Respiratory phase pacing based on tracking respiration with electrograms

Abstract

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

Description

[0001] Cross-related applications

[0002] This application claims the benefit of U.S. Provisional Patent Application Serial No. 63 / 568,269, filed March 21, 2024, the entire contents of which are incorporated herein by reference. Technical Field

[0003] This disclosure relates in general to medical devices, and more specifically to medical devices for delivering cardiac treatment. Background Technology

[0004] In healthy individuals, heart rate naturally increases during inhalation and decreases during exhalation. This phenomenon, known as respiratory sinus arrhythmia (RSA), supports ventilation / perfusion matching when blood enters the lungs, i.e., increased pulmonary blood flow when the lungs are inflated. Summary of the Invention

[0005] Generally, this disclosure describes techniques for delivering cardiac pacing to restore RSA, such as by increasing the cardiac pacing pulse rate during inspiration and, in some examples, decreasing the pulse rate during expiration. Many current pacemakers monotonically pace in view of lung inspiration / expiration, and the monotonic pacing rate increases with increasing lung activity (e.g., increases with increasing respiratory rate but does not change within the respiratory cycle).

[0006] Cardiac pacing that restores RSA (i.e., respiratory phase pacing) can provide therapeutic benefits, such as by increasing cardiac output and helping to reverse cardiac remodeling in patients with heart failure (HF). However, current procedures for restoring RSA are based on several averaged previously detected inspiratory and expiratory phases based on identified previous respiratory cycles. These inspiratory and expiratory phases mimic RSA when the patient is breathing at a steady rate (e.g., when 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).

[0007] The technology disclosed herein can be implemented by a cardiac treatment device (e.g., a pacemaker) that continuously senses and independently detects physiological signals indicative of inspiratory and expiratory phases. In other words, the pacemaker can identify inspiratory and expiratory phases without first identifying the respiratory cycle. The pacemaker can be configured to predict subsequent (e.g., immediately following) inspiratory and / or expiratory phases in a patient based on detected inspiratory and / or expiratory phases, and control treatment delivery circuitry to adjust the cardiac pacing pulses. By continuously monitoring inspiratory and / or expiratory phases and predicting subsequent inspiratory and / or expiratory phases based on previous inspiratory and / or expiratory phases, the technology disclosed herein improves RSA pacing. In some examples, the pacemaker can continuously update the predicted subsequent inspiratory and expiratory phases based on the accuracy of previous predictions.

[0008] In some instances, under certain conditions, such as when the patient has reached RSA or when the patient's heart rate exceeds a threshold, RSA pacing may be unnecessary, ineffective, or counterproductive. The techniques disclosed herein can avoid delivering RSA pacing under such conditions by determining, based on one or more sensed patient parameters, whether one or more criteria for adjusting cardiac pacing for simulation are met.

[0009] In some examples, the techniques disclosed herein may additionally include further adjustments to cardiac pacing based on patient status, for example, the pacemaker may increase or overdrive cardiac pacing pulses to a lesser extent for patients in one category compared to patients in different categories.

[0010] In one example, an apparatus includes: a treatment delivery circuit configured to deliver cardiac pacing pulses to a patient's heart via a plurality of electrodes; a sensing circuit configured to sense an electrogram (EGM) signal from the patient; and a processing circuit configured to: identify a previous inspiratory phase based on the EGM signal; determine the patient's heart rate based on the EGM signal; predict the onset of a subsequent inspiratory phase based on the previous inspiratory phase; and control the treatment delivery circuit to adjust the rate of cardiac pacing during the subsequent inspiratory phase based on the heart rate and the previous inspiratory phase.

[0011] In another example, a method includes: sensing an electrogram (EGM) signal of a patient by sensing circuitry of a medical device system; identifying a previous inspiratory phase by processing circuitry of the system based on the EGM signal; determining a heart rate by processing circuitry based on the EGM signal; predicting the start of a subsequent inspiratory phase by processing circuitry based on the previous inspiratory phase; and controlling a therapeutic delivery circuitry of the medical device to adjust the rate of cardiac pacing pulses delivered to the patient's heart during the subsequent inspiratory phase by processing circuitry based on the heart rate and the previous inspiratory phase.

[0012] 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 electrophysiological (EGM) signal from a patient; identify a previous inspiratory phase based on the EGM signal; determine the patient's heart rate based on the EGM signal; predict the start of a subsequent inspiratory phase based on the previous inspiratory phase; and control treatment delivery circuitry to adjust the rate of cardiac pacing during the subsequent inspiratory phase based on the heart rate and the previous inspiratory phase.

[0013] In another example, an apparatus includes: a treatment delivery circuit configured to deliver cardiac pacing pulses to a patient's heart via a plurality of electrodes; a sensing circuit configured to sense an electrogram (EGM) signal from the patient; and a processing circuit configured to: identify a previous expiratory phase based on the EGM signal; determine the patient's heart rate based on the EGM signal; predict the onset of a subsequent expiratory phase based on the previous expiratory phase; and control the treatment delivery circuit to adjust the rate of cardiac pacing during the subsequent expiratory phase based on the heart rate and the previous expiratory phase.

[0014] In another example, a method includes: sensing an electrogram (EGM) signal of a patient by sensing circuitry of a medical device system; identifying a previous expiratory phase by processing circuitry of the system based on the EGM signal; determining a heart rate by processing circuitry based on the EGM signal; predicting the start of a subsequent expiratory phase by processing circuitry based on the previous expiratory phase; and controlling a treatment delivery circuitry of the medical device to adjust the rate of cardiac pacing pulses delivered to the patient's heart during the subsequent expiratory phase by processing circuitry based on the heart rate and the previous expiratory phase.

[0015] 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 electrophysiological (EGM) signal from the patient; identify a previous expiratory phase based on the EGM signal; determine the patient's heart rate based on the EGM signal; predict the onset of a subsequent expiratory phase based on the previous expiratory phase; and control treatment delivery circuitry to adjust the rate of cardiac pacing during the subsequent expiratory phase based on the heart rate and the previous expiratory phase.

[0016] The present invention is intended to provide an overview of the subject matter described herein. It is not intended to provide an exclusive or exhaustive interpretation of the devices and methods described in detail in the following drawings and description. Further details of one or more examples are set forth in the following drawings and description. Attached Figure Description

[0017] Figure 1This is a conceptual diagram illustrating an example system configured to deliver cardiac pacing to simulate respiratory sinus arrhythmia (RSA) according to one or more technologies of this disclosure, the system including an implantable medical device (IMD) coupled to an implantable medical lead.

[0018] Figure 2 This illustrates the integration of one or more technologies according to this disclosure with the heart. Figure 1 A conceptual diagram of an example IMD and its lead wires.

[0019] Figure 3 This illustrates one or more technologies according to this disclosure. Figure 1 A functional block diagram of an example configuration for an IMD.

[0020] Figure 4 This is a flowchart illustrating an example operation of a device for adjusting the rate of cardiac pacing to simulate RSA according to one or more techniques of this disclosure.

[0021] Figure 5 This is a flowchart illustrating example operation of a device for determining whether to adjust the rate of cardiac pacing to simulate RSA, according to one or more techniques of this disclosure.

[0022] Figure 6 This is a flowchart illustrating an example operation of determining whether to adjust cardiac pacing to simulate RSA based on patient heart rate information, according to one or more techniques of this disclosure.

[0023] Figure 7 This is a graph illustrating an example EGM signal with information on the inspiratory and expiratory phases, which can be identified according to one or more techniques disclosed herein.

[0024] Figure 8 This is a flowchart illustrating an example operation of adjusting cardiac pacing based on patient condition according to one or more techniques of this disclosure.

[0025] Throughout the accompanying drawings and description, similar reference numerals refer to similar elements. Detailed Implementation

[0026] Various types of implantable and external devices are configured to monitor health based on sensed physiological signals. External devices that can be used for non-invasive sensing and monitoring of physiological signals include wearable devices with electrodes configured to contact a patient's skin, such as patches, watches, rings, necklaces, hearing aids, wearable cardiac monitors or automated external defibrillators (AEDs), clothing, car seats, or bed sheets. Such medical devices facilitate relatively long-term monitoring of a patient's health during normal daily activities.

[0027] Implantable medical devices (IMDs) also sense and monitor physiological signals and detect health events such as arrhythmias, cardiac arrest, myocardial infarction, stroke, and epileptic seizures. Example IMDs include pacemakers and implantable cardioverter defibrillators that can be coupled to intravascular or extravascular leads; and pacemakers with a shell configured for implantation within the heart, which can be leadless, such as Medtronic's Micra. ™ Leadless pacing devices. Pacemakers deliver pacing pulses to patients based on monitored physiological signals.

[0028] Many current pacemakers monotonically pace based on lung inspiration / expiration, and the monotonous pacing rate increases with activity levels (e.g., many current pacemakers provide constant pacing throughout the respiratory cycle). Cardiac pacing that mimics RSA (i.e., respiratory phase pacing) can provide therapeutic benefits, such as by increasing cardiac output and helping to reverse cardiac remodeling in patients with heart failure (HF) and / or improving quality of life / functional capacity. However, current procedures for restoring RSA are based on several previously detected, averaged inspiratory and expiratory phases based on the identified respiratory cycle. These inspiratory and expiratory phases mimic RSA when the patient is breathing at a steady rate (e.g., when 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).

[0029] The techniques disclosed herein can be implemented by a cardiac treatment device (e.g., a pacemaker) that continuously senses physiological signals (e.g., electrogrammography (EGM) signals) indicating the inspiratory and expiratory phases, and detects the inspiratory and expiratory phases independently. In other words, the pacemaker can identify the inspiratory and expiratory phases without first identifying the respiratory cycle. In some examples, the pacemaker can control the treatment delivery circuitry to adjust the cardiac pacing pulse based on the inspiratory and / or expiratory phases. By continuously monitoring the inspiratory and / or expiratory phases and adjusting the cardiac pacing pulse stepwise based on the inspiratory and / or expiratory phases immediately following them, the techniques disclosed herein improve RSA pacing accuracy. Therefore, patients can receive cardiac pacing that more closely mimics RSA, which can improve patient outcomes.

[0030] Under certain conditions, such as when a patient has reached an RSA or when a patient's heart rate exceeds a threshold, RSA pacing may be unnecessary, ineffective, or counterproductive. The techniques disclosed herein can avoid delivering RSA pacing under such conditions by determining, based on one or more sensed patient parameters, whether one or more criteria for adjusting cardiac pacing to simulate RSA are met. In this way, the techniques described herein can advantageously improve the operation of devices that deliver cardiac pacing to simulate RSA, for example, delivering such pacing when it is likely to be effective and avoiding the delivery of counterproductive treatments, thereby benefiting the patient.

[0031] In some examples, the techniques of this disclosure may additionally include further adjustments to cardiac pacing based on patient status. For example, the pacemaker may, based on patient status, slightly increase or overdrive the cardiac pacing pulse for patients in one category compared to patients in different categories. By adjusting cardiac pacing based on patient status, the techniques of this disclosure can improve the accuracy of respiratory pacing, which can improve patient outcomes.

[0032] The technology disclosed herein additionally includes: predicting the patient's subsequent (e.g., immediately following) inspiratory and / or expiratory phases based on previously detected inspiratory and / or expiratory phases, and controlling the treatment delivery circuitry to adjust the cardiac pacing pulses. Therefore, the patient can receive cardiac pacing that more closely mimics RSA, which can improve patient outcomes.

[0033] Figure 1 This is a conceptual diagram illustrating an example system 10 configured to deliver cardiac pacing in a patient 14 to simulate respiratory sinus arrhythmia (RSA) according to the technology of this disclosure. Figure 1 In this example, system 10 includes an implantable medical device (IMD) 16 and an external device 24, the IMD being coupled to leads 18, 20, and 22. The IMD 16 may be an implantable pacemaker, cardioverter-defibrillator, and / or defibrillator that provides electrical signals to the heart 12, for example, via electrodes coupled to one or more of leads 18, 20, and 22. Patient 14 is typically, but not necessarily, a human patient.

[0034] exist Figure 1 In the example, leads 18, 20, and 22 extend into the heart 12 of the patient 14 to sense the electrical activity of the heart 12 (e.g., one or more electrocardiogram (EGM) signals) and / or deliver electrical stimulation to the heart 12. Leads 18, 20, and 22 can also be used to detect impedance indicative of fluid volume in the patient 14 and the patient 14's respiration. In addition to impedance, the respiratory signal can also exist as a component of the cardiac EGM signal.

[0035] exist Figure 1In the example shown, the right ventricle (RV) lead 18 extends through one or more veins (not shown), the superior vena cava (not shown), and the right atrium 26, and enters the right ventricle 28. The left ventricle (LV) coronary sinus lead 20 extends through one or more veins, the vena cava, and the right atrium 26, and enters the coronary sinus 30, reaching the region adjacent to the free wall of the left ventricle 32 of the heart 12. The right atrium (RA) lead 22 extends through one or more veins and the vena cava, and enters the right atrium 26 of the heart 12.

[0036] The illustrated number and location of leads 18, 20, and 22 are examples. In other examples, IMD 16 may be coupled to one, two, or more than three leads extending to various locations. In some examples, system 10 may additionally or alternatively include one or more leads or one or more lead segments extending into the vena cava or other veins to deploy one or more electrodes. Figure 1 (Not shown in the image). Additionally, in some examples, system 10 may additionally or alternatively include an external vascular lead with electrodes implanted outside the heart 12, as an alternative to or supplement to transvenous, internal cardiac leads 18, 20, and 22. Such leads can 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, commercially available from Medtronic. ™ A pacemaker, as an alternative to or supplement to the IMD16. One or more leadless pacemakers may be configured to deliver cardiac pacing in RSA mode as described herein with respect to the IMD16. Additionally, an external medical device may be configured to deliver cardiac pacing in RSA mode as described herein with respect to the IMD16. In some examples, the technology of the present invention may be implemented by a system comprising two or more devices communicating with each other. For example, a first device (such as an implantable monitoring device, e.g., the Reveal LINQ, commercially available from Medtronic). ™ An insertable cardiac monitor can monitor the patient's 14 inhalation and / or exhalation, and adjust the pacing therapy delivered by the second device based on the monitoring.

[0037] IMD 16 can be connected via an electrode coupled to at least one of leads 18, 20, and 22. Figure 1(Not shown) to sense electrical signals accompanying depolarization and repolarization of the heart 12. In some examples, the IMD 16 delivers pacing pulses to the heart 12 based on the electrical signals sensed within the heart 12. The electrodes of the IMD 16 used for sensing and pacing can be configured as unipolar or bipolar. In some examples, the IMD 16 can deliver cardiac pacing to provide cardiac resynchronization therapy (CRT). In some examples, the IMD 16 can be additionally or alternatively configured to provide conduction system pacing, which can provide more physiological activation of the heart 12 than conventional pacing. In such examples, leads 18, 20, 22 can be configured / positioned such that their electrodes enter (are able to stimulate) the heart's conduction system, such as the His bundle, left bundle branch, or right bundle branch.

[0038] The IMD 16 can detect arrhythmias of the heart 12, such as tachycardia or fibrillation of the atria 26 and 36 and / or ventricles 28 and 32, and can also provide defibrillation therapy and / or cardioversion therapy via electrodes located on at least one of leads 18, 20, 22. In some examples, the IMD 16 can be programmed to deliver a treatment process, such as pulses of increasing energy levels, until the fibrillation of the heart 12 stops. The IMD 16 can detect fibrillation using one or more fibrillation detection techniques known in the art.

[0039] The IMD 16 can generate an EGM signal using two of any of the electrodes carried on leads 18, 20, and 22. In some examples, the IMD 16 can also use the housing electrodes (not shown) of the IMD 16 to generate an EGM signal and monitor cardiac activity. While these EGM signals can be used to monitor for potential arrhythmias and other conditions of the heart 12 for treatment, the EGM signals can also be used to monitor the condition of the heart 12. For example, the IMD 16 can monitor heart rate, heart rate variability, blood flow parameters, or other indicators of the heart 12's ability to pump blood or the progression of heart failure (HF).

[0040] In some examples, the IMD 16 can also use any two electrodes or housing electrodes of leads 18, 20, and 22 to sense the impedance of patient 14. As the fluid content within the pleural cavity of patient 14 increases, the impedance between the two electrodes may also change. The IMD 16 can use this impedance to create a fluid index. As the fluid index increases, more fluid may be more likely to remain in patient 14, and the heart 12 may be stressed to keep up with the movement of a larger amount of fluid.

[0041] IMD 16 can communicate with external device 24. In some examples, external device 24 includes a handheld computing device, a computer workstation, or a networked computing device. External device 24 can be configured to retrieve data from IMD 16, such as data for presentation to clinicians or other users, including sensed parameter data of patient 14 and data on the operation of IMD 16. In some examples, external device 24 can provide the retrieved data to a cloud computing system (such as CareLink, available from Medtronic). ™ The system (cloud computing system) can analyze data and provide reports of the analysis and / or data to clinicians or other users. In some examples, clinicians or other users can also interact with external devices 24 to program IMD 16, for example, to select values ​​for the operating parameters of IMD 16. Although the user is usually a clinician, in some examples the user may be a patient 14.

[0042] In some examples, the IMD 16, external device 24, or cloud computing system may determine HF metrics or other patient status information based on patient parameter data collected by the IMD 16. In some examples, the IMD 16, external device 24, or cloud computing system may determine, for example, the HF risk level based on HF risk metrics. For example, the risk level may be determined based on a predetermined number of metrics exceeding their representative threshold or a weighted score of each patient metric among patient metrics exceeding one or more thresholds. Additionally or alternatively, the risk level may be determined using the value or stratified status of each automatically detected patient metric, via a Bayesian belief network or other probabilistic techniques. For example, a Bayesian belief network may be applied to the value of a patient metric to determine the risk level, such as the probability that patient 14 will be hospitalized due to HF.

[0043] IMD 16 can identify each HF metric in the HF metric and store them within the IMD for later transmission. For example, patient metrics may include two or more of the following: pleural fluid index, duration of atrial fibrillation, ventricular systolic rate during atrial fibrillation, patient activity, nocturnal heart rate, heart rate variability, CRT percentage (e.g., the percentage of cardiac cycles providing CRT pacing), or the occurrence or number of therapeutic shocks.

[0044] The IMD 16 and external device 24 can communicate wirelessly using any technology known in the art. Examples of communication technologies may include, for example, radio frequency (RF) telemetry or Bluetooth. ® While communication protocols exist, other communication technologies such as magnetic coupling can also be considered.

[0045] The IMD 16 is an example of a device configured to deliver cardiac pacing pulses to a patient’s heart via multiple electrodes, sense the patient’s EGM, determine the patient’s heart rate, identify the inspiratory and / or expiratory phases, predict the subsequent onset of the inspiratory and / or expiratory phases, and adjust the cardiac pacing pulses based on the heart rate and the inspiratory and / or expiratory phases during the inspiratory and / or expiratory phases.

[0046] Figure 2 This is a conceptual diagram showing the IMD 16 and leads 18, 20, and 22 of system 10 in more detail. (See diagram below.) Figure 2 As shown, IMD 16 is coupled to leads 18, 20, and 22. Leads 18, 20, and 22 can be electrically coupled to the therapeutic delivery circuitry and sensing circuitry of IMD 16 via connector block 34. In some examples, the proximal ends of leads 18, 20, and 22 may include electrical contacts electrically coupled to corresponding electrical contacts within connector block 34 of IMD 16. Alternatively, in some examples, leads 18, 20, and 22 can be mechanically coupled to connector block 34 by means of a retaining screw, connecting pin, snap-fit ​​connector, or other suitable mechanical coupling mechanism.

[0047] Each of leads 18, 20, and 22 comprises an elongated, insulated lead body capable of carrying several concentric coiled conductors separated from each other by a tubular insulating sheath. Bipolar electrodes 40 and 42 are positioned adjacent to the distal end of lead 18 in the right ventricle 28. Additionally, bipolar electrodes 44 and 46 are positioned adjacent to the distal end of lead 20 in the coronary 30, and bipolar electrodes 48 and 50 are positioned adjacent to the distal end of lead 22 in the right atrium 26. In the illustrated example, no electrode is present in the left atrium 33. However, other examples may include electrodes in the left atrium 33. Furthermore, in an example where IMD 16 is configured to deliver conduction system pacing, lead 18 may be configured / positioned adjacent to... Figure 2 The differences shown allow electrode 42 to stimulate the conduction system, such as the His bundle, the left bundle branch, or the right bundle branch. For example, electrode 42 can be positioned on or within the interventricular septum.

[0048] Electrodes 40, 44, and 48 may be in the form of ring electrodes, and electrodes 42, 46, and 50 may be in the form of fixed and / or extendable spiral-tipped electrodes respectively mounted to insulated electrode heads 52, 54, and 56. In other examples, one or more of electrodes 42, 46, and 50 may be in the form of small circular electrodes at the tip of tin-plated leads or other fixing elements. Leads 18, 20, and 22 also include elongated electrodes 62, 64, and 66 respectively, which may be in the form of coils. Each of electrodes 40, 42, 44, 46, 48, 50, 62, 64, and 66 may be electrically coupled to a corresponding coil conductor within the lead body of its associated lead 18, 20, and 22, and thereby coupled to a corresponding electrical contact on the proximal end of leads 18, 20, and 22.

[0049] In some examples, such as Figure 2 As shown, the IMD 16 includes one or more housing electrodes, such as housing electrode 58, which may be integrally formed with or otherwise coupled to the outer surface of the hermetically sealed housing 60 of the IMD 16. In some examples, housing electrode 58 is defined by an uninsulated portion of the outward-facing part of the housing 60 of the IMD 16. Other divisions between the insulated and uninsulated portions of the housing 60 may be used to define two or more housing electrodes. In some examples, housing electrode 58 substantially encompasses the entire housing 60. (See reference...) Figure 3 In further detail, the housing 60 may encapsulate therapeutic 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 the heart 12 and other patient parameters.

[0050] The IMD 16 can sense electrical signals associated with the depolarization and repolarization of the heart 12 via electrodes 40, 42, 44, 46, 48, 50, 62, 64, and 66. These electrical signals are conducted from the electrodes to the IMD 16 via corresponding leads 18, 20, and 22. The IMD 16 can sense such electrical signals via any bipolar combination of electrodes 40, 42, 44, 46, 48, 50, 62, 64, and 66. Furthermore, any of electrodes 40, 42, 44, 46, 48, 50, 62, 64, and 66 can be combined with housing electrode 58 for unipolar sensing. The combination of electrodes used for sensing may be referred to as a sensing configuration or electrode vector.

[0051] In some examples, the IMD 16 delivers pacing pulses via a bipolar combination of electrodes 40, 42, 44, 46, 48, and 50 to generate depolarization of cardiac tissue in the heart 12. In some examples, the IMD 16 delivers pacing pulses via any of electrodes 40, 42, 44, 46, 48, and 50 in combination with a unipolar housing electrode 58. Furthermore, the IMD 16 may deliver defibrillation pulses to the heart 12 via any combination of elongated electrodes 62, 64, and 66 and housing electrode 58. Electrodes 58, 62, 64, and 66 may also be used to deliver cardioversion pulses to the heart 12. Electrodes 62, 64, and 66 may be made of any suitable conductive material, such as, but not limited to, platinum, platinum alloys, or other materials known to be suitable for use in implantable defibrillation electrodes. The electrodes used for delivery of therapy or sensing, their associated conductors and connectors, and any combination of tissue or fluid between the electrodes define the electrical path.

[0052] In some examples, the IMD 16 can sense far-field EGM signals via coil electrodes 62 and housing electrodes 58 located in RV 28. Additionally or alternatively, the IMD 16 can sense EGM signals via tip electrodes 42 and housing electrodes 58. Other EGM signal sensing configurations are also possible.

[0053] In addition to the EGM signal, any of electrodes 40, 42, 44, 46, 48, 50, 62, 64, 66, and 58 can be used to sense non-cardiac signals. For example, two or more electrodes can be used to measure, for instance, the intrathoracic impedance of patient 14. This impedance can be used to generate a fluid patient measure indicating the amount of fluid accumulating in patient 14. Since a larger fluid volume may indicate an increased pumping load on the heart 12, the fluid index can be used as an indicator of HF risk level. IMD 16 can periodically measure intrathoracic impedance to identify trends in the fluid index during patient monitoring over days, weeks, months, or even years.

[0054] In some examples, the two electrodes used to measure intrathoracic impedance may be located at two different locations within the chest of patient 14. For example, coil electrode 62 and housing electrode 58 can be used as sensing vectors for intrathoracic impedance because electrode 62 is located within RV28 and housing electrode 58 is located at the implantation site of IMD 16, which is typically in the upper chest region. However, other electrodes spanning multiple organs or tissues of patient 14 may also be used, such as additional implanted electrodes solely for measuring thoracic impedance.

[0055] Figure 3This is a functional block diagram illustrating an exemplary configuration of IMD 16. In the illustrated example, IMD 16 includes processing circuitry 80, sensing circuitry 82, one or more sensors 84, therapeutic 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 herein to IMD 16 and processing circuitry 80. Memory 90 may include any volatile, non-volatile, magnetic, optical, or electrical medium, such as 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 medium.

[0056] Processing circuitry 80 may include any or more of a microprocessor, controller, digital signal processor (DSP), application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), or equivalent discrete or analog logic circuitry. In some examples, processing circuitry 80 may include multiple components, such as one or more microprocessors, one or more controllers, one or more DSPs, one or more ASICs, or one or more FPGAs, and any combination of other discrete or integrated logic circuitry. The functionality attributed herein to processing circuitry 80 may be embodied in software, firmware, hardware, or any combination thereof, for example, in software or firmware executed on the processing circuitry.

[0057] Processing circuitry 80 controls treatment delivery circuitry 86 to deliver treatment to heart 12 according to treatment parameters and procedures that can be stored in memory 90. An example of treatment parameters stored in memory 90 is RSA pacing parameters 96 for delivering cardiac pacing. RSA pacing parameters 96 may include timing and duration parameters, such as increasing and / or decreasing the rate of cardiac pacing pulses to simulate the duration of RSA. Treatment delivery circuitry 86 is electrically coupled to electrodes 40, 42, 44, 46, 48, 50, 58, 62, 64, and 66, for example, via conductors of corresponding leads 18, 20, 22, or, in the case of housing electrodes 58, via electrical conductors disposed within housing 60 of IMD 16. In the illustrated example, treatment delivery circuitry 86 is configured to generate and deliver electrical therapy to heart 12. For example, treatment delivery circuitry 86 may deliver defibrillation shocks to heart 12 via at least two electrodes 58, 62, 64, 66. The therapeutic delivery circuit 86 can deliver pacing pulses via ring electrodes 40, 44, 48 and / or helical electrodes 42, 46 and 50 of leads 18, 20 and 22, respectively. In some examples, the therapeutic delivery circuit 86 delivers pacing, cardioversion, or defibrillation stimulation in the form of electrical pulses. In other examples, the therapeutic delivery circuit 86 can 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.

[0058] The treatment delivery circuit 86 includes circuitry such as a charge pump, capacitor, current mirror, or other signal generation circuitry for generating pulses or other signals. The treatment delivery circuit 86 may include a switching module, and the processing circuitry 80 may use the switching module to select, for example via a data / address bus, which of the available electrodes is used to deliver a defibrillation shock or pacing pulse. The switching module may include a switch array, switch matrix, multiplexer, or any other type of switching device suitable for selectively coupling stimulation energy to the selected electrode.

[0059] Sensing circuit 82 monitors signals from at least one of electrodes 40, 42, 44, 46, 48, 50, 58, 62, 64, or 66 to monitor the EGM signal of the heart and / or the electrical activity, impedance, respiration, or other patient parameters of the heart 12, the values ​​of which can be stored in memory 90 as patient parameter data 92. Sensing can be performed to detect inherent cardiac depolarization, determine heart rate or heart rate variability, or detect arrhythmias or other electrical signals. Sensing circuit 82 may include one or more filters, amplifiers, analog-to-digital converters, or other sensing circuitry.

[0060] The sensing circuit 82 may also include a switching module to select which of the available electrodes to use for sensing cardiac activity based on which electrode combination or electrode vector is used in the current sensing configuration. In some examples, the processing circuit 80 may select the electrodes to be used as sensing electrodes via the switching module within the sensing circuit 82, i.e., select the sensing configuration. The sensing circuit 82 may include one or more detection channels, each of which may be coupled to the selected electrode configuration for detecting cardiac signals via the electrode configuration. Some detection channels may be configured to detect cardiac events, such as P waves or R waves, and provide indication of the occurrence of such events to the processing circuit 80.

[0061] Processing circuit 80 can be configured to identify the patient's inspiratory and / or expiratory phases based on the EGM signal. To identify the inspiratory and / or expiratory phases, processing circuit 80 can detect peaks and troughs in the respiratory characteristics of the EGM signal, for example, by identifying the zero-slope point (a zero-crossing point in the derivative or differential of the signal), the point where the slope of the EGM's respiratory characteristics reverses sign (e.g., from negative to positive for troughs and from positive to negative for peaks), or using any other peak / trough detection technique to identify the maximum or minimum value of the signal. Processing circuit 80 can define the expiratory phase as the interval or window from the identified peak to the subsequent trough, and the inspiratory phase as the interval or window from the identified trough to the subsequent peak. Processing circuit 80 can determine respiratory effort based on one or more of the peak-to-trough amplitude or slope of the signal within the inspiratory phase. Processing circuit 80 can determine tidal volume based on the area under the curve during the respiratory cycle. In some examples, the processing circuit 80 can determine the tidal volume based on the peak-to-trough amplitude, which can vary with the tidal volume.

[0062] One or more sensors 84 may include, for example, one or more accelerometers, microphones, temperature sensors, or optical sensors, configured to provide signals or data representing one or more patient parameters to processing circuitry 80 via sensing circuitry 82. In some examples, processing circuitry 80 may determine the posture and / or activity level of patient 14 based on signals from one or more accelerometers. In some examples, processing circuitry 80 may determine respiratory information based on signals from one or more sensors 84. For example, processing circuitry 80 may determine respiratory information based on accelerometer signals. In some examples, processing circuitry 80 may determine respiratory information based on accelerometer signals and EGM. In other examples, processing circuitry 80 may use accelerometer signals instead of EGM.

[0063] Processing circuitry 80 implements a programmable counter that controls the basic time intervals associated with DDD, VVI, DVI, VDD, AAI, DDI, DDDR, VVIR, DVIR, VDDR, AAIR, DDIR, CRT, and other pacing modes. The intervals defined by processing circuitry 80 may include atrial and ventricular pacing escape intervals, AV intervals, VV intervals, and the refractory periods of sensed P and R waves that are ineffective in timing the restart interval. The duration of these intervals can be determined by processing circuitry 80 in response to data stored in memory 90.

[0064] In some examples, processing circuitry 80 may modify the escape interval based on a rate-response pacing pattern. Processing circuitry 80 may determine a sensor-indicated pacing rate based on parameters of the sensed patient 14, such as activity level or respiratory rate, and thereby modify the escape interval and pacing rate to provide cardiac pacing to support the patient 14's activities. In some examples, processing circuitry 80 may additionally modify the pacing pattern based on the patient's disease state or other patient data. In some examples, processing circuitry 80 may control IMD 16 to provide CRT by controlling the 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 AV and VV intervals.

[0065] When the R-wave and P-wave are sensed using the detection channel of the sensing circuit 82, the interval counter implemented by the processing circuit 80 can be reset. In an example where the IMD 16 provides pacing, the treatment delivery circuit 86 may include pacemaker output circuitry, which is selectively coupled, for example, via a switching module to any combination of electrodes 40, 42, 44, 46, 48, 50, 58, 62, or 66 suitable for delivering bipolar or monopolar pacing pulses to one of the chambers of the heart 12. In such an example, the processing circuit 80 can reset the interval counter when pacing pulses are generated by the treatment delivery circuit 86, and thereby control the basic timing of cardiac pacing functions including anti-tachyarrhythmia pacing.

[0066] When the sensed R and P waves are reset, the count values ​​stored in the interval counter can be used by the processing circuit 80 to measure the duration of the RR, PP, PR, and RP intervals, which are measurement results that can be stored in the memory 90. The processing circuit 80 can use the counts in the interval counter to detect rapid arrhythmic events, such as atrial fibrillation (AF), atrial tachycardia (AT), ventricular fibrillation (VF), or ventricular tachycardia (VT). These intervals can also be used to detect overall heart rate, ventricular systolic rate, and heart rate variability. A portion of the memory 90 can be configured as a plurality of recycle buffers capable of holding a series of measured intervals that can be analyzed by the processing circuit 80 in response to the occurrence of pacing or sensing interruption to determine whether the patient's heart 12 is currently exhibiting atrial or ventricular rapid arrhythmia.

[0067] In some examples, processing circuitry 80 can determine that a tachyarrhythmia has occurred by identifying a shortened RR (or PP) interval length. Generally, processing circuitry 80 detects tachycardia when the interval length drops below 220 milliseconds (ms) and detects fibrillation when the interval length drops below 180 ms. These interval lengths are merely examples, and the user can define the interval length as needed, which can then be stored in memory 90. As an example, it may be necessary to detect this interval length for a specific number of consecutive cycles, for a specific percentage of cycles within a running window, or for a running average of a specific number of cardiac cycles.

[0068] When processing circuit 80 detects atrial or ventricular tachyarrhythmias based on signals from sensing circuit 82 and requires anti-tachyarrhythmia pacing, processing circuit 80 can load a timing interval for generating anti-tachyarrhythmia pacing via treatment delivery circuit 86 to control the operation of an escape interval counter therein and define a refractory period during which R-wave and P-wave detection is ineffective for restarting the escape interval counter for anti-tachyarrhythmia pacing. When processing circuit 80 detects atrial or ventricular tachyarrhythmias based on signals from sensing circuit 82 and requires cardioversion or defibrillation shock, processing circuit 80 can control the amplitude, form, and timing of the shock delivered via treatment delivery circuit 86.

[0069] The memory 90 can be configured to store various operating parameters, treatment parameters, sensed and detected data, and any other information related to the treatment and care of the patient 14. Figure 3In this example, memory 90 includes patient parameter data 92, RSA activation criteria 94, and RSA pacing parameters. Patient parameters 92 may store all data generated from the sensing and detection of patient parameters described herein, such as heart rate, inspiratory and / or expiratory phases, activity, posture, fluid index, atrial tachycardia or fibrillation burden, ventricular systolic rate during atrial fibrillation, nocturnal heart rate, the difference between nocturnal and daytime heart rates, heart rate variability, percentage of cardiac resynchronization therapy, percentage of bradyarrhythmia pacing therapy (in the ventricles and / or atria), and the number or frequency of shock events, blood pressure, right ventricular pressure, pulmonary artery pressure, patient temperature, or biomarkers such as brain natriuretic peptide (BNP), troponin, or related surrogate markers. In some examples, processing circuitry 80 may determine a HF metric based on the sensed parameter data 92 and determine a HF risk level based on the HF metric.

[0070] RSA activation criteria 94 include processing circuitry 80 that can be applied to patient parameters 92 to determine whether to adjust cardiac pacing to simulate RSA. If patient parameter data 92 meets RSA activation criteria 94, processing circuitry 80 can adjust pacing to simulate RSA. RSA activation criteria 94 can be fixed, user-programmable, or variable based on conditions determined by processing circuitry 80. To adjust cardiac pacing to simulate RSA, processing circuitry 80 controls treatment delivery circuitry 86 to deliver pacing pulses according to RSA pacing parameters 96, with an increased rate during the inspiratory phase of the respiratory cycle and, in some examples, a decreased rate during the expiratory phase of the cardiac cycle, as described herein. The increase and decrease in pacing rate can be continuous, on a successive beat or other basis.

[0071] Communication circuit 88 includes any suitable hardware, firmware, software, or any combination thereof for use with external devices such as 24 ( Figure 1 The communication circuit 88 communicates with another device 24 under the control of the processing circuit 80. Under the control of the processing circuit 80, the communication circuit 88 can communicate with the external device 24 by means of an antenna that may be internal and / or external.

[0072] Figure 4 This is a flowchart illustrating an example operation of a device that adjusts the rate of cardiac pacing to simulate RSA. Although described in the context of IMD 16, Figure 4 The example operations may be performed additionally or alternatively by other devices, as described herein.

[0073] In some examples, the processing circuitry 80 of the IMD 16 controls the treatment delivery circuitry 86 to deliver cardiac pacing according to a basic pattern, such as demand pattern, rate response pattern, CRT pattern, or conduction system pacing pattern. Sensing circuitry 82 and / or sensor 84 sense the patient's EGM (e.g., far-field EGM), which indicates respiratory information, i.e., inspiratory and expiratory phase information. The processing circuitry 80 identifies the patient's previous inspiratory phase (402). In some examples, identifying the previous inspiratory phase includes: identifying the start of the previous inspiratory phase, for example by identifying troughs or local minima in respiratory characteristics based on the EGM signal. Additionally, the processing circuitry 80 continuously determines the patient's heart rate (404). In some examples, the processing circuitry 80 determines the heart rate based on the EGM signal. The processing circuitry 80 predicts the start of a subsequent inspiratory phase based at least on the previous inspiratory phase (406). In some examples, the processing circuitry 80 may utilize more than one previous inspiratory phase to predict the start of a subsequent inspiratory phase. For example, processing circuit 80 may predict the start of a subsequent inspiratory phase based on an immediately preceding inspiratory phase and one or more additional preceding inspiratory phases (e.g., an inspiratory phase that occurred before the immediately preceding preceding inspiratory phase). In some examples, processing circuit 80 may determine that the immediately preceding inspiratory phase should not be used to predict the subsequent inspiratory phase. For example, processing circuit 80 may determine that the immediately preceding inspiratory phase indicates a premature beat. In response to determining that the immediately preceding inspiratory phase indicates a premature beat, processing circuit 80 may use inspiratory phase information corresponding to an inspiratory phase that occurred before the immediately preceding preceding inspiratory phase to predict the start of the subsequent inspiratory phase.

[0074] In some examples, processing circuitry 80 may be configured to predict the start of a subsequent inspiratory phase based on the duration and / or timing of a previous inspiratory phase. In some examples, the algorithm may predict the start of a subsequent inspiratory phase based on a running average or moving average of multiple previous inspiratory phases. In some examples, processing circuitry 80 may implement one or more machine learning models to predict the start of a subsequent inspiratory phase. Based on heart rate and previous inspiratory phases, processing circuitry 80 controls treatment delivery circuitry 86 to adjust the rate (408) of cardiac pacing pulses during the subsequent inspiratory phase. In some examples, processing circuitry 80 may continuously update the algorithm for subsequent prediction based on the accuracy of one or more previous predictions relative to one or more previous inspiratory phases. For example, if a previous prediction of an inspiratory phase is relatively accurate relative to a detected inspiratory phase, processing circuitry 80 may maintain the algorithm, and if a previous prediction of an inspiratory phase is relatively inaccurate, processing circuitry 80 may update the algorithm to address the inaccuracies.

[0075] Figure 5 This is a flowchart illustrating example operation of a device that determines whether to adjust the rate of cardiac pacing to simulate RSA. Although described in the context of IMD 16, Figure 5Example operations may be performed additionally or alternatively by other devices, as described herein. In some examples, the processing circuitry 80 of the IMD 16 controls the treatment delivery circuitry 86 to deliver cardiac pacing according to a basic mode, such as demand mode, rate response mode, CRT mode, or conduction system pacing mode. Sensing circuitry 82 and / or sensor 84 sense the patient's EGM, which indicates respiratory information, i.e., inspiratory and expiratory phase information. The processing circuitry 80 identifies the patient's previous inspiratory phase (502). In some examples, identifying the previous inspiratory phase includes: identifying the start of the previous inspiratory phase, for example by identifying a trough or local minimum in the EGM signal. The processing circuitry 80 continuously determines the patient's heart rate (504). In some examples, the processing circuitry 80 additionally identifies the previous expiratory phase, for example, to improve the accuracy of subsequent predictions (506). In some examples, the processing circuitry 80 may utilize more than one previous inspiratory and / or expiratory phase to predict the start of a subsequent inspiratory and / or expiratory phase. For example, processing circuit 80 may predict the start of a subsequent inspiratory and / or expiratory phase based on an immediately preceding inspiratory and / or expiratory phase and one or more additional preceding inspiratory and / or expiratory phases (e.g., inspiratory and / or expiratory phases that occurred before the immediately preceding inspiratory and / or expiratory phase). In some examples, processing circuit 80 may determine that an immediately preceding inspiratory and / or expiratory phase should not be used to predict a subsequent inspiratory and / or expiratory phase. For example, processing circuit 80 may determine that an immediately preceding inspiratory and / or expiratory phase indicates a premature beat. In response to determining that an immediately preceding inspiratory and / or expiratory phase indicates a premature beat, processing circuit 80 may use inspiratory and / or expiratory phase information corresponding to an inspiratory and / or expiratory phase that occurred before the immediately preceding inspiratory and / or expiratory phase to predict the start of a subsequent inspiratory and / or expiratory phase. Based on the previous inspiratory phase and / or expiratory phase, processing circuit 80 predicts the start of the subsequent inspiratory phase (508). Optionally, based on the previous expiratory phase and / or previous inspiratory phase, processing circuit 80 predicts the start of the subsequent expiratory phase (510). Based on heart rate and one or more of the previous inspiratory and / or expiratory phases, processing circuitry determines whether to adjust cardiac pacing to simulate RSA during the subsequent inspiratory phase and optionally during the subsequent expiratory phase (512). If processing circuitry 80 determines to adjust cardiac pacing ("Yes" in 512), processing circuitry 80 controls treatment delivery circuitry 86 to adjust cardiac pacing pulses to simulate RSA, for example, based on RSA pacing parameter 96 (514). Processing circuitry 80 continues the example operation. If processing circuitry 80 determines not to adjust cardiac pacing ("No" in 512), the process continues. In some examples, processing circuitry 80 determines whether to adjust cardiac pacing pulses to simulate 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 has already inherently achieved RSA. If patient 14 is achieving RSA, for example, if patient 14's heart rate inherently increases during inspiration and decreases during expiration (e.g., at least one heartbeat per minute), processing circuitry 80 may determine not to adjust cardiac pacing. If patient 14 has not achieved RSA, processing circuitry 80 may determine to adjust cardiac pacing to simulate RSA.

[0076] In some examples, patient 14 may be fully paced, meaning IMD 16 may initiate depolarization at each step. In examples where patient 14 is fully paced, the processing circuitry may increase the pacing rate or overdrive pacing during the inspiratory phase relative to baseline heart rate and decrease the pacing rate during the expiratory phase, for example, by decreasing the pacing rate relative to baseline heart rate or by decreasing the pacing rate relative to the pacing rate during the inspiratory phase. In other examples, patient 14 may not be fully paced, i.e., IMD 16 may initiate some depolarization, for example, when the heart rate drops below a threshold or when patient 14 experiences a cardiac event, but patient 14's intrinsic pacing system may initiate other depolarizations. In examples where patient 14 is not fully paced, the processing circuitry may increase the pacing rate during the inspiratory phase and may allow patient 14's intrinsic pacing system to drive pacing at a relatively low baseline heart rate (e.g., intrinsic heart rate) during the expiratory phase.

[0077] Figure 5 The example describes the identification of the previous expiratory phase and the prediction of the expiratory phase as optional. However, in other examples, the processing circuit 80 may be configured to identify the previous expiratory phase to predict the subsequent expiratory phase and / or the subsequent inspiratory phase, and the previous inspiratory phase may optionally be identified, for example, to improve the accuracy of the prediction.

[0078] Figure 6 This is a flowchart illustrating example operations of determining whether to adjust cardiac pacing to simulate RSA based on patient heart rate information, according to one or more techniques of this disclosure. In some examples, Figure 6 Example operations can be in Figure 5In step 512, a part of determining whether to adjust cardiac pacing is performed. Processing circuitry 80 determines the patient's average heart rate (602). In some examples, the average heart rate includes the running average or moving average of the heart rate. Processing circuitry 80 compares the average heart rate with 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 the 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 threshold heart rate value may be determined by a clinician. In some examples, over-driving RSA pacing may not be expected in cases where the pacing load is already relatively high and / or the patient is experiencing an elevated heart rate.

[0079] If the average heart rate exceeds the threshold heart rate value ("Yes" in 604), the processing circuit 80 determines not to control the treatment delivery circuit 86 to adjust the cardiac pacing pulse to simulate RSA (608). If the average heart rate does not exceed the threshold heart rate value ("No" in 604), the processing circuit 80 controls the treatment 86 to adjust the cardiac pacing pulse to simulate RSA (606).

[0080] Figure 7 This is a graph illustrating an example EGM signal that includes information about the inspiratory and expiratory phases. Two electrodes from any of the electrodes carried on leads 18, 20, 22 and / or housing electrodes 58 (such as coil electrode 62 and housing electrode 58 in RV 28) sense the EGM signal 702. The peaks of the EGM signal 702 indicate the respiratory feature 704. The troughs 708 or local minimums of the respiratory feature 704 indicate the start of the inspiratory phase. The peaks 706 or local maximums of the respiratory feature 704 indicate the start of the expiratory phase. In some examples, the processing circuitry 80 is configured to identify the inspiratory and / or expiratory phases. In examples where the processing circuitry 80 is configured to identify the inspiratory and expiratory phases, the processing circuitry 80 can detect peaks in peak 706 or troughs in trough 708 by continuously comparing successive samples of the respiratory feature 704. In some examples, if the slope associated with consecutive samples of respiratory feature 704 changes from negative to positive, the processing circuit 80 detects a trough, i.e., a local minimum of respiratory feature 704, and records the trough as the start of inspiration to be stored in patient parameter data 92. Figure 3In the process of detecting peaks, if the slope associated with consecutive samples changes from positive to negative, the processing circuit 80 detects a peak (i.e., a local maximum of the respiratory feature 704) and records the peak as the start of expiration to be stored in the patient parameter data 92. In some examples, the processing circuit 80 may apply one or more thresholds during the peak and trough detection process to prevent erroneous peak and trough detection caused by noise or other sensing problems.

[0081] Figure 8 This is a flowchart illustrating example operations for adjusting cardiac pacing based on patient status. In some examples, patient parameter data 92 may include data indicating patient status. For example, patient parameter data 92 may include one or more of the following: data sensed by electrodes 40, 42, 62, 44, 46, 64, 48, 50, 66 and / or 58, data sensed by sensor 84, or historical patient data. As an example, patient status may be based on one or more of the following: patient activity level, patient age, or patient disease progression (e.g., HF risk level). Based on patient parameter data 92, processing circuitry 80 determines the patient status (802). Based on the patient status, processing circuitry 80 may adjust the rate of cardiac pacing pulses (804).

[0082] In an example where the patient status is based on the patient's activity level, processing circuitry 80 may determine the patient's activity level, for example, via an accelerometer of sensor 84, and / or, for example, based on an EGM signal, determine the patient's heart rate. Based on the patient's activity level, processing circuitry 80 may control treatment 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 simulate RSA by over-pacing during the inspiratory phase relative to a baseline heart rate or pacing the expiratory phase heart rate within a certain range (e.g., 5 to 20 heartbeats per minute). Based on the patient's activity level, processing circuitry 80 may determine to adjust cardiac pacing pulses to over-pac at the lower end of that range (e.g., 5 heartbeats per minute) or the upper end of that range (e.g., 20 heartbeats per minute).

[0083] In an example where the patient's state is based on the progression of the patient's disease, the processing circuitry 80 may determine the progression of the disease state based on, for example, a HF risk level. The processing circuitry 80 may determine to adjust the cardiac pacing pulses to overdrive pacing at the lower end of the range (e.g., 5 heartbeats per minute) for patients at a first (e.g., relatively high) HF risk level, and to overdrive pacing at the higher end of the range (e.g., 20 heartbeats per minute) for patients at a second (e.g., relatively low) HF risk level, which is different from the first HF risk level.

[0084] In some examples, for instance, if patient 14's average heart rate is close to the upper limit tracking rate value (e.g., Figure 6If the threshold in step 604 is not met, the processing circuitry can determine to adjust cardiac pacing to increase the pacing rate to a lower level (e.g., at the lower end of the range, such as 5 heartbeats per minute) to ensure, for example, that the patient's average heart rate does not exceed the upper limit tracking rate value (e.g., during inspiration). The threshold in step 604 is provided as an example only. In other examples, the upper limit tracking rate value includes values ​​other than the threshold in step 604. In some examples, the upper limit tracking rate value may be a predetermined value (e.g., 90 bpm, 100 bpm, 105 bpm, 110 bpm) or may be equal to a specific percentage (e.g., 80%, 90%, 100%) of the programmed upper limit tracking rate of the implanted cardiac device.

[0085] In some examples, clinicians may adjust the range of overdrive pacing, for example, to tailor pacing to a patient's specific needs. In other examples, processing circuitry 80 may adjust the range of overdrive pacing, for example, based on patient parameter data 92. In some examples, processing circuitry 80 may implement a machine learning model to determine the range of overdrive pacing for a patient.

[0086] Example 1. An apparatus comprising: a treatment delivery circuit configured to deliver cardiac pacing pulses to a patient's heart via a plurality of electrodes; a sensing circuit configured to sense an electrogram (EGM) signal from the patient; and a processing circuit configured to: identify a previous inspiratory phase based on the EGM signal; determine the patient's heart rate based on the EGM signal; predict the onset of a subsequent inspiratory phase based on the previous inspiratory phase; and control the treatment delivery circuit to adjust the rate of cardiac pacing during the subsequent inspiratory phase based on the heart rate and the previous inspiratory phase.

[0087] Example 2. The apparatus according to Example 1, wherein adjusting the rate of cardiac pacing during the subsequent inspiratory phase comprises: making the delivery of the cardiac pacing pulse more closely mimic respiratory sinus arrhythmia (RSA).

[0088] Example 3. The apparatus according to any one or more of Examples 1 to 2, wherein the processing circuitry is further configured to: identify a previous expiratory phase based on the EGM signal; predict the start of a subsequent expiratory phase based at least on the previous expiratory phase; and control the treatment delivery circuitry to adjust the rate of cardiac pacing during the subsequent inspiratory phase and the subsequent expiratory phase based on the heart rate, the previous inspiratory phase, and the previous expiratory phase.

[0089] Example 4. The apparatus according to Example 3, wherein the processing circuitry is further configured to: determine that the patient has not reached RSA based on the previous inspiratory phase, the previous expiratory phase, and the heart rate; and adjust the rate of cardiac pacing based on the determination to more closely simulate RSA.

[0090] Example 5. The apparatus according to any one or more of Examples 1 to 4, wherein, in order to adjust the cardiac pacing pulse, the processing circuit is configured to control the treatment delivery circuit to increase the rate of the cardiac pacing pulse from a baseline rate to a higher rate during the subsequent inspiration phase.

[0091] Example 6. The apparatus according to any one or more of Examples 3 to 4, wherein, in order to adjust the cardiac pacing pulse, the processing circuit is configured to: control the treatment delivery circuit to increase the rate of the cardiac pacing pulse from a baseline rate to a higher rate during the subsequent inspiratory phase, and decrease the rate of the cardiac pacing pulse relative to the higher rate during the subsequent expiratory phase.

[0092] Example 7. The apparatus according to any one or more of Examples 1 to 6, wherein the processing circuit is further configured to: compare the average patient heart rate with a threshold; and, in response to the average heart rate falling below the threshold, control the treatment delivery circuit to adjust the cardiac pacing pulse to simulate RSA.

[0093] Example 8. The apparatus according to any one or more of Examples 1 to 7, wherein the EGM signal includes a far-field EGM signal.

[0094] Example 9. The apparatus according to any one or more of Examples 1 to 8, wherein, in order to identify the previous inspiratory phase, the processing circuit is configured to: identify a local minimum of a respiratory feature based on the EGM signal, wherein the local minimum of the respiratory feature indicates the start of the previous inspiratory phase.

[0095] Example 10. An apparatus according to any one or more of Examples 3 to 9, wherein, in order to identify the previous exhalation phase, the processing circuit is configured to: identify a local maximum value of a respiratory feature based on the EGM signal, wherein the local maximum value of the respiratory feature indicates the start of the previous exhalation phase.

[0096] Example 11. An apparatus according to any one or more of Examples 1 to 10, wherein, in order to sense the EGM signal, the sensing circuit is configured to: sense the EGM signal via an RV coil electrode electrically coupled to the can electrode of the apparatus; or sense the EGM signal via an RV tip electrode electrically coupled to the can electrode of the apparatus.

[0097] Example 12. The apparatus according to any one or more of Examples 1 to 11, wherein the processing circuitry is further configured to: determine a patient state; and control the treatment delivery circuitry to adjust the rate of the cardiac pacing pulses based on the patient state.

[0098] Example 13. The device according to Example 12, wherein the patient state includes one or more of the following: patient disease state; or patient activity level.

[0099] Example 14. The device according to any one or more of Examples 1 to 13, wherein the device includes an implantable medical device (IMD).

[0100] Example 15. The device according to Example 14, wherein the IMD includes a pacemaker.

[0101] Example 16. A method comprising: sensing an electrophysiological (EGM) signal of a patient by a sensing circuit of a medical device system; identifying a previous inspiratory phase by a processing circuit of the system based on the EGM signal; determining a heart rate by the processing circuit based on the EGM signal; predicting the start of a subsequent inspiratory phase by the processing circuit based on the previous inspiratory phase; and controlling a treatment delivery circuit of the medical device to adjust the rate of cardiac pacing pulses delivered to the patient's heart during the subsequent inspiratory phase based on the heart rate and the previous inspiratory phase.

[0102] Example 17. The method according to Example 16, wherein adjusting the rate of cardiac pacing during the subsequent inspiratory phase comprises: making the delivery of the cardiac pacing pulse more closely mimic respiratory sinus arrhythmia (RSA).

[0103] Example 18. The method according to any one or more of Examples 16 to 17, wherein the processing circuit is further configured to: identify a previous expiratory phase based on the EGM signal; predict the start of a subsequent expiratory phase based at least on the previous expiratory phase; and control the treatment delivery circuit to adjust the rate of cardiac pacing during the subsequent inspiratory phase and the subsequent expiratory phase based on the heart rate, the previous inspiratory phase, and the previous expiratory phase.

[0104] Example 19. The method according to Example 18, the method further comprising: determining, by the processing circuitry, that the patient has not reached RSA based on the previous inspiratory phase, the previous expiratory phase, and the heart rate; and adjusting, by the processing circuitry, the rate of cardiac pacing based on the determination to more closely simulate RSA.

[0105] Example 20. The method according to any one or more of Examples 16 to 19, wherein adjusting the cardiac pacing pulse includes: the processing circuit controlling the treatment delivery circuit to increase the rate of the cardiac pacing pulse from a baseline rate to a higher rate during the subsequent inspiration phase.

[0106] Example 21. The method according to any one or more of Examples 18 to 20, wherein adjusting the cardiac pacing pulse comprises: the processing circuit controlling the treatment delivery circuit to increase the rate of the cardiac pacing pulse from a baseline rate to a higher rate during the subsequent inspiratory phase, and decreasing the rate of the cardiac pacing pulse relative to the higher rate during the subsequent expiratory phase.

[0107] Example 22. The method according to any one or more of Examples 16 to 21, the method further comprising: comparing the average patient heart rate with a threshold by the processing circuit; and controlling the treatment delivery circuit to adjust the cardiac pacing pulse to simulate RSA by the processing circuit in response to the average heart rate falling below the threshold.

[0108] Example 23. The method according to any one or more of Examples 16 to 22, wherein the EGM signal includes a far-field EGM signal.

[0109] Example 24. The method according to any one or more of Examples 16 to 23, wherein identifying the previous inspiratory phase includes: identifying a local minimum of a respiratory feature by the processing circuit based on the EGM signal, wherein the local minimum of the respiratory feature indicates the start of the previous inspiratory phase.

[0110] Example 25. The method according to any one or more of Examples 18 to 24, wherein identifying the previous exhalation phase includes: the processing circuit identifying a local maximum value of a respiratory feature based on the EGM signal, wherein the local maximum value of the respiratory feature indicates the start of the previous exhalation phase.

[0111] Example 26. The method according to any one or more of Examples 16 to 25, wherein sensing the EGM signal comprises: sensing the EGM signal by the sensing circuit via an RV coil electrode electrically coupled to the can electrode of the device; or sensing the EGM signal by the sensing circuit via an RV tip electrode electrically coupled to the can electrode of the device.

[0112] Example 27. The method according to any one or more of Examples 16 to 26, the method further comprising: determining a patient state by the processing circuit; and controlling the treatment delivery circuit to adjust the rate of the cardiac pacing pulse based on the patient state by the processing circuit.

[0113] Example 28. The method according to Example 27, wherein the patient status includes one or more of the following: patient disease status; or patient activity level.

[0114] Example 29. The method according to any one or more of Examples 16 to 28, wherein the medical device includes an implantable medical device (IMD).

[0115] Example 30. The method according to Example 29, wherein the IMD includes a pacemaker.

[0116] Example 31. A non-transitory computer-readable storage medium storing instructions that, when executed by a processing circuit, cause the processing circuit to: control a sensing circuit to sense an electrophysiological (EGM) signal of a patient; identify a previous inspiratory phase based on the EGM signal; determine the patient's heart rate based on the EGM signal; predict the start of a subsequent inspiratory phase based on the previous inspiratory phase; and control a treatment delivery circuit to adjust the rate of cardiac pacing during the subsequent inspiratory phase based on the heart rate and the previous inspiratory phase.

[0117] Example 32. An apparatus comprising: a treatment delivery circuit configured to deliver cardiac pacing pulses to a patient's heart via a plurality of electrodes; a sensing circuit configured to sense an electrogram (EGM) signal from the patient; and a processing circuit configured to: identify a previous expiratory phase based on the EGM signal; determine the patient's heart rate based on the EGM signal; predict the onset of a subsequent expiratory phase based on the previous expiratory phase; and control the treatment delivery circuit to adjust the rate of cardiac pacing during the subsequent expiratory phase based on the heart rate and the previous expiratory phase.

[0118] Example 33. The apparatus according to Example 32, wherein adjusting the rate of cardiac pacing during the subsequent expiratory phase comprises: making the delivery of the cardiac pacing pulse more closely mimic respiratory sinus arrhythmia (RSA).

[0119] Example 34. The apparatus according to any one or more of Examples 32 to 33, wherein the processing circuitry is further configured to: identify a previous inspiratory phase based on the EGM signal; predict the start of a subsequent inspiratory phase based at least on the previous inspiratory phase; and control the treatment delivery circuitry to adjust the rate of cardiac pacing during the subsequent expiratory phase and the subsequent inspiratory phase based on the heart rate, the previous expiratory phase, and the previous inspiratory phase.

[0120] Example 35. According to the apparatus of Example 34, the processing circuit is further configured to: determine, based on the previous expiratory phase, the previous inspiratory phase, and the heart rate, that the patient has not reached RSA; and adjust the rate of cardiac pacing based on the determination to more closely simulate RSA.

[0121] Example 36. The apparatus according to any one or more of Examples 34 to 35, wherein, in order to adjust the cardiac pacing pulse, the processing circuit is configured to control the treatment delivery circuit to increase the rate of the cardiac pacing pulse from a baseline rate to a higher rate during the subsequent inspiratory phase.

[0122] Example 37. The apparatus according to any one or more of Examples 34 to 35, wherein, in order to adjust the cardiac pacing pulse, the processing circuit is configured to: control the treatment delivery circuit to increase the rate of the cardiac pacing pulse from a baseline rate to a higher rate during the subsequent inspiratory phase, and decrease the rate of the cardiac pacing pulse relative to the higher rate during the subsequent expiratory phase.

[0123] Example 38. The apparatus according to any one or more of Examples 32 to 37, wherein the processing circuitry is further configured to: compare the average patient heart rate with a threshold; and, in response to the average heart rate falling below the threshold, control the treatment delivery circuitry to adjust the cardiac pacing pulse to simulate RSA.

[0124] Example 39. The apparatus according to any one or more of Examples 32 to 38, wherein the EGM signal includes a far-field EGM signal.

[0125] Example 40. An apparatus according to any one or more of Examples 34 to 39, wherein, in order to identify the previous inspiratory phase, the processing circuitry is configured to: identify a local minimum of a respiratory feature based on the EGM signal, wherein the local minimum of the respiratory feature indicates the start of the previous inspiratory phase.

[0126] Example 41. The apparatus according to any one or more of Examples 32 to 40, wherein, in order to identify the previous exhalation phase, the processing circuit is configured to: identify a local maximum value of a respiratory feature based on the EGM signal, wherein the local maximum value of the respiratory feature indicates the start of the previous exhalation phase.

[0127] Example 42. The apparatus according to any one or more of Examples 32 to 41, wherein, in order to sense the EGM signal, the sensing circuit is configured to: sense the EGM signal via an RV coil electrode electrically coupled to the can electrode of the apparatus; or sense the EGM signal via an RV tip electrode electrically coupled to the can electrode of the apparatus.

[0128] Example 43. The apparatus according to any one or more of Examples 32 to 42, wherein the processing circuitry is further configured to: determine a patient state; and control the treatment delivery circuitry to adjust the rate of the cardiac pacing pulses based on the patient state.

[0129] Example 44. The device according to Example 43, wherein the patient state includes one or more of the following: patient disease state; or patient activity level.

[0130] Example 45. The device according to any one or more of Examples 32 to 44, wherein the device includes an implantable medical device (IMD).

[0131] Example 46. The device according to Example 45, wherein the IMD includes a pacemaker.

[0132] Example 47. A method comprising: sensing an electrophysiological (EGM) signal of a patient by a sensing circuit of a medical device system; identifying a previous expiratory phase by a processing circuit of the system based on the EGM signal; determining a heart rate by the processing circuit based on the EGM signal; predicting the start of a subsequent expiratory phase by the processing circuit based on the previous expiratory phase; and controlling a treatment delivery circuit of the medical device to adjust the rate of cardiac pacing pulses delivered to the patient's heart during the subsequent expiratory phase based on the heart rate and the previous expiratory phase.

[0133] Example 48. The method according to Example 47, wherein adjusting the rate of cardiac pacing during the subsequent expiratory phase comprises: making the delivery of the cardiac pacing pulse more closely mimic respiratory sinus arrhythmia (RSA).

[0134] Example 49. The method according to any one or more of Examples 47 to 48, wherein the processing circuit is further configured to: identify a previous inspiratory phase based on the EGM signal; predict the start of a subsequent inspiratory phase based at least on the previous inspiratory phase; and control the treatment delivery circuit to adjust the rate of cardiac pacing during the subsequent expiratory phase and the subsequent inspiratory phase based on the heart rate, the previous expiratory phase, and the previous inspiratory phase.

[0135] Example 50. The method according to Example 49, the method further comprising: determining, by the processing circuitry, that the patient has not reached RSA based on the previous expiratory phase, the previous inspiratory phase, and the heart rate; and adjusting, by the processing circuitry, the rate of cardiac pacing based on the determination to more closely simulate RSA.

[0136] Example 51. The method according to any one or more of Examples 49 to 50, wherein adjusting the cardiac pacing pulse comprises: the processing circuit controlling the treatment delivery circuit to increase the rate of the cardiac pacing pulse from a baseline rate to a higher rate during the subsequent inspiration phase.

[0137] Example 52. The method according to any one or more of Examples 49 to 50, wherein adjusting the cardiac pacing pulse comprises: the processing circuit controlling the treatment delivery circuit to increase the rate of the cardiac pacing pulse from a baseline rate to a higher rate during the subsequent inspiratory phase, and to decrease the rate from the baseline rate to a lower rate during the subsequent expiratory phase.

[0138] Example 53. The method according to any one or more of Examples 47 to 52, the method further comprising: comparing the average patient heart rate with a threshold by the processing circuit; and controlling the treatment delivery circuit to adjust the cardiac pacing pulse to simulate RSA by the processing circuit in response to the average heart rate falling below the threshold.

[0139] Example 54. The method according to any one or more of Examples 47 to 53, wherein the EGM signal includes a far-field EGM signal.

[0140] Example 55. The method according to any one or more of Examples 49 to 54, wherein identifying the previous inspiratory phase includes: identifying a local minimum of a respiratory feature by the processing circuit based on the EGM signal, wherein the local minimum of the respiratory feature indicates the start of the previous inspiratory phase.

[0141] Example 56. The method according to any one or more of Examples 47 to 55, wherein identifying the previous exhalation phase includes: the processing circuit identifying a local maximum value of a respiratory feature based on the EGM signal, wherein the local maximum value of the respiratory feature indicates the start of the previous exhalation phase.

[0142] Example 57. The method according to any one or more of Examples 47 to 56, wherein sensing the EGM signal comprises: sensing the EGM signal by the sensing circuit via an RV coil electrode electrically coupled to the can electrode of the device; or sensing the EGM signal by the sensing circuit via an RV tip electrode electrically coupled to the can electrode of the device.

[0143] Example 58. The method according to any one or more of Examples 47 to 57, the method further comprising: determining a patient state by the processing circuit; and controlling the treatment delivery circuit to adjust the rate of the cardiac pacing pulse based on the patient state by the processing circuit.

[0144] Example 59. The method according to Example 58, wherein the patient status includes one or more of the following: patient disease status; or patient activity level.

[0145] Example 60. The method according to any one or more of Examples 47 to 59, wherein the medical device includes an implantable medical device (IMD).

[0146] Example 61. The method according to Example 60, wherein the IMD includes a pacemaker.

[0147] Example 62. A non-transitory computer-readable storage medium storing instructions that, when executed by a processing circuit, cause the processing circuit to: control a sensing circuit to sense an electrophysiological (EGM) signal of a patient; identify a previous expiratory phase based on the EGM signal; determine the patient's heart rate based on the EGM signal; predict the onset of a subsequent expiratory phase based on the previous expiratory phase; and control a treatment delivery circuit to adjust the rate of cardiac pacing during the subsequent expiratory phase based on the heart rate and the previous expiratory phase.

[0148] Various embodiments have been described. These and other embodiments are within the scope of the appended claims.

Claims

1. An apparatus, the apparatus comprising: A treatment delivery circuit configured to deliver cardiac pacing pulses to a patient’s heart via multiple electrodes; A sensing circuit configured to sense the patient's electrophysiological record (EGM) signal; and Processing circuit, the processing circuit being configured to: The previous inhalation phase is identified based on the EGM signal; The patient's heart rate is determined based on the EGM signal; Predicting the start of the subsequent inspiratory phase based on the previous inspiratory phase; and The treatment delivery circuitry is controlled to adjust the rate of the cardiac pacing pulses during the subsequent inspiratory phase based on the heart rate and the previous inspiratory phase.

2. The apparatus of claim 1, wherein, in order to adjust the rate of the cardiac pacing pulse during the subsequent inspiratory phase, the processing circuit causes the treatment delivery circuit to deliver the cardiac pacing pulse to more closely mimic respiratory sinus arrhythmia (RSA).

3. The apparatus according to any one or more of claims 1 to 2, wherein the processing circuit is further configured to: The previous expiratory phase is identified based on the EGM signal; The onset of the subsequent expiratory phase is predicted based at least on the preceding expiratory phase; and The treatment delivery circuit controls the rate of the cardiac pacing pulses during the subsequent inhalation and exhalation phases based on the heart rate, the previous inhalation phase, and the previous exhalation phase.

4. The apparatus of claim 3, wherein the processing circuit is further configured to: Based on the previous inspiratory phase, the previous expiratory phase, and the heart rate, it was determined that the patient had not reached RSA; and Based on the determination, the rate of the cardiac pacing pulse is adjusted to more closely simulate RSA.

5. The apparatus according to any one or more of claims 1 to 4, wherein, in order to adjust the cardiac pacing pulse, the processing circuit is configured to: The treatment delivery circuit controls the rate of the cardiac pacing pulse to increase from the baseline rate to a higher rate during the subsequent inspiratory phase.

6. The apparatus according to any one or more of claims 3 to 4, wherein, in order to adjust the cardiac pacing pulse, the processing circuit is configured to: The treatment delivery circuit controls the rate of the cardiac pacing pulse to increase from a baseline rate to a higher rate during the subsequent inspiratory phase and to decrease the rate of the cardiac pacing pulse relative to the higher rate during the subsequent expiratory phase.

7. The apparatus according to any one or more of claims 1 to 6, wherein the processing circuitry is further configured to: Compare the average patient heart rate to a threshold; and In response to the average heart rate dropping below the threshold, the treatment delivery circuit is controlled to adjust the cardiac pacing pulse to simulate RSA.

8. The apparatus according to any one or more of claims 1 to 7, wherein the EGM signal includes a far-field EGM signal.

9. The apparatus according to any one or more of claims 1 to 8, wherein the processing circuitry is configured to: The local minimum of the respiratory feature is identified based on the EGM signal, wherein the local minimum of the respiratory feature indicates the start of the previous inspiratory phase.

10. The apparatus according to any one or more of claims 3 to 9, wherein the processing circuitry is configured to: The local maximum value of the respiratory feature is identified based on the EGM signal, wherein the local maximum value of the respiratory feature indicates the start of the previous expiratory phase.

11. The apparatus according to any one or more of claims 1 to 10, wherein, in order to sense the EGM signal, the sensing circuit is configured to: The EGM signal is sensed by the RV coil electrode, which is electrically coupled to the can electrode of the device; or The EGM signal is sensed by the RV tip electrode of the can electrode of the device, which is electrically coupled to the device.

12. The apparatus according to any one or more of claims 1 to 11, wherein the processing circuitry is further configured to: Determine the patient's condition; and The treatment delivery circuit is controlled to adjust the rate of the cardiac pacing pulse based on the patient's condition.

13. The device of claim 12, wherein the patient state includes one or more of the following: Patient's disease state; or Patient activity level.

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

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

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