Tracking respiration and respiration phase pacing using bioimpedance

Abstract

This disclosure describes techniques for tracking respiration and respiratory phase pacing using bioimpedance measurements. 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 a bioimpedance signal from the patient; and a processing circuit configured to: identify the start of the patient's current inspiratory phase based on the bioimpedance signal; and control the treatment delivery circuit to adjust the rate of cardiac pacing during the current inspiratory phase based on the identification of the start of the current inspiratory phase.

Description

[0001] This application claims the benefit of U.S. Provisional Application Serial No. 63 / 568,283, filed March 21, 2024, entitled “TRACKING RESPIRATION AND RESPIROPHASIC PACING USING BIOIMPEDANCE”, the entire contents of which are incorporated herein by reference. Technical Field

[0002] This disclosure relates in general to medical devices, and more specifically to medical devices for delivering cardiac treatment. Background Technology

[0003] 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

[0004] Generally, this disclosure describes techniques for delivering cardiac pacing to mimic RSA, such as by increasing the cardiac pacing pulse rate during inspiration and, in some examples, decreasing the pulse rate during expiration.

[0005] 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 pacing that remains constant throughout the respiratory cycle). Cardiac pacing that mimics RSA (i.e., respiratory phase pacing) can provide therapeutic benefits, for example, by increasing cardiac output and helping to reverse cardiac remodeling in patients with heart failure (HF). However, current approaches to restoring RSA are based on several previously detected, averaged inspiratory and expiratory phases of 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).

[0006] The technology disclosed herein can be implemented by a cardiac treatment device (e.g., a pacemaker) that continuously senses physiological signals (e.g., bioimpedance and / or electrogram (EGM) signals) indicating inspiratory and expiratory phases, and independently detects the inspiratory and expiratory phases. 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 treatment delivery circuitry to adjust cardiac pacing pulses based on the inspiratory and / or expiratory phases. In some examples, the pacemaker can be configured to predict subsequent inspiratory and / or expiratory phases for the patient based on detected inspiratory and / or expiratory phases, and control treatment delivery circuitry to adjust cardiac pacing pulses.

[0007] In some instances, under certain conditions, such as when the patient has already achieved 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.

[0008] 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.

[0009] In some examples, the techniques disclosed herein may include determining one or more stimulation parameters, such as stimulation amplitude, for measuring a bioimpedance signal. In some examples, determining one or more stimulation parameters may include determining whether each of a plurality of stimulation parameters causes a quality level associated with the signal to satisfy one or more thresholds.

[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 a bioimpedance signal from the patient; and a processing circuit configured to: identify the start of the patient's current inspiratory phase based on the bioimpedance signal; and control the treatment delivery circuit to adjust the rate of cardiac pacing during the current inspiratory phase based on the identification of the start of the current inspiratory phase.

[0011] In another example, one method includes: sensing a patient's bioimpedance signal by sensing circuitry of a medical device; identifying the start of the patient's current inspiratory phase by processing circuitry of the medical device based on the bioimpedance signal; and controlling a treatment delivery circuitry of the medical device by the processing circuitry to adjust the rate of cardiac pacing during the current inspiratory phase, wherein the treatment delivery circuitry is configured to deliver cardiac pacing pulses to the patient's heart via multiple electrodes based on the identification of the start of the current inspiratory phase.

[0012] 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 a patient's bioimpedance signal; and a processing circuit configured to: identify the start of the patient's current expiratory phase based on the bioimpedance signal; and to control the treatment delivery circuit to adjust the rate of cardiac pacing during a respiratory cycle associated with the current expiratory phase based on the identification of the start of the current expiratory phase.

[0013] In another example, one method includes: sensing a patient's bioimpedance signal by sensing circuitry of a medical device; identifying the start of the patient's current expiratory phase by processing circuitry of the medical device based on the bioimpedance signal; and controlling a treatment delivery circuitry of the medical device by the processing circuitry to adjust the rate of cardiac pacing during a respiratory cycle associated with the current expiratory phase, wherein the treatment delivery circuitry is configured to deliver cardiac pacing pulses to the patient's heart via multiple electrodes based on the identification of the start of the current expiratory phase.

[0014] In another example, a non-transitory computer-readable medium stores instructions that, when executed by processing circuitry, cause the processing circuitry to: identify the start of the patient’s current inspiratory phase based on bioimpedance signals; and control a treatment delivery circuitry to adjust the rate of cardiac pacing during the current inspiratory phase based on the identification of the start of the current inspiratory phase.

[0015] In another example, a non-transitory computer-readable medium stores instructions that, when executed by processing circuitry, cause the processing circuitry to: identify the start of the patient’s current expiratory phase based on bioimpedance signals; and control a treatment delivery circuitry to adjust the rate of cardiac pacing during the respiratory cycle associated with the current expiratory phase based on the identification of the start of the current 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 1 This 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 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 a cardiac pacing pulse according to one or more techniques of this disclosure.

[0022] Figure 6 This is a flowchart illustrating an example operation for determining whether to switch to sensing an EGM signal according to one or more techniques of this disclosure.

[0023] Figure 7 This is a flowchart illustrating an example operation of determining whether to adjust the rate of cardiac pacing pulses based on one or more techniques according to this disclosure.

[0024] Figure 8 This is a flowchart illustrating example operations for identifying valleys and peaks in bioimpedance signals according to one or more techniques of this disclosure.

[0025] Figure 9 This is a graph illustrating an example bioimpedance signal that includes information about the inspiratory and expiratory phases, and this example bioimpedance signal can be identified according to one or more techniques of this disclosure.

[0026] Figure 10 This is a flowchart illustrating an example operation of selecting one or more stimulation parameters to sense a bioimpedance signal according to one or more techniques of this disclosure.

[0027] Figure 11 This is a flowchart illustrating an example operation of adjusting the rate of cardiac pacing pulses based on patient condition, according to one or more techniques of this disclosure.

[0028] Figure 12This is a flowchart illustrating an example operation of adjusting cardiac pacing pulses based on predicted inspiratory and expiratory phases, according to one or more techniques of this disclosure.

[0029] Figure 13 This is a flowchart illustrating an example operation of dynamically adjusting one or more stimulation parameters for sensing bioimpedance signals according to one or more techniques of this disclosure.

[0030] Throughout the accompanying drawings and description, the same reference numerals refer to the same elements. Detailed Implementation

[0031] 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.

[0032] 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.

[0033] Many current pacemakers monotonically pace based on lung inspiration / expiration, and the monotonous pacing rate increases with activity (e.g., increases with activity level but remains unchanged within the respiratory cycle). Cardiac pacing that mimics RSA (i.e., respiratory phase pacing) can provide therapeutic benefits, for example, by increasing cardiac output and helping to reverse cardiac remodeling in patients with heart failure (HF). However, current approaches to 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).

[0034] The techniques disclosed herein can be implemented by a cardiac treatment device (e.g., a pacemaker) that continuously senses physiological signals (e.g., bioimpedance and / or electrogram (EGM) signals) indicating the inspiratory and expiratory phases, and independently detects the inspiratory and expiratory phases. 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 current inspiratory and / or expiratory phases. By continuously monitoring the inspiratory and / or expiratory phases and adjusting the cardiac pacing pulse based on the current inspiratory and / or expiratory phases, the techniques disclosed herein improve the accuracy of RSA pacing. Therefore, patients can receive cardiac pacing that more closely mimics RSA, which can improve patient outcomes.

[0035] Under certain conditions, such as when a patient has already achieved 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 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 would likely be effective and avoiding the delivery of counterproductive treatments, thereby benefiting the patient.

[0036] 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.

[0037] In some examples, the techniques of this disclosure may include determining one or more stimulation parameters, such as stimulation amplitude, for measuring a bioimpedance signal. In some examples, determining one or more stimulation parameters may include determining whether each of a plurality of stimulation parameters causes the quality level associated with the signal to meet one or more thresholds. In some examples, the techniques may additionally include selecting stimulation parameters that conserve battery life, which can increase device lifespan. As an example, to determine one or more stimulation parameters (e.g., stimulation amplitude), the techniques of this disclosure may include periodically fine-tuning the stimulation amplitude until one or more features of the bioimpedance signal corresponding to the stimulation amplitude fall within a range defined by an upper threshold and a lower threshold. By fine-tuning the stimulation amplitude until one or more features of the bioimpedance signal corresponding to the stimulation amplitude fall within this range, the techniques of this disclosure can facilitate maintaining a stimulation amplitude above a quality level threshold while selecting a stimulation amplitude that conserves battery life.

[0038] In some examples, the techniques of this disclosure may include switching from sensing one type of physiological signal to another in response to changes in patient activity, for example, switching from sensing a bioimpedance signal to sensing an EGM signal. In some examples, some physiological signals may be more noise-resistant than others, for example, particularly during periods of relatively high patient activity, but may also require more battery power. By switching between physiological signals in response to changes in patient activity levels, the techniques of this disclosure can increase accuracy and battery life, thereby improving RSA pacing, which in turn improves patient outcomes.

[0039] Additionally or alternatively, in some examples, the techniques of this disclosure may include: predicting (e.g., intermittently predicting and / or predicting over an extended period of time) subsequent inspiratory and / or expiratory phases of the patient based on detected inhalation and / or exhalation, and controlling treatment delivery circuitry to adjust cardiac pacing pulses. By intermittently predicting inspiratory and / or expiratory phases based on one or more prior phases, such as predicting every one or every three inspiratory and / or expiratory phases and / or inspiratory and / or expiratory phases over an extended period of time, for example, when the baseline patient heart rate is below a certain baseline heart rate threshold, when the inherent change in heart rate is less than a heart rate change threshold and / or when the activity level is less than an activity threshold, the techniques of this disclosure can save battery life, which can increase device lifespan.

[0040] Figure 1 This is a conceptual diagram illustrating an example system 10 configured to deliver cardiac pacing in a patient 14 to mimic respiratory sinus arrhythmia (RSA) (i.e., respiratory phase pacing) according to one or more techniques 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.

[0041] 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 bioimpedance signals, 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 bioimpedance indicating fluid volume in the patient 14 and the patient 14's respiration. In addition to bioimpedance, respiratory characteristics indicating the inspiratory and expiratory phases can also exist as components of the cardiac EGM signal.

[0042] exist Figure 1 In 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.

[0043] 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 lead segments extending into the vena cava or other veins to deploy one or more electrodes. Figure 1 (Not shown). Additionally, in some examples, system 10 may additionally or alternatively include an external vascular lead having an electrode 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 complement to the IMD 16. One or more leadless pacemakers may be configured to deliver cardiac pacing in RSA mode as described herein with respect to the IMD 16. Additionally, an external medical device may be configured to deliver cardiac pacing in RSA mode as described herein with respect to the IMD 16. In some examples, the system may additionally or alternatively include one or more implantable or external monitoring devices that monitor patient parameters but do not provide treatment, such as the Reveal LINQ, commercially available from Medtronic. ™ A heart monitor can be inserted.

[0044] 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 provides 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 capable of stimulating) the heart's conduction system, such as the His bundle, left bundle branch, or right bundle branch.

[0045] 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 the 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.

[0046] The IMD 16 can utilize two of any of the electrodes carried on leads 18, 20, and 22 to stimulate and sense bioimpedance signals. In some examples, the IMD 16 can also utilize the shell electrode (not shown) of the IMD 16 to stimulate and sense bioimpedance signals and monitor cardiac activity. While these bioimpedance signals can be used to monitor the heart 12 for therapeutic purposes, in some examples, the IMD 16 can also use any two of the electrodes on leads 18, 20, and 22 or the shell electrode to sense the bioimpedance of the patient 14 to monitor the condition of the heart 12. For example, the IMD 16 can monitor heart rate, heart rate variability, blood flow parameters, or the heart 12's ability to pump blood or other indicators of heart failure (HF) progression based on the bioimpedance signal or another sensed signal.

[0047] As another example, as the fluid content in the tissue within patient 14's pleural cavity increases, the impedance between the two electrodes can also change. IMD 16 can use this bioimpedance to create a fluid index. As the fluid index increases, more fluid may be more likely to remain in patient 14's body, and the heart 12 may be stressed to keep up with the movement of a larger amount of fluid.

[0048] The IMD 16 may additionally or alternatively utilize two of the electrodes carried on leads 18, 20, 22 to sense the EGM signal. In some examples, the IMD 16 may also use the housing electrodes (not shown) of the IMD 16 to sense the 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 signal can also be used to monitor the condition of the heart 12. For example, the IMD 16 may monitor heart rate, heart rate variability, blood flow parameters, or the heart 12's ability to pump blood or the progression of heart failure (HF) and / or other indicators of a disease state (e.g., hypertension) based on the EGM signal or another sensing signal.

[0049] 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 the IMD 16, for example, to select values ​​for the operating parameters of the IMD 16. Although the user is usually a clinician, in some examples the user may be a patient 14.

[0050] 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.

[0051] 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.

[0052] 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.

[0053] 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 bioimpedance, identify the inspiratory and / or expiratory phases, and adjust the cardiac pacing pulses based on heart rate and the inspiratory and / or expiratory phases during the inspiratory and / or expiratory phases.

[0054] Figure 2 This is a conceptual diagram illustrating the IMD 16 and leads 18, 20, and 22 of system 10 in more detail according to one or more techniques of this disclosure. 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 contain electrical contacts of corresponding electrical contacts within connector block 34 electrically coupled to 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.

[0055] Each of leads 18, 20, and 22 includes 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 electrodes are present in the left atrium 33. However, other examples may include electrodes in the left atrium 33. Furthermore, in the example where the IMD 16 is configured to deliver conduction system pacing, lead 18 may be configured / positioned adjacent to… Figure 2The 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.

[0056] 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 in the coil conductor within the lead body of its associated lead 18, 20, and 22, and thereby coupled to a corresponding electrical contact in an electrical contact on the proximal end of leads 18, 20, and 22.

[0057] In some examples, such as Figure 2 As illustrated, 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.

[0058] 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.

[0059] 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 electrode used for delivery of therapy or sensing, its associated conductors and connectors, and any combination of tissue or fluid between the electrodes define the electrical path.

[0060] In some examples, to stimulate and sense bioimpedance signals, the IMD 16 is stimulated via a loop electrode (e.g., electrode 40) located in RV 28 and a loop electrode (e.g., electrode 44) located in LV 32, and senses bioimpedance signals via a tip electrode (e.g., electrode 42) located in RV 28 and a tip electrode (e.g., electrode 46) located in LV 32. The IMD 16 can also be stimulated via a tip electrode (e.g., electrode 42) located in RV 28 and a coil electrode (e.g., electrode 62) located in RV 28, and senses bioimpedance signals via a loop electrode (e.g., electrode 40) located in RV 28 and a coil electrode (e.g., electrode 62) located in RV 28. The IMD 16 can also be stimulated via a tip electrode (e.g., electrode 50) located in the right atrium 26 and a tip electrode (e.g., electrode 42) located in the RV 28, and bioimpedance signals can be sensed via a loop electrode (e.g., electrode 48) located in the right atrium 26 and a loop electrode (e.g., electrode 40) located in the RV 28. The stimulation and sensing configurations described herein are for illustrative purposes only. Several other stimulation and sensing configurations are also possible.

[0061] In some examples, the IMD 16 may additionally or alternatively sense far-field EGM signals via coil electrodes 62 and housing electrodes 58 positioned in the RV 28. Additionally or alternatively, the IMD 16 may sense EGM signals via tip electrodes 42 and housing electrodes 58. Other EGM signal sensing configurations are also possible.

[0062] In addition to sensing bioimpedance to identify the inspiratory and / or expiratory phases, 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 intrathoracic bioimpedance, for example, in patient 14. This bioimpedance 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 bioimpedance to identify trends in the fluid index during patient monitoring over days, weeks, months, or even years.

[0063] In some examples, the two electrodes used to measure intrathoracic bioimpedance 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 RV 28 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 bioimpedance.

[0064] Figure 3 This is a functional block diagram illustrating an example configuration of an IMD 16 according to one or more technologies of this disclosure. In the illustrated example, the 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 the IMD 16 and processing circuitry 80 to perform various functions attributed herein to the 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.

[0065] 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.

[0066] 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, or increasing and / or decreasing the rate of cardiac pacing pulses to simulate the degree of RSA. RSA pacing parameters 96 may additionally include bioimpedance stimulation and sensing configurations and stimulation parameters, such as stimulation amplitude and signal quality thresholds. In some examples, processing circuitry 80 may be configured to periodically (e.g., hourly, daily, or weekly) control treatment delivery circuitry 86 to deliver treatment at multiple stimulation amplitudes during a search phase (e.g., a 30-second to 60-second search phase). Based on bioimpedance signals corresponding to the multiple stimulation amplitudes, processing circuitry 80 selects the stimulation amplitude to be used in treatment delivery. In some examples, to select the stimulation amplitude, processing circuitry 80 compares one or more characteristics of the bioimpedance signal with one or more quality thresholds. The processing circuit 80 can select the lowest stimulation amplitude value associated with one or more characteristics of a bioimpedance signal that meets one or more quality thresholds.

[0067] The thresholds and one or more features may include one or more of the following: the standard deviation of the interval between consecutive trough thresholds (such as 60 ms), the standard deviation of the interval between consecutive peak thresholds (such as 60 ms), the coefficient of variation of amplitude at each peak in the bioimpedance signal threshold (such as 25), the coefficient of variation of amplitude at each trough in the bioimpedance signal threshold (such as 25), and / or the difference between the mean peak amplitude and the mean trough amplitude threshold, for example, to measure the bioimpedance signal strength. In some examples, one or more quality and / or periodic thresholds may additionally or alternatively include one or more of the following: an average dynamic range threshold window, a peak / trough consistency threshold window, or a peak-to-trough interval consistency threshold window.

[0068] In some examples, to select the stimulation amplitude, processing circuitry 80 may control treatment delivery circuitry 86 to fine-tune the stimulation amplitude until one or more characteristics of the bioimpedance signal (e.g., average dynamic range, peak / trough consistency, and / or peak-to-trough interval consistency) fall within one or more corresponding threshold windows. Average dynamic range may include the average ratio between the maximum and minimum measurable signal levels of the bioimpedance signal. In some examples, average dynamic range may be measured in decibels. Processing circuitry 80 may compare the average dynamic range of the bioimpedance signal associated with the stimulation amplitude to an average dynamic range threshold window. The threshold window may be defined by an upper threshold and a lower threshold. The threshold window may be associated with a range of values ​​for which the average dynamic range meets quality criteria and also with power savings. If the average dynamic range is within the average dynamic range threshold window, processing circuitry 80 may determine to set the stimulation amplitude. Otherwise, processing circuitry 80 may adjust the stimulation amplitude and repeat the process.

[0069] Peak / valley consistency can include the consistency of peak / valley amplitude. In some examples, processing circuitry 80 can determine peak / valley consistency by comparing the peak / valley amplitudes in the signal over time. More consistent peak / valley amplitudes may be associated with higher values, and less consistent peak / valley amplitudes may be associated with lower values. Processing circuitry 80 can compare the peak / valley consistency of the bioimpedance signal associated with the stimulus amplitude to a peak / valley consistency threshold window. The threshold window may be defined by an upper threshold and a lower threshold. The threshold window may be associated with a range of values ​​for which peak / valley consistency meets quality criteria, and also with power savings. If the peak / valley consistency is within the peak / valley consistency threshold window, processing circuitry 80 can determine to set the stimulus amplitude. Otherwise, processing circuitry 80 can adjust the stimulus amplitude and repeat the process.

[0070] Peak-to-trough interval consistency can include the consistency of timing between peaks and troughs, such as timing between consecutive peaks, timing between consecutive troughs, and / or timing between consecutive peaks and troughs. In some examples, processing circuitry 80 can determine peak-to-trough interval consistency by comparing peak-to-trough intervals in the signal over time. More consistent peak-to-trough intervals may be associated with higher values, and less consistent peak-to-trough intervals may be associated with lower values. Processing circuitry 80 can compare the peak-to-trough interval consistency of the bioimpedance signal associated with stimulus amplitude to a peak-to-trough interval consistency threshold window. The threshold window may be defined by an upper threshold and a lower threshold. The threshold window may be associated with a range of values ​​for which peak-to-trough interval consistency meets quality criteria, and also with power savings. If the peak-to-trough interval consistency is within the peak-to-trough interval consistency threshold window, processing circuitry 80 can determine to set the stimulus amplitude. Otherwise, processing circuitry 80 can adjust the stimulus amplitude and repeat the process.

[0071] The treatment delivery circuit 86 is electrically coupled to electrodes 40, 42, 44, 46, 48, 50, 58, 62, 64, and 66, for example, via conductors of the respective leads 18, 20, 22, or, in the case of housing electrodes 58, via electrical conductors disposed within the housing 60 of the IMD 16. In the illustrated example, the treatment delivery circuit 86 is configured to generate and deliver electrical therapy to the heart 12. For example, the treatment delivery circuit 86 may deliver a defibrillation shock to the heart 12 via at least two electrodes 58, 62, 64, and 66. The treatment delivery circuit 86 may 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 treatment 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.

[0072] 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.

[0073] Sensing circuitry 82 monitors signals from at least one of electrodes 40, 42, 44, 46, 48, 50, 58, 62, 64, or 66 to monitor cardiac bioimpedance signals and / or electrical activity of heart 12, patient 14 respiration, or other patient parameters, 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 circuitry 82 may include one or more filters, amplifiers, analog-to-digital converters, or other sensing circuitry.

[0074] The sensing circuit 82 may also include a switching module to select which of the available electrodes to use to sense 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.

[0075] Processing circuit 80 can be configured to identify the inspiratory and / or expiratory phases of a patient based on a bioimpedance signal, an EGM signal, or another physiological signal. To identify the inspiratory and / or expiratory phases, processing circuit 80 can, for example, detect peaks and troughs in the bioimpedance characteristics of the EGM signal and / or peaks and troughs in the respiratory characteristics, for example, by identifying a zero-slope point (a zero-crossing point in the derivative or differential of the signal) 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 an interval or window from the identified peak to the subsequent trough, and the inspiratory phase as an 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, processing circuit 80 can determine tidal volume based on the peak-to-trough amplitude, which may vary with tidal volume.

[0076] 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 use one or more of the sensors 84 to identify the inspiratory and / or expiratory phases. For example, processing circuitry 80 may use accelerometer signal data to identify inspiratory and / or expiratory phases. In some examples, processing circuitry 80 may use accelerometer signal data to identify inspiratory and / or expiratory phases as a supplement to or alternative to bioimpedance and / or EGM signal data. In some examples, local minima and local maxima in the accelerometer signals may indicate the onset of the inspiratory and expiratory phases, respectively.

[0077] 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.

[0078] 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.

[0079] 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.

[0080] 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 tachyarrhythmic 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 multiple recirculation 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 interruptions to determine whether the patient's heart 12 is currently exhibiting atrial or ventricular tachyarrhythmias.

[0081] 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 is less than 220 milliseconds (ms) and fibrillation when the interval length is less than 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.

[0082] 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.

[0083] 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.

[0084] 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.

[0085] 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 can communicate 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.

[0086] Figure 4 This is a flowchart illustrating example operation of a device for adjusting the rate of cardiac pacing to simulate RSA according to one or more techniques of this disclosure. 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.

[0087] 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 physiological signals (e.g., bioimpedance signals) from the patient 14, indicating respiratory information, i.e., inspiratory and expiratory phase information. The processing circuitry 80 identifies the start of the inspiratory phase of the patient 14 (402). In some examples, to identify the start of the inspiratory phase, the processing circuitry 80 identifies a valley or local minimum in the bioimpedance signal. Based on the identification of the start of the inspiratory phase of the patient 14, the processing circuitry 80 controls the treatment delivery circuitry 86 to adjust the rate of the cardiac pacing pulses during the inspiratory phase, e.g., to increase the rate of the cardiac pacing pulses relative to a baseline pacing rate or intrinsic pacing rate (404). Optionally, the processing circuitry 80 may identify the start of the expiratory phase of the patient 14 (406). In some examples, to identify the onset of inspiration during the expiratory phase, processing circuitry 80 identifies peaks or local maxima in the bioimpedance signal. Based on the identification of the onset of the expiratory phase in patient 14, processing circuitry 80 controls treatment delivery circuitry 86 to adjust the rate of cardiac pacing pulses during the expiratory phase, for example, by returning pacing to a baseline or intrinsic pacing rate, or otherwise reducing the pacing rate relative to the pacing rate during the inspiratory phase (408). In some examples, processing circuitry 80 may control treatment delivery circuitry 86 to adjust the rate of cardiac pacing pulses throughout the entire duration of the respiratory cycle associated with the inspiratory phase. Although in Figure 4 The description of identifying the start of the exhalation phase is optional, but in other examples, the processing circuit 80 may identify the exhalation phase, and identifying the inhalation phase may be optional.

[0088] 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. 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 bioimpedance signal, which indicates respiratory information, i.e., inspiratory and expiratory phase information. The processing circuitry 80 identifies the start of the patient's inspiratory phase (502). In some examples, identifying the start of a previous inspiratory phase includes identifying a trough or local minimum in the bioimpedance signal. The processing circuitry 80 additionally identifies the start of the expiratory phase (504). The processing circuitry 80 continuously determines the patient's heart rate (506). Based on the heart rate during the inspiratory and expiratory phases, the processing circuitry 80 determines, for example, whether the patient 14 is achieving RSA by determining whether the heart rate during the inspiratory phase increases relative to the expiratory phase, for example, at least once per minute (508). If processing circuit 80 determines that patient 14 has not achieved RSA (508 "No"), processing circuit 80 controls treatment delivery circuit 86 to adjust cardiac pacing pulses to simulate RSA, for example, based on RSA pacing parameter 96 (510). Processing circuit 80 continues the example operation. If processing circuit 80 determines that patient 14 is achieving RSA (512 "Yes"), the process continues.

[0089] 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 baseline heart rate) during the expiratory phase.

[0090] Figure 6This is a flowchart illustrating example operations of determining whether to switch from sensing a bioimpedance signal to sensing an EGM signal to identify respiratory information (i.e., the inspiratory and expiratory phases) according to one or more techniques of this disclosure. In some examples, the bioimpedance signal may be more noise-resistant than other signals, such as the EGM signal, which require less battery power. In some examples, the EGM signal may be particularly susceptible to noise-related sensing problems when the patient is active and less susceptible to noise-related sensing problems when the patient is inactive (e.g., sleeping or resting). Processing circuitry 80 determines the patient's activity level (602). In some examples, processing circuitry 80 determines the patient's activity level based on accelerometer signal data (e.g., the accelerometer of sensor 84) and / or based on the patient's heart rate. Processing circuitry determines whether the patient's activity level meets a threshold activity level (604). If the patient's activity level does not meet the threshold ("No" in 604), the process continues. If the patient's activity level does indeed meet the threshold ("Yes" in 604), the processing circuitry 80 can control the sensing circuitry 82 to switch from sensing the bioimpedance signal to sensing the EGM signal to identify respiratory information (606). By switching from sensing the bioimpedance signal to sensing the EGM signal during periods of relatively low patient activity, the technology of this disclosure can advantageously save battery power, which can increase the lifespan of the IMD 16. After switching to sensing the EGM signal, the processing circuitry 80 can continuously determine whether to switch back to sensing the bioimpedance signal based on the patient's activity level and / or based on the signal quality of the EGM signal falling below a quality threshold (608).

[0091] Figure 7 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 7 Example operations can be in Figure 5 In 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 (704). 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.

[0092] If the average heart rate exceeds the threshold heart rate value ("Yes" in 704), the processing circuit 80 determines not to control the treatment delivery 86 circuit to adjust the cardiac pacing pulse to simulate RSA (708). If the average heart rate does not exceed the threshold heart rate value ("No" in 704), the processing circuit 80 controls the treatment 86 to adjust the cardiac pacing pulse to simulate RSA (706).

[0093] Figure 8This is a flowchart illustrating example operations for identifying valleys and peaks in a bioimpedance signal according to one or more techniques of this disclosure. Processing circuitry 80 determines one or more bioimpedance signal characteristics, such as maximum signal amplitude (802). In some examples, processing circuitry 80 stores one or more bioimpedance signal characteristics in patient parameter data 92. In some examples, processing circuitry 80 determines a baseline signal or other information for use in peak and valley detection based on one or more signal characteristics. As part of a valley detection process 818, processing circuitry 80 determines the difference between consecutive samples of bioimpedance signal data (806). Processing circuitry 80 determines, for example, whether the difference between consecutive samples indicates a valley in the signal by determining whether the difference changes from a negative value to 0 or a positive value (808). If the difference does not indicate a valley ("No" in 808), processing circuitry 80 continues to determine the difference between consecutive samples (806). If the difference indicates a valley ("Yes" in 808), processing circuitry 80 records the valley (810) and continues to determine the difference between consecutive samples (812) as part of a peak detection process 820. In some examples, processing circuit 80 determines a difference indicating a peak based on the change of the difference in consecutive samples from negative or 0 to positive. Processing circuit 80 additionally continues to determine the difference between consecutive samples (806) in the valley detection process 818. In some examples, processing circuit 80 may skip data for a period of time (e.g., 2 seconds) before continuing to determine the difference between consecutive samples (806) to, for example, prevent the same valley from being identified and recorded multiple times. Processing circuit 80 determines whether the difference between consecutive samples indicates a peak in the signal (814). If the difference does not indicate a peak ("No" in 814), processing circuit 80 continues to determine the difference between consecutive samples (812). If the difference indicates a peak ("Yes" in 814), processing circuit 80 records the peak (816) and continues to determine the difference between consecutive samples (806) in the valley detection process 818. In some examples, processing circuit 80 may apply one or more thresholds during the peak and valley detection process to prevent erroneous peak and valley detection caused by noise or other sensing problems. For example, processing circuit 80 can determine whether a sample meets or exceeds a threshold amplitude by comparing the sample amplitude with a threshold amplitude. In some examples, to verify that a true peak has occurred, processing circuit 80 can compare the sample amplitude with a threshold amplitude. In some examples, the threshold amplitude is based on one or more signal characteristics. For example, the threshold amplitude may be based on a previously identified maximum amplitude of the signal; for example, the threshold amplitude may be 50% of the maximum amplitude value or some other percentage.

[0094] Figure 9This is a graph illustrating example bioimpedance signals including information on the inspiratory and expiratory phases according to one or more techniques of this disclosure. In some examples, to stimulate and sense the bioimpedance signal, the IMD 16 is stimulated via a ring electrode (e.g., electrode 40) located in RV 28 and a ring electrode (e.g., electrode 44) located in LV 32, and the bioimpedance signal is sensed via a tip electrode (e.g., electrode 42) located in RV 28 and a tip electrode (e.g., electrode 46) located in LV 32. The IMD 16 may also be stimulated via a tip electrode (e.g., electrode 42) located in RV 28 and a coil electrode (e.g., electrode 62) located in RV 28, and the bioimpedance signal may be sensed via a ring electrode (e.g., electrode 40) located in RV 28 and a coil electrode (e.g., electrode 62) located in RV 28. The IMD 16 can also be stimulated via a tip electrode (e.g., electrode 50) located in the right atrium 26 and a tip electrode (e.g., electrode 42) located in the RV 28, and can sense bioimpedance signals via a ring electrode (e.g., electrode 48) located in the right atrium 26 and a ring electrode (e.g., electrode 40) located in the RV 28. Other sensing and stimulating electrode configurations are also possible. A trough 904 or local minimum of the bioimpedance signal 900 indicates the start of the inspiratory phase. A peak 902 or local maximum of the bioimpedance signal 900 indicates the start of the expiratory phase. In some examples, the processing circuit 80 is configured to identify the inspiratory and / or expiratory phases based on peaks (such as peak 902) and troughs (such as trough 904). The processing circuit 80 can use Figure 8 The example operations are used to identify peaks and valleys.

[0095] Figure 10 This is a flowchart illustrating example operation of selecting one or more stimulation parameters to sense a bioimpedance signal according to one or more techniques of this disclosure. The processing circuitry 80 may perform this operation periodically and / or in response to sensed signals (e.g., sensed changes in patient activity level / posture or changes in heart rate or baseline heart rate). Figure 10Example operation. In some examples, to stimulate and sense bioimpedance signals, the IMD 16 is stimulated via a loop electrode (e.g., electrode 40) located in RV 28 and a loop electrode (e.g., electrode 44) located in LV 32, and senses bioimpedance signals via a tip electrode (e.g., electrode 42) located in RV 28 and a tip electrode (e.g., electrode 46) located in LV 32. The IMD 16 can also be stimulated via a tip electrode (e.g., electrode 42) located in RV 28 and a coil electrode (e.g., electrode 62) located in RV 28, and can sense bioimpedance signals via a loop electrode (e.g., electrode 40) located in RV 28 and a coil electrode (e.g., electrode 62) located in RV 28. The IMD 16 can also be stimulated via a tip electrode (e.g., electrode 50) located in the right atrium 26 and a tip electrode (e.g., electrode 42) located in the RV 28, and bioimpedance signals can be sensed via a ring electrode (e.g., electrode 48) located in the right atrium 26 and a ring electrode (e.g., electrode 40) located in the RV 28. Other sensing and stimulating electrode configurations are also possible.

[0096] In some examples, processing circuitry 80 is configured to select one or more stimulation parameters for a predetermined sensing and stimulation configuration. In other examples, processing circuitry 80 may select a sensing and stimulation configuration based on a sensing and stimulation configuration that achieves a bioimpedance signal satisfying one or more quality and / or periodicity thresholds. In some examples, processing circuitry 80 may initially select a sensing and stimulation configuration and switch to a different sensing and stimulation configuration in response to the sensing and stimulation configuration failing to produce a bioimpedance signal satisfying one or more quality and / or periodicity thresholds. For one or more of the possible sensing and stimulation electrode configurations, processing circuitry 80 controls one or more electrodes to stimulate at multiple stimulation amplitudes (1002). In some examples, the multiple stimulation amplitudes may be in the range of stimulation amplitudes, for example, from 0.5 μA to 10 μA. Sensing circuitry 82 may sense each of the multiple bioimpedance signals corresponding to the multiple stimulation amplitudes. For each of the multiple stimulation amplitudes, processing circuitry 80 receives the corresponding bioimpedance signal, for example, for a certain number of respiratory cycles (such as 10 cycles) or a certain time period (such as 30 seconds to 60 seconds) (1004). For each of a plurality of corresponding bioimpedance signals, processing circuit 80 compares the bioimpedance signal to one or more quality and / or periodicity thresholds (1006). The one or more quality and / or periodicity thresholds may include one or more of the following: the standard deviation of the interval between consecutive trough thresholds (e.g., 60 ms), the standard deviation of the interval between consecutive peak thresholds (e.g., 60 ms), the coefficient of variation of amplitude at each peak in the bioimpedance signal thresholds (e.g., 25), the coefficient of variation of amplitude at each trough in the bioimpedance signal thresholds (e.g., 25), and / or the difference between the mean peak amplitude and the mean trough amplitude threshold, for example, to measure the bioimpedance signal strength. In some examples, the one or more quality and / or periodicity thresholds may additionally or alternatively include one or more of an average dynamic range threshold window, a peak / trough consistency threshold window, or a peak-to-trough interval consistency threshold window. In some examples, processing circuit 80 may optionally determine the minimum stimulation amplitude at which the corresponding bioimpedance signal satisfies one or more quality and / or periodicity thresholds (1008). Processing circuit 80 selects a stimulation amplitude (1010) from a plurality of stimulation amplitudes that corresponds to a bioimpedance signal that satisfies one or more quality thresholds for stimulation. In an example where processing circuit 80 determines the lowest stimulation amplitude when the corresponding bioimpedance signal satisfies one or more quality and / or periodicity thresholds, processing circuit 80 may select the lowest stimulation amplitude for stimulation at step 1010, for example, to save battery life. In other examples, processing circuit 80 may select a stimulation amplitude other than the lowest stimulation amplitude, wherein the corresponding bioimpedance signal satisfies the quality and / or periodicity thresholds.For example, the processing circuit 80 can determine that the second minimum stimulation amplitude is associated with a bioimpedance signal with high signal quality, and can select the second minimum stimulation amplitude.

[0097] In some examples, the processing circuit 80 may implement a cost function to select the stimulus amplitude. The inputs to the cost function may include one or more of the following, for example: for each of a plurality of stimulus amplitudes, the standard deviation of the interval between consecutive peaks, the standard deviation of the interval between consecutive peaks, the coefficient of variation of the amplitude at each peak in the bioimpedance signal, the coefficient of variation of the amplitude at each trough in the bioimpedance signal, and / or the difference between the mean peak amplitude and the mean trough amplitude.

[0098] Figure 11 This is a flowchart illustrating example operations of adjusting the rate of cardiac pacing pulses based on patient status according to one or more techniques of this disclosure. 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 progression and / or hypertension). Based on patient parameter data 92, processing circuitry 80 determines the patient status (1102). Based on the patient status, processing circuitry 80 may adjust the rate of cardiac pacing pulses (1104).

[0099] In an example where the patient's condition is based on their 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 a bioimpedance 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 relative to a baseline heart rate or pacing expiratory heart rate within a certain range (e.g., 5 to 20 heartbeats per minute) during the inspiratory phase. Based on the patient's activity level, processing circuitry 80 may determine to adjust cardiac pacing pulses to overdrive pacing 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).

[0100] In an example where the patient's condition is based on disease progression, processing circuitry 80 may determine disease progression based on, for example, a heart failure (HF) risk level. Processing circuitry 80 may determine to adjust 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 first (e.g., relatively low) HF risk level different from the first HF risk level.

[0101] In some examples, for instance, if patient 14's average heart rate is close to the upper limit tracking rate value (e.g., Figure 6 If the threshold in step 604 is used, 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 that range, such as 5 heartbeats per minute) to, for example, ensure that the patient's average heart rate does not exceed the upper limit tracking rate value. The threshold in step 604 is provided as an example only. In other examples, the upper limit tracking rate value includes values ​​other than, for example, values ​​higher or lower than the threshold in step 604.

[0102] 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.

[0103] Figure 12 This is a flowchart illustrating an example operation of adjusting cardiac pacing pulses based on predicted inspiratory and expiratory phases, according to one or more techniques of this disclosure. Figure 12 The technology can be used as Figure 6 This can be used as a supplement or alternative to other technologies to perform the procedure. In some examples, bioimpedance signals or other methods may be used. Figure 6 The EGM signal is used to execute Figure 12The technology involves predicting subsequent inspiratory and / or expiratory phases to control the treatment delivery circuitry to adjust cardiac pacing pulses, for example, to simulate RSA. In some examples, intermittently predicting inspiratory and / or expiratory phases and / or predicting inspiratory and / or expiratory phases over extended periods (e.g., as an alternative to identifying each inspiratory and / or expiratory phase) can conserve battery life of the IMD 16. In some examples, to determine the predicted subsequent inspiratory and / or expiratory phases, the processing circuitry 80 can determine that the patient 14's activity level is below a predicted threshold, such as the activity level threshold in step 604. For example, when the patient 14 is resting (e.g., sleeping), the patient 14's activity level may be below the predicted threshold. Additionally or alternatively, when the patient's heart rate is below a threshold heart rate (e.g., 75 beats per minute, 70 beats per minute, or 65 beats per minute), and / or when the patient's heart rate has not changed beyond a change threshold (e.g., 5 beats per minute), the processing circuit 80 may determine to predict inhalation and / or exhalation. In some examples, the processing circuit 80 may determine to predict inhalation and / or exhalation intermittently, for example, predicting every three inhalations. In some examples, the processing circuit 80 predicts inhalation and / or exhalation over extended periods of time (e.g., when the patient is resting). The processing circuit 80 predicts the onset and / or duration of a subsequent inhalation phase based on one or more previous inhalation and / or exhalation phases (1202). The processing circuit 80 predicts the onset and / or duration of a subsequent exhalation phase based on one or more previous expiratory and / or inhalation phases (1204). Based on the predicted inspiratory and / or expiratory phases, processing circuitry 80 can control the treatment delivery circuitry to adjust the cardiac pacing pulses, for example, to simulate RSA (1206). In some examples, processing circuitry 80 determines that the patient 14's activity level has exceeded a prediction threshold and can switch back to sensing all inspiratory and / or expiratory phases. In some examples, processing circuitry 80 can determine that these predictions do not meet an accuracy threshold and can switch back to sensing all inspiratory and / or expiratory phases; that is, processing circuitry 80 can stop predicting subsequent inspiratory and expiratory phases.

[0104] Figure 13 This is a flowchart illustrating example operation of one or more techniques according to this disclosure for dynamically adjusting one or more stimulation parameters (e.g., stimulation amplitude) to sense bioimpedance signals. The processing circuitry 80 may perform this operation periodically (e.g., hourly, daily, or weekly) and / or in response to sensed signals (e.g., sensed changes in patient activity level / posture or changes in heart rate or baseline heart rate). Figure 13Example operation. In some examples, to stimulate and sense the bioimpedance signal, the therapeutic delivery circuit 86 of the IMD 16 is stimulated via a loop electrode (e.g., electrode 40) located in RV 28 and / or a loop electrode (e.g., electrode 44) located in LV 32, and senses the bioimpedance signal via a tip electrode (e.g., electrode 42) located in RV 28 and a tip electrode (e.g., electrode 46) located in LV 32. The IMD 16 may also be stimulated via a tip electrode (e.g., electrode 42) located in RV 28 and / or a coil electrode (e.g., electrode 62) located in RV 28, and may sense the bioimpedance signal via a loop electrode (e.g., electrode 40) located in RV 28 and / or a loop electrode (e.g., electrode 62) located in RV 28. The IMD 16 can also be stimulated via a tip electrode (e.g., electrode 50) located in the right atrium 26 and / or a tip electrode (e.g., electrode 42) located in the RV 28, and can sense bioimpedance signals via a ring electrode (e.g., electrode 48) located in the right atrium 26 and / or a ring electrode (e.g., electrode 40) located in the RV 28. Other sensing and stimulating electrode configurations are also possible.

[0105] In some examples, processing circuitry 80 is configured to select one or more stimulation parameters for a predetermined sensing and stimulation configuration. In other examples, processing circuitry 80 may select a sensing and stimulation configuration based on a sensing and stimulation configuration that achieves a bioimpedance signal satisfying one or more quality and / or periodicity thresholds. In some examples, processing circuitry 80 may initially select a sensing and stimulation configuration and switch to a different sensing and stimulation configuration in response to the sensing and stimulation configuration failing to produce a bioimpedance signal satisfying one or more quality and / or periodicity thresholds. Processing circuitry 80 measures an impedance signal associated with the stimulation amplitude (1302). In some examples, the stimulation amplitude value is in, for example, a stimulation amplitude range from 0.5 μA to 10 μA. Sensing circuitry 82 senses the bioimpedance signal corresponding to the stimulation amplitude. The duration of the bioimpedance signal may correspond to a number of respiratory cycles (such as 10 cycles) or a time period (such as 30 to 60 seconds). Processing circuitry 80 determines one or more characteristics of the bioimpedance signal (1304). In some examples, the one or more features may include one or more of the following: average dynamic range, peak / valley consistency, or peak-to-valley interval consistency.

[0106] Average dynamic range can include the average ratio between the maximum and minimum measurable signal levels of a bioimpedance signal. In some examples, average dynamic range can be measured in decibels. A relatively high average dynamic range indicates good signal quality, and a relatively low average dynamic range indicates poor signal quality. Peak / valley consistency can include the consistency of peak / valley amplitudes. In some examples, processing circuitry 80 can determine peak / valley consistency by comparing peak / valley amplitudes in the signal over time. More consistent peak / valley amplitudes can be associated with higher values ​​and good signal quality, and less inconsistent peak / valley amplitudes can be associated with lower values ​​and poor signal quality. Peak-to-valley interval consistency can include the consistency of timing between peaks and valleys, such as timing between consecutive peaks, timing between consecutive valleys, and / or timing between consecutive peaks and valleys. In some examples, processing circuitry 80 can determine peak-to-valley interval consistency by comparing peak-to-valley intervals in the signal over time. More consistent peak-to-valley intervals can be associated with higher values ​​and good signal quality, and less inconsistent peak-to-valley intervals can be associated with lower values ​​and poor signal quality.

[0107] In some examples, to select one or more sensing and stimulation parameters (e.g., stimulation amplitude), processing circuitry 80 can control treatment delivery circuitry 86 to fine-tune the stimulation amplitude until one or more characteristics of the bioimpedance signal (e.g., average dynamic range, peak / valley consistency, and / or peak-to-valley interval consistency) fall within one or more corresponding threshold windows. Processing circuitry 80 can compare the average dynamic range of the bioimpedance signal associated with the stimulation amplitude with an average dynamic range threshold window. The threshold window can be defined by an upper threshold and a lower threshold. The threshold window can be associated with a range of values ​​for which the average dynamic range meets quality criteria and is also associated with power savings.

[0108] The processing circuit 80 can compare the peak / valley consistency of the bioimpedance signal associated with the stimulus amplitude with a peak / valley consistency threshold window. The threshold window can be defined by an upper threshold and a lower threshold. The threshold window can be associated with a range of values ​​for which peak / valley consistency meets quality criteria, and also with power savings.

[0109] The processing circuit 80 can compare the peak-to-trough consistency of the bioimpedance signal associated with the stimulus amplitude with a peak-to-trough consistency threshold window. The threshold window can be defined by an upper threshold and a lower threshold. The threshold window can be associated with a range of values ​​for which the peak-to-trough consistency meets quality criteria, and also with power savings.

[0110] In examples where one or more features include more than one feature (e.g., three features), the techniques of this disclosure may include adjusting the stimulus amplitude in response to all features indicating adjustment (e.g., increasing or decreasing). Alternatively, the techniques of this disclosure may include adjusting the stimulus amplitude in response to a majority of features (e.g., at least two of three features) indicating adjustment (e.g., increasing or decreasing). In some examples, the techniques may include weighting each of the one or more features. As an example, the dynamic range feature may be assigned a higher weight than the peak / valley consistency feature and the peak-to-valley interval consistency feature. Processing circuitry 80 may determine a score based on the weighted features. Based on a comparison of the score with one or more thresholds (e.g., a decrease amplitude threshold and an increase amplitude threshold), processing circuitry 80 may determine whether to increase the stimulus amplitude, maintain the stimulus amplitude, or decrease the stimulus amplitude.

[0111] For each of one or more features, processing circuit 80 determines whether the feature value of the bioimpedance signal associated with the stimulus amplitude is greater than the corresponding lower threshold of the corresponding threshold window (1306). If the feature value is less than the lower threshold ("No" in 1306), processing circuit 80 determines whether the stimulus amplitude value is less than the maximum stimulus amplitude value associated with the range of stimulus amplitude values, such as 10 microamps (1308). If the stimulus amplitude is less than the maximum stimulus amplitude value ("Yes" in 1308), processing circuit 80 determines to control treatment delivery circuit 86 to increase the stimulus amplitude (1310). In an example where there is more than one feature, processing circuit 80 may increase only the stimulus amplitude if the feature of the threshold number indicates an increase in stimulus amplitude or if the weighted score associated with the feature satisfies an increase in the stimulus threshold. Processing circuit 80 then controls sensing circuit 82 to measure the bioimpedance associated with the increased stimulus amplitude (1302). If the stimulus amplitude is not less than the maximum stimulus amplitude value, for example, if the stimulus amplitude is equal to the maximum stimulus amplitude value ("No" in 1308), processing circuit 80 determines to maintain the stimulus amplitude value (1312). In examples with more than one feature, if the feature indicating the threshold number maintains the stimulus amplitude, or if the weighted score associated with the feature falls within the range defined by increasing and decreasing the stimulus window, then the processing circuit 80 may maintain only the stimulus amplitude. In some examples, if the stimulus amplitude is set to the maximum stimulus amplitude value and the feature is greater than the lower threshold, the processing circuit 80 may switch to sensing different signals, switch to different sensing configurations, and / or output an indication to the user.

[0112] If the feature value is greater than the lower threshold ("Yes" in 1306), then processing circuit 80 determines whether the feature value is greater than the corresponding upper threshold of the corresponding threshold window (1314). If the feature value is less than the upper threshold ("No" in 1314), then processing circuit 80 determines to maintain the stimulus amplitude value (1312). In this type of example, the feature value is within the threshold window. In examples where there is more than one feature, if the number of features indicates maintaining the stimulus amplitude, or if the weighted score associated with the feature falls within the range defined by increasing and decreasing the stimulus window, then processing circuit 80 may maintain only the stimulus amplitude.

[0113] If the feature value is greater than the upper threshold ("Yes" in 1314), then processing circuit 80 determines whether the stimulus amplitude is greater than the minimum stimulus amplitude value associated with the stimulus amplitude value range, for example, 0.5 microamps (1316). If the stimulus amplitude is not greater than the minimum stimulus amplitude value, for example, if the stimulus amplitude is equal to the minimum stimulus amplitude value ("No" in 1316), then processing circuit 80 determines to maintain the stimulus value (1312). In examples where there is more than one feature, if the number of features indicates that the stimulus amplitude should be maintained, or if the weighted score associated with the feature falls within the range defined by the increasing and decreasing stimulus windows, then processing circuit 80 may maintain only the stimulus amplitude.

[0114] If the stimulation amplitude is greater than the minimum stimulation amplitude value ("Yes" in 1316), then processing circuit 80 determines to control treatment delivery circuit 86 to reduce the stimulation amplitude (1318). In an example where there is more than one feature, processing circuit 80 may reduce only the stimulation amplitude if the feature indicating the number of thresholds indicates a reduction in stimulation amplitude or if the weighted score associated with the feature satisfies a reduction in stimulation threshold. Processing circuit 80 then controls sensing circuit 82 to measure the bioimpedance associated with the reduced stimulation amplitude (1302).

[0115] In some examples, processing circuitry 80 may apply hysteresis to prevent frequent transitions associated with changes in stimulus amplitude from disrupting signal processing. In some examples, processing circuitry 80 may store diagnostic values ​​in memory 90 indicating which stimulus amplitudes have been used and / or the frequency at which each stimulus amplitude has been used. Based on the diagnostic values, processing circuitry 80 may estimate battery life. For example, if IMD 16 uses relatively high stimulus amplitude values, the battery life may be shorter than if IMD 16 uses relatively low stimulus amplitude values. In some examples, diagnostic values ​​may be combined with diagnostic values ​​for other patients. In some examples, diagnostic values ​​may be used for research. As an example, diagnostic values ​​may be used to determine initial and / or default stimulus values ​​based on patient type (e.g., patient disease state, patient comorbidities, patient age, patient sex, and / or patient ethnicity) for use in future algorithms. For example, processing circuitry 80 may send diagnostic values ​​to external device 24 and / or a computing system (not depicted) to determine or adjust initial and / or default stimulus values ​​for similar patients.

[0116] Although the main description is about adjusting the magnitude of the stimulus Figure 13 The example operation is shown, but the technology disclosed herein is not limited thereto. For example, the processing circuit 80 may implement... Figure 13 Example operations are provided to set the measurement frequency (e.g., between 16 Hz and 32 Hz) or any other sensing and stimulation parameters.

[0117] 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 a bioimpedance signal from the patient; and a processing circuit configured to: identify the start of a current inspiratory phase of the patient based on the bioimpedance signal; and control the treatment delivery circuit to adjust the rate of cardiac pacing during the current inspiratory phase based on the identification of the start of the current inspiratory phase.

[0118] Example 2. The apparatus according to Example 1, wherein the processing circuitry is further configured to: after the current inspiratory phase, identify the start of the patient's current expiratory phase based on the bioimpedance signal; and control the treatment delivery circuitry to perform either: reduce the rate of cardiac pacing during the current expiratory phase relative to the rate associated with the current inspiratory phase; or stop providing cardiac pacing at the rate associated with the current inspiratory phase during the current expiratory phase.

[0119] Example 3. The apparatus according to any one or more of Examples 1 to 2, wherein the processing circuitry is further configured to: determine a patient activity level; and, in response to the patient activity level being below a threshold activity level, control the sensing circuitry to switch to sensing the patient’s electrogram (EGM) signal to identify the start of the current inspiratory phase.

[0120] Example 4. The apparatus according to any one or more of Examples 1 to 3, wherein adjusting the rate of the cardiac pacing includes: making the delivery of the cardiac pacing pulse more closely mimic respiratory sinus arrhythmia (RSA).

[0121] Example 5. The apparatus according to any one or more of Examples 2 to 4, wherein the processing circuitry is further configured to: determine a patient's heart rate; determine that the patient has not reached an RSA based on the patient's heart rate and one or more of a previous inspiratory phase or a previous expiratory phase; and control the treatment delivery circuitry to adjust the rate of cardiac pacing during one or more of the current inspiratory phase or the current expiratory phase based on the determination that the patient has not reached an RSA.

[0122] Example 6. The apparatus according to any one or more of Examples 1 to 5, wherein the processing circuit is further configured to: receive a sensed bioimpedance signal during an initialization phase; and determine at least one signal characteristic based on the sensed bioimpedance signal.

[0123] Example 7. The apparatus according to any one or more of Examples 1 to 6, wherein the processing circuit is further configured to: compare an average 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.

[0124] Example 8. The apparatus according to any one or more of Examples 1 to 7, wherein the processing circuitry is configured to select one or more stimulation parameters for sensing the bioimpedance signal.

[0125] Example 9. The apparatus according to Example 8, wherein selecting one or more stimulation parameters includes selecting a stimulation amplitude, and wherein, in order to select the stimulation amplitude, the processing circuit is configured to: control one or more of the plurality of electrodes to stimulate with a plurality of stimulation amplitudes; determine, for each of the plurality of stimulation amplitudes, whether a corresponding bioimpedance signal satisfies one or more quality thresholds; and select the stimulation amplitude from the plurality of stimulation amplitudes in response to the corresponding bioimpedance signal satisfying the one or more quality thresholds.

[0126] Example 10. The apparatus according to Example 9, wherein the processing circuit is further configured to: determine the minimum stimulation amplitude when the corresponding bioimpedance signal satisfies the one or more quality thresholds; and select the minimum stimulation amplitude when the corresponding bioimpedance signal satisfies the one or more quality thresholds.

[0127] Example 11. The apparatus according to any one of Examples 1 to 10, wherein the processing circuit is further configured to: determine a patient state; and control the treatment delivery circuit to adjust the rate of the cardiac pacing pulse based on the patient state.

[0128] Example 12. The device according to Example 11, wherein the patient state includes one or more of the following: patient disease state; or patient activity level.

[0129] Example 13. The apparatus according to any one or more of Examples 2 to 12, wherein the processing circuitry is further configured to: predict a subsequent inspiratory phase based on a previous inspiratory phase; predict a subsequent expiratory phase based on a previous expiratory phase; and control the treatment delivery circuitry to deliver the cardiac pacing pulses during the subsequent inspiratory and expiratory phases to simulate respiratory sinus arrhythmia (RSA) based on the previous inspiratory and expiratory phases.

[0130] Example 14. The device according to any one or more of Examples 1 to 13, wherein the device includes a pacemaker.

[0131] Example 15. A method comprising: sensing a patient's bioimpedance signal by a sensing circuit of a medical device; identifying the start of a current inspiratory phase of the patient by a processing circuit of the medical device based on the bioimpedance signal; and controlling a therapeutic delivery circuit of the medical device by the processing circuit to adjust the rate of cardiac pacing during the current inspiratory phase, wherein the therapeutic delivery circuit is configured to deliver cardiac pacing pulses to the patient's heart via a plurality of electrodes based on the identification of the start of the current inspiratory phase.

[0132] Example 16. The method according to Example 15, the method further comprising: after the current inspiratory phase, having the processing circuit identify the start of the patient's current expiratory phase based on the bioimpedance signal; and based on the identification of the start of the current expiratory phase, having the processing circuit control the treatment delivery circuit to perform either: reducing the rate of cardiac pacing during the current expiratory phase relative to the rate associated with the current inspiratory phase during the current expiratory phase; or stopping the delivery of cardiac pacing at the rate associated with the current inspiratory phase during the current expiratory phase.

[0133] Example 17. The method according to any one or more of Examples 15 to 16, the method further comprising: determining a patient activity level by the processing circuit; and controlling a sensing circuit to switch to sensing an electrophysiological (EGM) signal of the patient to identify the start of the current inspiratory phase in response to the processing circuit being below a threshold activity level.

[0134] Example 18. The method according to any one or more of Examples 15 to 17, wherein adjusting the rate of the cardiac pacing pulse comprises: making the delivery of the cardiac pacing pulse more closely mimic respiratory sinus arrhythmia (RSA).

[0135] Example 19. The method according to any one or more of Examples 16 to 18, the method further comprising: determining a patient's heart rate by the processing circuit; determining, based on the patient's heart rate and one or more of a previous inspiratory phase or a previous expiratory phase, that the patient has not reached an RSA; and controlling, based on the determination that the patient has not reached an RSA, the processing circuit to adjust the rate of cardiac pacing during one or more of the current inspiratory phase or the current expiratory phase.

[0136] Example 20. The method according to any one or more of Examples 15 to 19, the method further comprising: during an initialization phase, sensing the bioimpedance signal by the sensing circuit; and determining at least one signal characteristic by the processing circuit based on the sensed bioimpedance signal.

[0137] Example 21. The method according to any one or more of Examples 15 to 20, the method further comprising: comparing an average heart rate with a threshold by the processing circuit; and controlling the treatment delivery circuit to adjust the cardiac pacing pulse to simulate RSA in response to the average heart rate falling below the threshold by the processing circuit.

[0138] Example 22. The method according to any one or more of Examples 15 to 21, the method further comprising: selecting one or more stimulation parameters for sensing the bioimpedance signal by the processing circuit.

[0139] Example 23. The method according to Example 22, wherein selecting one or more stimulation parameters includes selecting a stimulation amplitude, wherein selecting the stimulation amplitude includes: controlling one or more of the plurality of electrodes to stimulate with a plurality of stimulation amplitudes by the processing circuit; for each of the plurality of stimulation amplitudes, determining by the processing circuit whether the corresponding bioimpedance signal satisfies one or more quality thresholds; and selecting the stimulation amplitude from the plurality of stimulation amplitudes by the processing circuit in response to the corresponding bioimpedance signal satisfying the one or more quality thresholds.

[0140] Example 24. According to the method of Example 23, the method further includes: determining by the processing circuit the minimum stimulation amplitude when the corresponding bioimpedance signal satisfies one or more quality thresholds; and selecting by the processing circuit the minimum stimulation amplitude when the corresponding bioimpedance signal satisfies one or more quality thresholds.

[0141] Example 25. The method according to any one of Examples 15 to 24, 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.

[0142] Example 26. The method according to Example 25, wherein the patient status includes one or more of the following: patient disease status; or patient activity level.

[0143] Example 27. The method according to any one or more of Examples 16 to 26, the method further comprising: predicting a subsequent inspiratory phase by the processing circuit based on a previous inspiratory phase; predicting a subsequent expiratory phase by the processing circuit based on a previous expiratory phase; and controlling the treatment delivery circuit by the processing circuit to deliver the cardiac pacing pulse during the subsequent inspiratory phase and the subsequent expiratory phase to simulate respiratory sinus arrhythmia (RSA) based on the previous inspiratory phase and the previous expiratory phase.

[0144] Example 28. The method according to any one or more of Examples 15 to 27, wherein the medical device includes a pacemaker.

[0145] Example 29. 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 a bioimpedance signal from the patient; and a processing circuit configured to: identify the start of a current expiratory phase of the patient based on the bioimpedance signal; and control the treatment delivery circuit to adjust the rate of cardiac pacing during a respiratory cycle associated with the current expiratory phase based on the identification of the start of the current expiratory phase.

[0146] Example 30. The apparatus according to Example 29, wherein the processing circuitry is further configured to: identify the start of the patient’s current inspiratory phase based on the bioimpedance signal; and control the treatment delivery circuitry to increase the rate of cardiac pacing during the current inspiratory phase relative to the rate associated with the current expiratory phase based on the identification of the start of the current inspiratory phase.

[0147] Example 31. The apparatus according to any one or more of Examples 29 to 30, wherein the processing circuitry is further configured to: determine a patient activity level; and, in response to the patient activity level being below a threshold activity level, control the sensing circuitry to switch to sensing the patient’s electrogram (EGM) signal to identify the start of the current expiratory phase.

[0148] Example 32. The apparatus according to any one or more of Examples 29 to 31, wherein adjusting the rate of the cardiac pacing includes: making the delivery of the cardiac pacing pulse more closely mimic respiratory sinus arrhythmia (RSA).

[0149] Example 33. An apparatus according to any one or more of Examples 30 to 32, wherein the processing circuitry is further configured to: determine a patient’s heart rate; determine that the patient has not reached an RSA based on the patient’s heart rate and one or more of a previous inspiratory phase or a previous expiratory phase; and control the treatment delivery circuitry to adjust the rate of cardiac pacing during one or more of the current inspiratory phase or the current expiratory phase based on the determination that the patient has not reached an RSA.

[0150] Example 34. An apparatus according to any one or more of Examples 29 to 33, wherein the processing circuit is configured to: receive a sensed bioimpedance signal during an initialization phase; and determine at least one signal characteristic based on the sensed bioimpedance signal.

[0151] Example 35. The apparatus according to any one or more of Examples 29 to 34, wherein the processing circuitry is further configured to: compare an average 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.

[0152] Example 36. The apparatus according to any one or more of Examples 29 to 35, wherein the processing circuitry is configured to select one or more stimulation parameters for sensing the bioimpedance signal.

[0153] Example 37. The apparatus according to Example 36, wherein selecting one or more stimulation parameters includes selecting a stimulation amplitude, and wherein, in order to select the stimulation amplitude, the processing circuitry is configured to: control one or more of the plurality of electrodes to stimulate with a plurality of stimulation amplitudes; determine, for each of the plurality of stimulation amplitudes, whether a corresponding bioimpedance signal satisfies one or more quality thresholds; and, in response to the corresponding bioimpedance signal satisfying the one or more quality thresholds, select the stimulation amplitude from the plurality of stimulation amplitudes.

[0154] Example 38. The apparatus according to Example 37, wherein the processing circuit is further configured to: determine the minimum stimulation amplitude when the corresponding bioimpedance signal satisfies the one or more quality thresholds; and select the minimum stimulation amplitude when the corresponding bioimpedance signal satisfies the one or more quality thresholds.

[0155] Example 39. The apparatus according to any one of Examples 29 to 38, 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.

[0156] Example 40. The device according to Example 39, wherein the patient state includes one or more of the following: patient disease state; or patient activity level.

[0157] Example 41. The apparatus according to any one or more of Examples 30 to 40, wherein the processing circuitry is further configured to: predict a subsequent inspiratory phase based on a previous inspiratory phase; predict a subsequent expiratory phase based on a previous expiratory phase; and control the treatment delivery circuitry to deliver the cardiac pacing pulses during the subsequent inspiratory and expiratory phases to simulate respiratory sinus arrhythmia (RSA) based on the previous inspiratory and expiratory phases.

[0158] Example 42. The device according to any one or more of Examples 29 to 41, wherein the device includes a pacemaker.

[0159] Example 43. A method comprising: sensing a patient's bioimpedance signal by a sensing circuit of a medical device; identifying the start of a current expiratory phase of the patient by a processing circuit of the medical device based on the bioimpedance signal; and controlling a treatment delivery circuit of the medical device by the processing circuit to adjust the rate of cardiac pacing during a respiratory cycle associated with the current expiratory phase, wherein the treatment delivery circuit is configured to deliver cardiac pacing pulses to the patient's heart via a plurality of electrodes based on the identification of the start of the current expiratory phase.

[0160] Example 44. The method according to Example 43, the method further comprising: identifying the start of the patient's current inspiratory phase by the processing circuit based on the bioimpedance signal; and controlling the treatment delivery circuit to increase the rate of cardiac pacing during the current inspiratory phase relative to the rate associated with the expiratory phase by the processing circuit based on the identification of the start of the current inspiratory phase.

[0161] Example 45. The method according to any one or more of Examples 43 to 44, the method further comprising: determining a patient activity level by the processing circuit; and controlling a sensing circuit to switch to sensing an electrophysiological (EGM) signal of the patient to identify the start of the current expiratory phase by the processing circuit in response to the patient activity level being below a threshold activity level.

[0162] Example 46. The method according to any one or more of Examples 43 to 45, wherein adjusting the rate of the cardiac pacing pulse comprises: making the delivery of the cardiac pacing pulse more closely mimic respiratory sinus arrhythmia (RSA).

[0163] Example 47. The method according to any one or more of Examples 44 to 46, the method further comprising: determining a patient's heart rate by the processing circuit; determining, based on the patient's heart rate and one or more of a previous inspiratory phase or a previous expiratory phase, that the patient has not reached an RSA; and controlling, based on the determination that the patient has not reached an RSA, the processing circuit to adjust the rate of cardiac pacing during one or more of the current inspiratory phase or the current expiratory phase.

[0164] Example 48. The method according to any one or more of Examples 43 to 47, the method further comprising: during an initialization phase, sensing the bioimpedance signal by the sensing circuit; and determining at least one signal characteristic by the processing circuit based on the sensed bioimpedance signal.

[0165] Example 49. The method according to any one or more of Examples 43 to 48, the method further comprising: comparing an average heart rate with a threshold by the processing circuit; and controlling the treatment delivery circuit to adjust the cardiac pacing pulse to simulate RSA in response to the average heart rate falling below the threshold by the processing circuit.

[0166] Example 50. The method according to any one or more of Examples 43 to 49, the method further comprising: selecting one or more stimulation parameters for sensing the bioimpedance signal by the processing circuit.

[0167] Example 51. The method according to Example 50, wherein selecting one or more stimulation parameters includes selecting a stimulation amplitude, wherein selecting the stimulation amplitude includes: controlling one or more electrodes of the plurality of electrodes to stimulate with a plurality of stimulation amplitudes by the processing circuit; for each of the plurality of stimulation amplitudes, determining by the processing circuit whether the corresponding bioimpedance signal satisfies one or more quality thresholds; and selecting a corresponding stimulation amplitude of the plurality of stimulation amplitudes by the processing circuit in response to the corresponding bioimpedance signal satisfying the one or more quality thresholds.

[0168] Example 52. According to the method of Example 51, the method further includes: determining by the processing circuit the minimum stimulation amplitude when the corresponding bioimpedance signal satisfies one or more quality thresholds; and selecting by the processing circuit the minimum stimulation amplitude when the corresponding bioimpedance signal satisfies one or more quality thresholds.

[0169] Example 53. The method according to any one of Examples 43 to 52, 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.

[0170] Example 54. The method according to Example 53, wherein the patient status includes one or more of the following: patient disease status; or patient activity level.

[0171] Example 55. The method according to any one or more of Examples 44 to 54, the method further comprising: predicting a subsequent inspiratory phase by the processing circuit based on a previous inspiratory phase; predicting a subsequent expiratory phase by the processing circuit based on a previous expiratory phase; and controlling the treatment delivery circuit by the processing circuit to deliver the cardiac pacing pulse during the subsequent inspiratory phase and the subsequent expiratory phase to simulate respiratory sinus arrhythmia (RSA) based on the previous inspiratory phase and the previous expiratory phase.

[0172] Example 56. The method according to any one or more of Examples 43 to 55, wherein the medical device includes a pacemaker.

[0173] Example 57. A non-transitory computer-readable medium storing instructions that, when executed by a processing circuit, cause the processing circuit to: identify the start of a patient’s current inspiratory phase based on a bioimpedance signal; and control a treatment delivery circuit to adjust the rate of cardiac pacing during the current inspiratory phase based on the identification of the start of the current inspiratory phase.

[0174] Example 58. A non-transitory computer-readable medium storing instructions that, when executed by a processing circuit, cause the processing circuit to: identify the start of a patient's current expiratory phase based on a bioimpedance signal; and control a treatment delivery circuit to adjust the rate of cardiac pacing during a respiratory cycle associated with the current expiratory phase based on the identification of the start of the current expiratory phase.

[0175] 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 bioimpedance signal; and Processing circuit, the processing circuit being configured to: The bioimpedance signal is used to identify the start of the patient's current inspiratory phase; and The treatment delivery circuit controls the rate of the cardiac pacing pulse during the current inspiratory phase based on the identifier of the start of the current inspiratory phase.

2. The apparatus of claim 1, wherein the processing circuit is further configured to: Following the current inspiratory phase, the start of the patient's current expiratory phase is identified based on the bioimpedance signal; and The treatment delivery circuit is controlled to perform any of the following based on the identifier indicating the start of the current exhalation phase: The rate of the cardiac pacing pulse during the current expiratory phase is reduced relative to the rate associated with the current inspiratory phase; or The cardiac pacing pulses are stopped during the current expiratory phase at the rate associated with the current inspiratory phase.

3. The apparatus according to any one or more of claims 1 to 2, wherein the processing circuit is further configured to: Determine the patient's activity level; and In response to the patient’s activity level being below a threshold activity level, the control sensing circuit switches to sensing the patient’s electrogram (EGM) signal to identify the start of the current inspiratory phase.

4. The apparatus according to any one or more of claims 1 to 3, wherein adjusting the rate of the cardiac pacing pulse comprises: The delivery of the cardiac pacing pulse more closely mimics respiratory sinus arrhythmia (RSA).

5. The apparatus according to any one or more of claims 2 to 4, wherein the processing circuitry is further configured to: Determine the patient's heart rate; It is determined that the patient has not reached RSA based on the patient's heart rate and one or more of the previous inspiratory or expiratory phase; and Based on determining that the patient has not reached RSA, the treatment delivery circuit controls the rate of the cardiac pacing pulse to be adjusted during one or more of the current inspiratory or expiratory phases.

6. The apparatus according to any one or more of claims 1 to 5, wherein the processing circuitry is further configured to: During the initialization phase, the sensed bioimpedance signal is received; and At least one signal characteristic is determined based on the sensed bioimpedance signal.

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 heart rate to the 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 processing circuitry is configured to select one or more stimulation parameters for sensing the bioimpedance signal.

9. The apparatus of claim 8, wherein selecting one or more stimulation parameters includes selecting stimulation amplitude, and wherein, in order to select the stimulation amplitude, the processing circuitry is configured to: Control one or more of the plurality of electrodes to stimulate with multiple stimulation amplitudes; For each of the plurality of stimulus amplitudes, determine whether the corresponding bioimpedance signal satisfies one or more quality thresholds; and In response to the corresponding bioimpedance signal satisfying one or more quality thresholds, the stimulation amplitude among the plurality of stimulation amplitudes is selected.

10. The apparatus of claim 9, wherein the processing circuit is further configured to: Determine the minimum stimulation amplitude required for the corresponding bioimpedance signal to satisfy one or more quality thresholds; and Select the lowest stimulation amplitude when the corresponding bioimpedance signal satisfies one or more quality thresholds.

11. The apparatus according to any one of claims 1 to 10, wherein the processing circuit 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.

12. The device of claim 11, wherein the patient state includes one or more of the following: Patient's disease state; or Patient activity level.

13. The apparatus according to any one or more of claims 2 to 12, wherein the processing circuitry is further configured to: Predicting subsequent inhalation phases based on previous inhalation phases; Predicting subsequent expiratory phases based on previous expiratory phases; and The treatment delivery circuit is controlled to deliver the cardiac pacing pulses during the subsequent inspiratory and expiratory phases to simulate respiratory sinus arrhythmia (RSA) based on the previous inspiratory and expiratory phases.

14. The device according to any one or more of claims 1 to 13, wherein the device includes a pacemaker.

15. A non-transitory computer-readable medium storing instructions that, when executed by processing circuitry, cause the processing circuitry to: Using bioimpedance signals to identify the start of the patient's current inspiratory phase; and The treatment delivery circuitry adjusts the rate of cardiac pacing pulses during the current inspiratory phase based on the identifier of the start of the current inspiratory phase.

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