In some examples, patient parameter data 92 may include data indicative of a patient state. For example, patient parameter data 92 may include one or more of data sensed by electrodes 40, 42, 62, 44, 46, 64, 48, 50, 66, and / or 58, data sensed by sensor(s) 84, or historical patient data. As examples, patient state can be based on one or more of patient activity level, patient age, or patient disease progression, e.g., HF risk level. Based on patient parameter data 92, processing circuitry 80 determines a patient state (802).Based on the patient state, processing circuitry 80 may adjust the rate of cardiac pacing pulses (804).

[0081] In examples in which patient state is based on patient activity level, processing circuitry 80 may determine a patient motion level, e.g., via an accelerometer of sensor(s) 84, and / or a patient heart rate, e.g., based on an EGM signal. Based on the patient activity level, processing circuitry 80 may control therapy delivery circuitry 86 to adjust the rate of cardiac pacing pulses. For example, processing circuitry 80 may be configured to adjust cardiac pacing pulses to mimic RSA by overdriving pacing during inspiration phase within a range, e.g., by 5 to 20 beats per minute, relative to a baseline heart rate or a paced expiration phase heart rate. Based on the patient activity level, processing circuitry 80 may determine to adjust cardiac pacing pulses to overdrive pacing at a low end of the range, e.g., 5 beats per minute, or at a high end of the range, e.g., 20 beats per minute.

[0082] In examples in which patient state is based on patient disease progression, processing circuitry 80 may determine disease state progression based on, for example, a HF risk level. Processing circuitry 80 may determine to adjust cardiac pacing pulses to overdrive pacing at the low end of the range, e.g., 5 beats per minute, for patients at a first, e.g., a relatively high, HF risk level and overdrive pacing at the high end of the range, e.g., 20 beats per minute, for patients at a second, e.g., a relatively low, HF risk level different from the first HF risk level.

[0083] In some examples, e.g., if patient 14’s average heart rate is near an upper tracking rate value, e.g., the threshold in step 604 of FIG. 6, processing circuitry may determine to adjust cardiac pacing to increase a rate of cardiac pacing to a lower extent, e.g., at a low end of the range, such as 5 beats per minute, to, for example, ensure that patient 14’ s average heart rate does not exceed the upper tracking rate value, e.g., during inspiration. The threshold in step 604 is provided merely as an example. In other examples, the upper tracking rate value comprises a value other than the value of the threshold in step 604. In some examples, the upper tracking rate value may be a predetermined value (e.g. 90 bpm, 100 bpm, 105 bpm, 110 bpm) or may be equal to a certain percentage (e.g. 80%, 90%, 100%) of the programmed upper tracking rate of implantable cardiac device.

[0084] In some examples, a clinician may adjust the range for overdrive pacing, e.g., to tailor pacing to patient specific needs. In other examples, processing circuitry 80 may adjust the range for overdrive pacing, e.g., based on patient parameter data 92. In some examples, processing circuitry 80 may implement a machine learning model to determine a range for overdrive pacing of the patient.

[0085] Example 1. A device comprising: therapy delivery circuitry configured to deliver cardiac pacing pulses to a heart of a patient via a plurality of electrodes; sensing circuitry configured to sense an electrogram (EGM) signal of a patient; and processing circuitry configured to: identify a prior inspiration phase based on the EGM signal; determine a heart rate of the patient based on the EGM signal; predict a beginning of a subsequent inspiration phase based on the prior inspiration phase; and control the therapy delivery circuitry to adjust a rate of the cardiac pacing during the subsequent inspiration phase based on the heart rate and the prior inspiration phase.

[0086] Example 2. The device of example 1, wherein adjusting the rate of the cardiac pacing during the subsequent inspiration phase comprises causing the delivery of the cardiac pacing pulses to more closely mimic respiratory sinus arrhythmia (RSA).

[0087] Example 3. The device of any one or more of examples 1-2, wherein the processing circuitry is further configured to: identify a prior expiration phase based on the EGM signal; predict a beginning of a subsequent expiration phase based on at least the prior expiration phase; and control the therapy delivery circuitry to adjust the rate of the cardiac pacing during the subsequent inspiration phase and the subsequent expiration phase based on the heart rate, the prior inspiration phase, and the prior expiration phase.

[0088] Example 4. The device of example 3, wherein the processing circuitry is further configured to: determine the patient is not achieving RSA based on the prior inspiration phase, the prior expiration phase, and the heart rate; and adjust the rate of the cardiac pacing to more closely mimic RSA based on the determination.

[0089] Example 5. The device of any one or more of examples 1-4, wherein to adjust the cardiac pacing pulses, the processing circuitry is configured to: control the therapy delivery circuitry to increase the rate of the cardiac pacing pulses from a baseline rate to a higher rate during the subsequent inspiration phase.

[0090] Example 6. The device of any one or more of examples 3-4, wherein to adjust the cardiac pacing pulses, the processing circuitry is configured to: control the therapy delivery circuitry to increase the rate of the cardiac pacing pulses from a baseline rate to a higher rate during the subsequent inspiration phase and decrease the rate of the cardiac pacing pulses relative to the higher rate during the subsequent expiration phase.

[0091] Example 7. The device of any one or more of examples 1-6, wherein the processing circuitry is further configured to: compare an average patient heart rate to a threshold; and control the therapy delivery circuitry to adjust the cardiac pacing pulses to mimic RSA responsive to the average heart rate falling below the threshold.

[0092] Example 8. The device of any one or more of examples 1-7, wherein theEGM signal comprises a far-field EGM signal.

[0093] Example 9. The device of any one or more of examples 1-8, wherein to identify the prior inspiration phase, the processing circuitry is configured to: identify a local minimum of a respiratory signature based on the EGM signal, wherein the local minimum of the respiratory signature is indicative of the beginning of the prior inspiration phase.

[0094] Example 10. The device of any one or more of examples 3-9, wherein to identify the prior expiration phase, the processing circuitry is configured to: identify a local maximum of a respiratory signature based on the EGM signal, wherein the local maximum of the respiratory signature is indicative of the beginning of the prior expiration phase.

[0095] Example 11. The device of any one or more of examples 1-10, wherein to sense the EGM signal, the sensing circuitry is configured to: sense the EGM signal via an RV coil electrode of the device electrically coupled to a can electrode of the device; or sense the EGM signal via an RV tip electrode of the device electrically coupled to the can electrode of the device.

[0096] Example 12. The device of any one or more of examples 1-11, wherein the processing circuitry is further configured to: determine a patient state; and control the therapy delivery circuitry to adjust the rate of the cardiac pacing pulses based on the patient state.

[0097] Example 13. The device of example 12, wherein the patient state comprises one or more of: a patient disease state; or a patient activity level.

[0098] Example 14. The device of any one or more of examples 1-13, wherein the device comprises an implantable medical device (IMD).

[0099] Example 15. The device of example 14, wherein the IMD comprises a pacemaker.

[0100] Example 16. A method comprising: sensing, by sensing circuitry of a medical device of a medical device system, an electrogram (EGM) signal of a patient; and identifying, by processing circuitry of the system, a prior inspiration phase based on the EGM signal; determining, by the processing circuitry, a heart rate of the patient based on the EGM signal; predicting, by the processing circuitry, a beginning of a subsequent inspiration phase based on the prior inspiration phase; and controlling, by the processing circuitry, therapy delivery circuitry of the medical device to adjust a rate of cardiac pacing pulses to a heart of the patient during the subsequent inspiration phase based on the heart rate and the prior inspiration phase.

[0100] Example 17. The method of example 16, wherein adjusting the rate of the cardiac pacing during the subsequent inspiration phase comprises causing the delivery of the cardiac pacing pulses to more closely mimic respiratory sinus arrhythmia (RSA).

[0101] Example 18. The method of any one or more of examples 16-17, wherein the processing circuitry is further configured to: identifying, by the processing circuitry, a prior expiration phase based on the EGM signal; predicting, by the processing circuitry, a beginning of a subsequent expiration phase based on at least the prior expiration phase; and controlling, by the processing circuitry, the therapy delivery circuitry to adjust the rate of the cardiac pacing during the subsequent inspiration phase and the subsequent expiration phase based on the heart rate, the prior inspiration phase, and the prior expiration phase.

[0102] Example 19. The method of example 18, further comprising: determining, by the processing circuitry, the patient is not achieving RSA based on the prior inspiration phase the prior expiration phase, and the heart rate; and adjusting, by the processing circuitry, the rate of the cardiac pacing to more closely mimic RSA based on the determination.

[0103] Example 20. The method of any one or more of examples 16-19, wherein adjusting the cardiac pacing pulses comprises: controlling, by the processing circuitry, the therapy delivery circuitry to increase the rate of the cardiac pacing pulses from a baseline rate to a higher rate during the subsequent inspiration phase.

[0104] Example 21. The method of any one or more of examples 18-20, wherein adjusting the cardiac pacing pulses comprises: controlling, by the processing circuitry, the therapy delivery circuitry to increase the rate of the cardiac pacing pulses from a baseline rate to a higher rate during the subsequent inspiration phase and decrease the rate of the cardiac pacing pulses relative to the higher rate during the subsequent expiration phase.

[0105] Example 22. The method of any one or more of examples 16-21, further comprising: comparing, by the processing circuitry, an average patient heart rate to a threshold; and controlling, by the processing circuitry, the therapy delivery circuitry to adjust the cardiac pacing pulses to mimic RSA responsive to the average heart rate falling below the threshold.

[0106] Example 23. The method of any one or more of examples 16-22, wherein the EGM signal comprises a far-field EGM signal.

[0107] Example 24. The method of any one or more of examples 16-23, wherein identifying the prior inspiration phase comprises: identifying, by the processing circuitry, a local minimum of a respiratory signature based on the EGM signal, wherein the localminimum of the respiratory signature is indicative of the beginning of the prior inspiration phase.

[0108] Example 25. The method of any one or more of examples 18-24, wherein identifying the prior expiration phase comprises: identifying, by the processing circuitry, a local maximum of a respiratory signature based on the EGM signal, wherein the local maximum of the respiratory signature is indicative of the beginning of the prior expiration phase.

[0109] Example 26. The method of any one or more of examples 16-25, wherein sensing the EGM signal comprises: sensing, by the sensing circuitry, the EGM signal via an RV coil electrode of the device electrically coupled to a can electrode of the device; or sensing, by the sensing circuitry, the EGM signal via an RV tip electrode of the device electrically coupled to the can electrode of the device.

[0110] Example 27. The method of any one or more of examples 16-26, further comprising: determining, by the processing circuitry, a patient state; and controlling, by the processing circuitry, the therapy delivery circuitry to adjust the rate of the cardiac pacing pulses based on the patient state.

[0111] Example 28. The method of example 27, wherein the patient state comprises one or more of: a patient disease state; or a patient activity level.

[0112] Example 29. The method of any one or more of examples 16-28, wherein the medical device comprises and implantable medical device (IMD).

[0113] Example 30. The method of example 29, wherein the IMD comprises a pacemaker.

[0114] Example 31. A non-transitory computer-readable storage medium storing instructions that, when executed by processing circuitry, cause the processing circuitry to: control sensing circuitry to sense an electrogram (EGM) signal of a patient; identify a prior inspiration phase based on the EGM signal; determine a heart rate of the patient based on the EGM signal; predict a beginning of a subsequent inspiration phase based on the prior inspiration phase; and control therapy delivery circuitry to adjust a rate of cardiac pacing during the subsequent inspiration phase based on the heart rate and the prior inspiration phase.

[0115] Example 32. A device comprising: therapy delivery circuitry configured to deliver cardiac pacing pulses to a heart of a patient via a plurality of electrodes; sensing circuitry configured to sense an electrogram (EGM) signal of a patient; and processing circuitry configured to: identify a prior expiration phase based on the EGM signal; determinea heart rate of the patient based on the EGM signal; predict a beginning of a subsequent expiration phase based on the prior expiration phase; and control the therapy delivery circuitry to adjust a rate of the cardiac pacing during the subsequent expiration phase based on the heart rate and the prior expiration phase.

[0116] Example 33. The device of example 32, wherein adjusting the rate of the cardiac pacing during the subsequent expiration phase comprises causing the delivery of the cardiac pacing pulses to more closely mimic respiratory sinus arrhythmia (RSA).

[0117] Example 34. The device of any one or more of examples 32-33, wherein the processing circuitry is further configured to: identify a prior inspiration phase based on the EGM signal; predict a beginning of a subsequent inspiration phase based on at least the prior inspiration phase; and control the therapy delivery circuitry to adjust the rate of the cardiac pacing during the subsequent expiration phase and the subsequent inspiration phase based on the heart rate, the prior expiration phase, and the prior inspiration phase.

[0118] Example 35. The device of example 34, wherein the processing circuitry is further configured to: determine the patient is not achieving RSA based on the prior expiration phase, the prior inspiration phase, and the heart rate; and adjust the rate of the cardiac pacing to more closely mimic RSA based on the determination.

[0119] Example 36. The device of any one or more of examples 34-35, wherein to adjust the cardiac pacing pulses, the processing circuitry is configured to: control the therapy delivery circuitry to increase the rate of the cardiac pacing pulses from a baseline rate to a higher rate during the subsequent inspiration phase.

[0120] Example 37. The device of any one or more of examples 34-35, wherein to adjust the cardiac pacing pulses, the processing circuitry is configured to: control the therapy delivery circuitry to increase the rate of the cardiac pacing pulses from a baseline rate to a higher rate during the subsequent inspiration phase and decrease the rate of the cardiac pacing pulses relative to the higher rate during the subsequent expiration phase.

[0121] Example 38. The device of any one or more of examples 32-37, wherein the processing circuitry is further configured to: compare an average patient heart rate to a threshold; and control the therapy delivery circuitry to adjust the cardiac pacing pulses to mimic RSA responsive to the average heart rate falling below the threshold.

[0122] Example 39. The device of any one or more of examples 32-38, wherein theEGM signal comprises a far-field EGM signal.

[0123] Example 40. The device of any one or more of examples 34-39, wherein to identify the prior inspiration phase, the processing circuitry is configured to: identify a localminimum of a respiratory signature based on the EGM signal, wherein the local minimum of the respiratory signature is indicative of the beginning of the prior inspiration phase.

[0124] Example 41. The device of any one or more of examples 32-40, wherein to identify the prior expiration phase, the processing circuitry is configured to: identify a local maximum of a respiratory signature based on the EGM signal, wherein the local maximum of the respiratory signature is indicative of the beginning of the prior expiration phase.

[0125] Example 42. The device of any one or more of examples 32-41, wherein to sense the EGM signal, the sensing circuitry is configured to: sense the EGM signal via an RV coil electrode of the device electrically coupled to a can electrode of the device; or sense the EGM signal via an RV tip electrode of the device electrically coupled to the can electrode of the device.

[0126] Example 43. The device of any one or more of examples 32-42, wherein the processing circuitry is further configured to: determine a patient state; and control the therapy delivery circuitry to adjust the rate of the cardiac pacing pulses based on the patient state.

[0127] Example 44. The device of example 43, wherein the patient state comprises one or more of: a patient disease state; or a patient activity level.

[0128] Example 45. The device of any one or more of examples 32-44, wherein the device comprises an implantable medical device (IMD).

[0129] Example 46. The device of example 45, wherein the IMD comprises a pacemaker.

[0130] Example 47. A method comprising: sensing, by sensing circuitry of a medical device of a medical device system, an electrogram (EGM) signal of a patient; and identifying, by processing circuitry of the system, a prior expiration phase based on the EGM signal; determining, by the processing circuitry, a heart rate of the patient based on the EGM signal; predicting, by the processing circuitry, a beginning of a subsequent expiration phase based on the prior expiration phase; and controlling, by the processing circuitry, therapy delivery circuitry of the medical device to adjust a rate of cardiac pacing pulses to a heart of the patient during the subsequent expiration phase based on the heart rate and the prior expiration phase.

[0131] Example 48. The method of example 47, wherein adjusting the rate of the cardiac pacing during the subsequent expiration phase comprises causing the delivery of the cardiac pacing pulses to more closely mimic respiratory sinus arrhythmia (RSA).

[0132] Example 49. The method of any one or more of examples 47-48, wherein the processing circuitry is further configured to: identifying, by the processing circuitry, aprior inspiration phase based on the EGM signal; predicting, by the processing circuitry, a beginning of a subsequent inspiration phase based on at least the prior inspiration phase; and controlling, by the processing circuitry, the therapy delivery circuitry to adjust the rate of the cardiac pacing during the subsequent expiration phase and the subsequent inspiration phase based on the heart rate, the prior expiration phase, and the prior inspiration phase.

[0133] Example 50. The method of example 49, further comprising: determining, by the processing circuitry, the patient is not achieving RSA based on the prior expiration phase, the prior inspiration phase, and the heart rate; and adjusting, by the processing circuitry, the rate of the cardiac pacing to more closely mimic RSA based on the determination.

[0134] Example 51. The method of any one or more of examples 49-50, wherein adjusting the cardiac pacing pulses comprises: controlling, by the processing circuitry, the therapy delivery circuitry to increase the rate of the cardiac pacing pulses from a baseline rate to a higher rate during the subsequent inspiration phase.

[0135] Example 52. The method of any one or more of examples 49-50, wherein adjusting the cardiac pacing pulses comprises: controlling, by the processing circuitry, the therapy delivery circuitry to increase the rate of the cardiac pacing pulses from a baseline rate to a higher rate during the subsequent inspiration phase and decrease the rate of the cardiac pacing pulses from a baseline rate to a lower rate during the subsequent expiration phase.

[0136] Example 53. The method of any one or more of examples 47-52, further comprising: comparing, by the processing circuitry, an average patient heart rate to a threshold; and controlling, by the processing circuitry, the therapy delivery circuitry to adjust the cardiac pacing pulses to mimic RSA responsive to the average heart rate falling below the threshold.

[0137] Example 54. The method of any one or more of examples 47-53, wherein the EGM signal comprises a far-field EGM signal.

[0138] Example 55. The method of any one or more of examples 49-54, wherein identifying the prior inspiration phase comprises: identifying, by the processing circuitry, a local minimum of a respiratory signature based on the EGM signal, wherein the local minimum of the respiratory signature is indicative of the beginning of the prior inspiration phase.

[0139] Example 56. The method of any one or more of examples 47-55, wherein identifying the prior expiration phase comprises: identifying, by the processing circuitry, a local maximum of a respiratory signature based on the EGM signal, wherein the localmaximum of the respiratory signature is indicative of the beginning of the prior expiration phase.

[0140] Example 57. The method of any one or more of examples 47-56, wherein sensing the EGM signal comprises: sensing, by the sensing circuitry, the EGM signal via an RV coil electrode of the device electrically coupled to a can electrode of the device; or sensing, by the sensing circuitry, the EGM signal via an RV tip electrode of the device electrically coupled to the can electrode of the device.

[0141] Example 58. The method of any one or more of examples 47-57, further comprising: determining, by the processing circuitry, a patient state; and controlling, by the processing circuitry, the therapy delivery circuitry to adjust the rate of the cardiac pacing pulses based on the patient state.

[0142] Example 59. The method of example 58, wherein the patient state comprises one or more of: a patient disease state; or a patient activity level.

[0143] Example 60. The method of any one or more of examples 47-59, wherein the medical device comprises an implantable medical device (IMD).

[0144] Example 61. The method of example 60, wherein the IMD comprises a pacemaker.

[0145] Example 62. A non-transitory computer-readable storage medium storing instructions that, when executed by processing circuitry, cause the processing circuitry to: control sensing circuitry to sense an electrogram (EGM) signal of a patient; identify a prior expiration phase based on the EGM signal; determine a heart rate of the patient based on the EGM signal; predict a beginning of a subsequent expiration phase based on the prior expiration phase; and control therapy delivery circuitry to adjust a rate of cardiac pacing during the subsequent expiration phase based on the heart rate and the prior expiration phase.

[0146] Various examples have been described. These and other examples are within the scope of the following claims.

Claims

WHAT IS CLAIMED IS:

1. A device comprising: therapy delivery circuitry configured to deliver cardiac pacing pulses to a heart of a patient via a plurality of electrodes; sensing circuitry configured to sense an electrogram (EGM) signal of a patient; and processing circuitry configured to: identify a prior inspiration phase based on the EGM signal; determine a heart rate of the patient based on the EGM signal; predict a beginning of a subsequent inspiration phase based on the prior inspiration phase; and control the therapy delivery circuitry to adjust a rate of the cardiac pacing pulses during the subsequent inspiration phase based on the heart rate and the prior inspiration phase.

2. The device of claim 1, wherein to adjust the rate of the cardiac pacing pulses during the subsequent inspiration phase, the processing circuitry causes the therapy delivery circuitry to deliver the cardiac pacing pulses to more closely mimic respiratory sinus arrhythmia (RSA).

3. The device of any one or more of claims 1-2, wherein the processing circuitry is further configured to: identify a prior expiration phase based on the EGM signal; predict a beginning of a subsequent expiration phase based on at least the prior expiration phase; and control the therapy delivery circuitry to adjust the rate of the cardiac pacing pulses during the subsequent inspiration phase and the subsequent expiration phase based on the heart rate, the prior inspiration phase, and the prior expiration phase.

4. The device of claim 3, wherein the processing circuitry is further configured to: determine the patient is not achieving RSA based on the prior inspiration phase, the prior expiration phase, and the heart rate; and adjust the rate of the cardiac pacing pulses to more closely mimic RSA based on the determination.

5. The device of any one or more of claims 1-4, wherein to adjust the cardiac pacing pulses, the processing circuitry is configured to: control the therapy delivery circuitry to increase the rate of the cardiac pacing pulses from a baseline rate to a higher rate during the subsequent inspiration phase.

6. The device of any one or more of claims 3-4, wherein to adjust the cardiac pacing pulses, the processing circuitry is configured to: control the therapy delivery circuitry to increase the rate of the cardiac pacing pulses from a baseline rate to a higher rate during the subsequent inspiration phase and decrease the rate of the cardiac pacing pulses relative to the higher rate during the subsequent expiration phase.

7. The device of any one or more of claims 1-6, wherein the processing circuitry is further configured to: compare an average patient heart rate to a threshold; and control the therapy delivery circuitry to adjust the cardiac pacing pulses to mimic RSA responsive to the average heart rate falling below the threshold.

8. The device of any one or more of claims 1-7, wherein the EGM signal comprises a far-field EGM signal.

9. The device of any one or more of claims 1-8, wherein to identify the prior inspiration phase, the processing circuitry is configured to: identify a local minimum of a respiratory signature based on the EGM signal, wherein the local minimum of the respiratory signature is indicative of the beginning of the prior inspiration phase.

10. The device of any one or more of claims 3-9, wherein to identify the prior expiration phase, the processing circuitry is configured to: identify a local maximum of a respiratory signature based on the EGM signal, wherein the local maximum of the respiratory signature is indicative of the beginning of the prior expiration phase.

11. The device of any one or more of claims 1-10, wherein to sense the EGM signal, the sensing circuitry is configured to: sense the EGM signal via an RV coil electrode of the device electrically coupled to a can electrode of the device; or sense the EGM signal via an RV tip electrode of the device electrically coupled to the can electrode of the device.

12. The device of any one or more of claims 1-11, wherein the processing circuitry is further configured to: determine a patient state; and control the therapy delivery circuitry to adjust the rate of the cardiac pacing pulses based on the patient state.

13. The device of claim 12, wherein the patient state comprises one or more of: a patient disease state; or a patient activity level.

14. The device of any one or more of claims 1-13, wherein the device comprises an implantable medical device (IMD).

15. The device of claim 14, wherein the IMD comprises a pacemaker.

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