Detection of HFPEF using exertional heart sounds

Abstract

This document discusses, among other things, systems and methods for determining an indication of heart failure with preserved ejection fraction (HFpEF) in a subject using a determined change in cardiac acceleration information of the subject during exertion relative to cardiac acceleration information of the subject at rest. The system may include: a signal receiver circuit configured to receive cardiac acceleration information of the subject and exertion information of the subject; and an evaluation circuit configured to determine a change in cardiac acceleration information of the subject during exertion relative to cardiac acceleration information of the subject at rest, and to determine an indication of HFpEF in the subject using the determined change in cardiac acceleration information.

Description

[0001] Priority claim

[0002] This application claims priority under 35 U.S.C. §119(e) to U.S. Provisional Patent Application Serial No. 62 / 777,977, filed on December 11, 2018, which is incorporated herein by reference in its entirety. Technical Field

[0003] This document relates generally to medical devices and, more particularly, but not by way of limitation, to systems, devices, and methods for monitoring or detecting heart failure with preserved ejection fraction (HFpEF) using exertional heart sounds. Background Art

[0004] Heart failure (HF) is the reduced ability of the heart to deliver enough blood to meet the body's needs, affecting more than 5 million patients in the United States alone. HF patients often have an enlarged heart with weakened myocardium, resulting in reduced contractility and poor cardiac output. Typical signs of HF include: pulmonary congestion, edema, dyspnea, etc.

[0005] Ejection fraction (EF) is a measure of the heart's pumping efficiency, or the heart's ability to pump blood out of the left ventricle and into the body's circulatory system. EF is typically measured as a percentage of the blood ejected from the left ventricle during the systolic phase of the heartbeat to the total capacity of the left ventricle. The EF of a normally functioning heart can be between 50% and 70%. A preserved EF typically refers to a measure of 50% or higher. A reduced EF typically refers to a measure of 40% or lower. An EF between 40% and 50% can be considered critical. In other examples, a reduced EF can refer to a measure below 50%, while a preserved EF can refer to a measure above 50%.

[0006] A reduced EF (e.g., an EF below 40%) may indicate certain types of heart failure (HF) or cardiomyopathy. In contrast, an EF above 75% may indicate certain heart conditions, such as hypertrophic cardiomyopathy or a reduced volume of the left ventricle. Although a reduced EF may indicate a type of HF (called heart failure with reduced ejection fraction (HF with reduced EF, HFrEF) or systolic HF), nearly half of HF patients exhibit a normal or preserved EF (called heart failure with preserved ejection fraction (HFpEF) or diastolic HF).

[0007] In developed countries, the prevalence of HFpEF continues to rise with increasing common risk factors including age, sex (higher prevalence in female patients), hypertension, metabolic syndrome, renal dysfunction, and obesity. Furthermore, HFpEF patients do not respond to all HFrEF medications and treatments. Therefore, there is a need to enhance existing HF detection and treatment to distinguish HFpEF from HFrEF, thereby increasing the sensitivity and specificity of existing medical devices and systems and improving the performance and functionality of specific modern medical technologies. Summary of the invention

[0008] This document discusses, among other things, systems and methods for determining an indication of heart failure with preserved ejection fraction (HFpEF) in a subject using a determined change in cardiac acceleration information (e.g., cardiac vibration, acceleration, pressure wave, or heart sound information) of the subject during exertion relative to the subject's cardiac acceleration information at rest. The system may include: a signal receiver circuit configured to receive the subject's cardiac acceleration information and the subject's exertion information; and an evaluation circuit configured to determine a change in the subject's cardiac acceleration information during exertion relative to the subject's cardiac acceleration information at rest, and use the determined change in cardiac acceleration information to determine an indication of HFpEF in the subject.

[0009] In Example 1, a subject (e.g., a medical device system) may include: a signal receiver circuit configured to receive exertion information of a subject and cardiac oscillation information of the subject; and an evaluation circuit configured to determine a change in cardiac acceleration information of the subject during exertion relative to the cardiac acceleration information of the subject at rest, and to use the determined change in cardiac acceleration information to determine an indication of heart failure with preserved ejection fraction (HFpEF) of the subject.

[0010] In Example 2, the subject matter of Example 1 may optionally be configured such that the signal receiver circuit is configured to receive cardiac acceleration information indicative of third heart sound (S3) or fourth heart sound (S4) information of the subject.

[0011] In Example 3, the subject matter of any one or more of Examples 1 to 2 may optionally be configured such that the evaluation circuit is configured to determine a rest period of the subject using the received effort information; determine an exertion period of the subject using the received effort information; determine a measure of the subject's cardiac acceleration information during the determined rest period, and determine a measure of the subject's cardiac acceleration information during the determined exertion period, and in order to determine a change in the subject's cardiac acceleration information, the evaluation circuit is configured to determine a change in the determined measure of the subject's cardiac acceleration information between the determined rest period and exertion period.

[0012] In Example 4, the subject matter of any one or more of Examples 1 to 3 may optionally be configured such that the evaluation circuit is configured to trend the determined measure of the subject's cardiac acceleration information for a determined rest period, trend the determined measure of the subject's cardiac acceleration information for a determined exertion period, and use the trend to determine changes in the determined measure of the subject's cardiac acceleration information.

[0013] In Example 5, the subject matter of any one or more of Examples 1 to 4 can optionally be configured such that the signal receiver circuit is configured to receive posture information of the subject, and the evaluation circuit is configured to determine a rest period of the subject using the received force information and the received posture information, and to determine a force period of the subject using the received force information and the received posture information.

[0014] In Example 6, the subject matter of any one or more of Examples 1 to 5 can optionally be configured such that the evaluation circuit is configured to trend the determined changes in the subject's cardiac acceleration information during exertion relative to the subject's cardiac acceleration information at rest, and use the trend to determine changes in the subject's cardiac acceleration information.

[0015] In Example 7, the subject matter of any one or more of Examples 1 to 6 can optionally be configured such that the signal receiver circuit is configured to receive cardiac acceleration information of the subject and exertion information of the subject using the same acceleration sensor at different times, and the evaluation circuit is configured to determine the exertion level using the acceleration information from the acceleration sensor, detect a transition from a first exertion level to a lower second transition level, determine a measure of the subject's cardiac acceleration information indicative of the subject's cardiac acceleration information at the first exertion level after the detected transition from the first exertion level to the second exertion level, and determine a measure of the subject's cardiac acceleration information indicative of the subject's cardiac acceleration information at the second exertion level after a recovery period after the detected transition from the first exertion level to the second exertion level.

[0016] In Example 8, the subject matter of any one or more of Examples 1 to 7 may optionally be configured to include a posture sensor configured to sense posture information of a subject, wherein the evaluation circuit is configured to detect a transition from a first force level to a lower second transition level using the subject's force information and the subject's posture information.

[0017] In Example 9, the subject matter of any one or more of Examples 1 to 8 may optionally be configured to include an acceleration sensor configured to sense cardiac acceleration information of the subject and effort information of the subject, wherein the signal receiver circuit is configured to receive the cardiac acceleration information of the subject and the effort information of the subject from the acceleration sensor, and the second effort level is resting.

[0018] In Example 10, the subject matter of any one or more of Examples 1 to 9 may optionally be configured to include a cardiac acceleration sensor configured to sense cardiac acceleration information of the subject and an activity sensor configured to sense effort information of the subject, wherein the signal receiver circuit is configured to receive the cardiac acceleration information of the subject from the cardiac acceleration sensor and to receive the effort information of the subject from the activity sensor.

[0019] In Example 11, the subject matter of any one or more of Examples 1 to 10 may optionally be configured such that the evaluation circuit is configured to determine an indication of HFpEF of the subject using a determined change in the cardiac acceleration information during exertion relative to the cardiac acceleration information of the subject at rest that is greater than a HFpEF threshold.

[0020] In Example 12, the subject matter of any one or more of Examples 1 to 11 can optionally be configured such that, to determine an indication of HFpEF of the subject, the evaluation circuit is configured to determine an indication of worsening of the subject's HFpEF using the determined changes in the cardiac acceleration information, the example also including a user interface configured to provide a human-perceptible alarm to the subject or a clinician using the determined indication of worsening of the subject's HFpEF.

[0021] In Example 13, the subject matter (e.g., a method of controlling a medical device system) may include: receiving, using a signal receiver circuit, exertion information of a subject and cardiac acceleration information of the subject; determining, using an evaluation circuit, a change in the cardiac acceleration information of the subject during exertion relative to the cardiac acceleration information of the subject at rest, and using the determined change in the cardiac acceleration information to determine an indication of heart failure with preserved ejection fraction (HFpEF) of the subject.

[0022] In Example 14, the subject matter of any one or more of Examples 1 to 13 may optionally be configured such that determining changes in the subject's cardiac acceleration information includes: using the received effort information to determine a rest period of the subject; using the received effort information to determine an exertion period of the subject; determining a measure of the subject's cardiac acceleration information during the determined rest period, and determining a measure of the subject's cardiac acceleration information during the determined exertion period, and determining changes in the subject's cardiac acceleration information includes determining changes in the determined measures of the subject's cardiac acceleration information during the determined rest period and exertion period.

[0023] In Example 15, the subject matter of any one or more of Examples 1 to 14 may optionally be configured to include trending the determined measure of the subject's cardiac acceleration information for the determined rest period and trending the determined measure of the subject's cardiac acceleration information for the determined exertion period, wherein determining a change in the determined measure of the subject's cardiac acceleration information includes using the trend, and determining an indication of the subject's HFpEF includes using the determined change in the determined measure of the subject's cardiac acceleration information to determine an indication of a worsening of the subject's HFpEF.

[0024] In Example 16, the subject matter of any one or more of Examples 1 to 15 can optionally be configured to include receiving posture information of the subject using a signal receiver circuit, wherein determining a rest period of the subject includes using the received force information and the received posture information, and determining a strain period of the subject includes using the received force information and the received posture information.

[0025] In Example 17, the subject matter of any one or more of Examples 1 to 16 can optionally be configured to include trending determined changes in the subject's cardiac acceleration information during exertion relative to the subject's cardiac acceleration information at rest, wherein determining changes in the subject's cardiac acceleration information includes using trends.

[0026] In Example 18, the subject matter of any one or more of Examples 1 to 17 can optionally be configured such that receiving cardiac acceleration information of the subject and exertion information of the subject includes using the same acceleration sensor at different times, the example also including: using the acceleration information from the acceleration sensor to determine exertion level; detecting a transition from a first exertion level to a lower second transition level; after the detected transition from the first exertion level to the second exertion level, determining a measure of the subject's cardiac acceleration information indicative of the subject's cardiac acceleration information at the first exertion level; and after a recovery period after the detected transition from the first exertion level to the second exertion level, determining a measure of the subject's cardiac acceleration information indicative of the subject's cardiac acceleration information at the second exertion level, wherein the second exertion level is resting.

[0027] In Example 19, the subject matter of any one or more of Examples 1 to 18 may optionally be configured to include sensing cardiac acceleration information of the subject using a cardiac acceleration sensor and sensing effort information of the subject using an activity sensor, wherein receiving the cardiac acceleration information of the subject includes receiving it from the cardiac acceleration sensor, and receiving the effort information of the subject includes receiving it from the activity sensor.

[0028] In Example 20, the subject matter of any one or more of Examples 1 to 19 may optionally be configured such that determining an indication of HFpEF for the subject comprises using a determined change in cardiac acceleration information during exertion relative to cardiac acceleration information for the subject at rest that is greater than a HFpEF threshold.

[0029] In Example 21, the subject matter (e.g., a system or apparatus) may optionally combine any portion or combination of any one or more of Examples 1 to 20 to include a "device for performing any portion of any one or more of the functions or methods of Examples 1 to 20" or a "non-transitory machine-readable medium" that includes instructions that, when executed by a machine, cause the machine to perform any portion of any one or more of the functions or methods of Examples 1 to 20.

[0030] This summary is intended to provide an overview of the subject matter of this patent application. It is not intended to provide an exclusive or exhaustive explanation of the present disclosure. A detailed description is included to provide further information about this patent application. Other aspects of the present disclosure will be apparent to those skilled in the art upon reading and understanding the following detailed description and viewing the accompanying drawings that form a part thereof (each of which is not to be viewed in a limiting sense). BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In the accompanying drawings, which are not necessarily drawn to scale, like numbers may describe similar components in different views. The same numbers with different letter suffixes may represent different instances of similar components. The accompanying drawings generally illustrate various embodiments discussed in this document by way of example and not limitation.

[0032] Figures 1 to 4 Example relationships between physiological information of a subject are shown.

[0033] Figure 5 An example medical device system including a signal receiver circuit and an evaluation circuit is shown.

[0034] Figure 6 An example medical device system including an ambulatory medical device (AMD) configured to sense or detect information from a subject and an external system is shown.

[0035] Figure 7 An example method is shown that includes using determined changes in cardiac acceleration information of a subject to determine an indication of heart failure with preserved ejection fraction (HFpEF) in the subject.

[0036] Figure 8 A block diagram is shown of an example machine upon which any one or more of the techniques discussed herein may be executed. DETAILED DESCRIPTION

[0037] Heart sounds are recurring mechanical signals associated with heart vibrations or accelerations caused by blood flow or other heart movements through the heart for each cardiac cycle, and can be distinguished and classified according to the activities associated with such vibrations, accelerations, movements, pressure waves or blood flow. Heart sounds include four main features: the first to fourth heart sounds. The first heart sound (S1) is the vibration sound emitted by the heart during the closure of the atrioventricular (AV) valve, mitral valve and tricuspid valve at the beginning of the systolic period. The second heart sound (S2) is the vibration sound emitted by the heart during the closure of the aortic valve and pulmonary valve at the beginning of the diastolic period. The third and fourth heart sounds (S3, S4) are related to the filling pressure of the left ventricle during the diastolic period. Valve closure and blood movement and pressure changes in the heart may cause acceleration, vibration or movement of the heart wall, which is detected using an accelerometer or microphone to provide an output referred to as heart acceleration information in this article. In other examples, valve motion may be detected directly by imaging techniques such as echocardiography and magnetic resonance imaging (MRI) or by intracardiac impedance plethysmography.

[0038] Heart sounds may be used to detect various physiological conditions, including, for example, acute physiological events such as one or more abnormal heart rhythms (e.g., atrial fibrillation, atrial flutter, mechanical cardiac dyssynchrony, etc.) or chronic physiological events (e.g., ischemia, etc.). For example, heart sounds may be used to detect heart failure (HF). In particular, HF may be monitored using the third heart sound (S3), such as disclosed in commonly assigned U.S. Patent No. 7,115,096 to Siejke et al., entitled “Third Heart Sound Activity Index for Heart Failure Monitoring,” which is incorporated herein by reference in its entirety. A HF risk score may be determined, and the measured physiological parameters of the sensed S3 heart sound may be used to regulate heart failure worsening (worsening heart failure) risk factors. No. 9,968,266 to An et al., entitled “Risk-Stratified Heart Failure Detection Algorithm,” which is incorporated herein by reference in its entirety. Physiological indicators such as HF status indications can be determined using trends in heart sound characteristics determined after a transition from an elevated activity level to an elevated lower activity level, such as disclosed in U.S. Pat. No. 9,345,410 to Thakur et al., entitled “Diagnosis and Optimization Using Exercise Recovery Data,” which is incorporated herein by reference in its entirety.

[0039] The inventors have recognized that, in particular, certain existing mobile medical device systems may under-detect certain HF conditions, such as HF with preserved ejection fraction (HFpEF). In addition, the inventors have recognized that specific cardiac acceleration (e.g., cardiac oscillations, pressure waveforms, endocardial accelerations, heart sounds, etc.) information, such as exertional heart sounds, including specific heart sound information at a specific activity level (such as an elevated activity level) or heart sound information after a transition from an elevated activity level to an elevated lower activity level, may be used to detect HFpEF (or to differentiate between HF with reduced ejection fraction (HFrEF)). In an example, the heart sound information after the transition may include information immediately after the transition, such that the heart sound information indicates heart sound information during the elevated activity level (taking into account the time after the detected transition, such as taking into account any recovery or change in the detected heart sound information, in certain examples).

[0040] Heart sounds can be used to detect certain physiological information. For example, heart sound information can be used to detect atrial filling pressure, such as shown in commonly assigned U.S. Patent No. 7,972,275 to Siejko et al., entitled "Method and Apparatus for Monitoring Diastolic Hemodynamics," or commonly assigned U.S. Patent No. 8,048,001 to Patangay et al., entitled "Method and Apparatus for Detecting Atrial Filling Pressure," each of which is incorporated herein by reference in its entirety.

[0041] There are fundamental differences in heart sound information between HFpEF patients and HFrEF patients. For example, baseline S3 may be lower in HFpEF patients compared to HFrEF patients, but may increase abnormally with exertion (indicative of an amplified hemodynamic response). Activity or posture information may be used to detect exertion. Changes in S3 with exertion at elevated activity levels, or after elevated activity levels, or after a transition from a first activity level to a second, lower activity level, may increase the sensitivity or specificity of HFpEF detection, or enable HFpEF detection in existing systems that were previously unable to detect such conditions.

[0042] Increased sensitivity or specificity of detection can improve data collection and storage efficiency, thereby, in some examples, providing a more robust patient monitoring system that uses less storage or data processing than existing systems. Moreover, improved detection of conditions or detection of additional conditions in complex, regulated medical systems, components, or machinery can improve the efficiency of medical system resources, thereby improving the functionality of modern regulated technology systems and methods that cannot be performed or managed by general-purpose computers, components, or machinery.

[0043] Figure 1 An example relationship 100 is shown between physiological information including heart sounds 102 (first, second, third, and fourth heart sounds (S1, S2, S3, and S4)), left atrial pressure 104, left ventricular pressure 106, aortic pressure 108, ventricular volume 110, and an electrocardiogram 112 (such as detected from one or more sensors).

[0044] At a first time (T1), the mitral valve closes, which signals a rise in left ventricular pressure 106, as well as the first heart sound (S1) and the beginning of systole or ventricular contraction. At a second time (T2), the aortic valve opens, which signals a rise in aortic pressure 108, a fall in ventricular volume 110, and a continuation of S1. S1 is caused by the closure of the atrioventricular (AV) valves (including the mitral and tricuspid valves) and can be used to monitor cardiac contractility. As left ventricular pressure 106 falls, the plethysmogram 114 rises.

[0045] At a third time (T3), the aortic valve closes, resulting in aortic pressure 108 and a dicrotic notch in the second heart sound (S2), marking the end of systole, or ventricular contraction, and the beginning of diastole, or ventricular relaxation. S2 can be used to monitor blood pressure. At a fourth time (T4), the mitral valve opens, the left atrial pressure 104 decreases, and the ventricular volume 110 increases. A sudden cessation of early diastolic filling may cause the third heart sound (S3), which may indicate heart failure (HF) (or an early sign of heart failure). When the left ventricular pressure 106 relaxes and the ventricular volume 110 increases, the plethysmogram 114 decreases. Vibrations caused by atrial beating may cause a fourth heart sound (S4), which can be used to monitor ventricular compliance.

[0046] Systolic time intervals such as pre-ejection period (PEP) or left ventricular ejection time (LVET) can indicate clinically relevant information, including contractility, arrhythmias, QT prolongation (with electrocardiogram (EGM) information), etc. PEP can be measured from the Q wave of the EGM to the time of aortic valve opening ( Figure 1 LVET can include the time between the opening of the aortic valve (T2) and the closing of the aortic valve (T3). In other examples, one or more contraction time intervals can be detected and used to detect physiological information of the subject (e.g., PEP / LVET, one or more mechanical, electrical or electromechanical time intervals, etc.).

[0047] Figure 2 An example relationship 200 is shown between physiological information including ventricular volume 210 and ventricular filling velocity 214, such as those detected or obtained from one or more sensors (e.g., pressure sensor, Doppler echocardiogram, ultrasound imaging, etc.) during three periods of diastole: early filling (or rapid or passive filling) period 216, slow filling period 218, and late filling period 220. Ventricular filling velocity 214 has two peaks: an E wave in early filling period 216; and an A wave in late filling period 220. 70-85% of ventricular filling occurs in early filling period 216, and 15-20% in late filling period 220.

[0048] The E wave provides information about the left atrial (LA) pressure in early diastole and occurs immediately after the isovolumetric relaxation time (IVRT) and the opening of the mitral valve. Figure 2The slope or time of the second downward edge of the E wave in the middle (the slope or time of the second downward edge of the E wave in the middle) is affected by the rate of rise in LV diastolic pressure (LVDP) due to early filling. A rapid cessation of flow can indicate a rapidly rising pressure in the LV, or rapid emptying of the LA into a highly compliant LV. The A wave velocity is affected by the LA pressure and LV compliance at the end of diastole. The A wave amplitude and duration are affected by the stiffness of the ventricles. The ventricular filling velocity 214 can be characterized by the shape, timing or amplitude of the E wave or A wave, or the ratio, timing or other measure between the E wave and the A wave (such as the E / A ratio (the ratio of the amplitude of the E wave to the amplitude of the A wave) or EDT), and HF can be detected using one or more measures or characterizations of the ventricular filling velocity 214. Normal diagnostic function can be characterized by an E / A ratio between 0.8 and 2, which decreases with age.

[0049] The third heart sound (S3) is consistent with the deceleration phase of the E wave and suggests a restrictive filling pattern with steep E wave deceleration. Detection of S3 using phonocardiography can be associated with higher E wave amplitudes and shorter EDT, and can be correlated with EDT (correlation coefficient (r) = 0.43). Acceleration information (e.g., HS information) indicating S3 can be consistent with the deceleration phase of the E wave and can be inversely correlated with EDT. The detected S3 (in mG) can be correlated with EDT (r = 0.55). One or more characteristics or metrics of S3 (e.g., amplitude, energy, timing, etc.) can be used to determine an indication of EDT or detect EDT changes.

[0050] It is expected that the E wave will be abnormally long in HFpEF. A long EDT is one diagnostic criterion for HFpEF. For example, for patients under 50 years of age, an E / A ratio of less than 1.0 and an EDT greater than 220 ms indicate HFpEF. For patients over 50 years of age, an E / A ratio of less than 0.5 and an EDT greater than 280 ms indicate HFpEF. From first principles, it can be expected that a longer EDT and a lower E / A ratio will result in a lower (or no) S3 in HFpEF. However, the inventors have recognized that the EDT can be significantly shortened during exercise. Even if S3 is too low to be detected in HFpEF at rest, it may be evident during exertion. A large proportion of HFpEF patients may not show abnormalities in S3 or EDT at rest, but show significant exacerbations during exertion. An increase in the E wave metric or a combination of increases in the E wave and S3 metrics can be used to detect HFpEF during or immediately after exertion.

[0051] Figure 3 and Figure 4 Example physiological information at rest and during exercise is generally shown. Figure 3Pulmonary artery (PA) mean pressure information 300 at rest or during exercise (or exertion) is shown for a patient 302 with non-cardiac dyspnea (NCD) and for a patient 304 with HFpEF. For the patient 302 with NCD, the difference between rest and exercise is approximately 20%, while for the patient 304 with HFpEF, the difference between rest and exercise is greater, approximately 100%.

[0052] Figure 4 LV end-diastolic pressure (LVEDP) information 400 is shown at rest and during exercise for a patient with NCD 402 and for a patient with HFpEF 404. For the patient with NCD 402, the difference between rest and exercise is again approximately 20%, while for the patient with HFpEF 404, the difference between rest and exercise is greater, greater than 100%.

[0053] Indications or measures of certain physiological information can be determined using HS. For example, S3 information can be used to determine an indication of one or more of mean PA pressure, LVEDP, EDT, or one or more other E wave measures (e.g., amplitude, timing, etc.). In some examples, S4 information can be used to determine one or more E wave measures (e.g., amplitude, timing, etc.). For example, a comparison of S3 and S4 information can be used to determine a measure, indication, or change in the E / A ratio. Thus, HFpEF can be detected, or a measure or change in HS information (such as S3 or S4 information) at rest can be used to confirm, enhance, or improve existing HF detection or existing medical device systems or methods compared to during exercise or exertion or after (e.g., immediately thereafter).

[0054] Ambulatory medical devices (AMDs), including implantable or wearable medical devices, may be configured to monitor, detect, or treat various cardiac conditions associated with a reduced ability of the heart to adequately deliver blood to the body, such as HF, arrhythmias, hypertension, etc. An AMD may include a single device or multiple medical devices or monitors implanted in a subject or otherwise positioned on or about a subject to monitor subject physiological information of the subject (such as heart sounds, respiration (e.g., respiratory rate, tidal volume, etc.), impedance (e.g., thoracic impedance, cardiac impedance, etc.), pressure (e.g., blood pressure), cardiac activity (e.g., heart rate), physical activity, posture, plethysmography, or one or more other physiological parameters of the subject) or to provide electrical stimulation or one or more other therapies or treatments to optimize or control the contraction of the heart.

[0055] In an example, the AMD may include one or more of the following: a respiratory sensor configured to receive respiratory information (e.g., respiration rate (RR), respiratory volume (tidal volume), etc.); an acceleration sensor (e.g., accelerometer, microphone, etc.) configured to receive cardiac acceleration information (e.g., cardiac vibration information, pressure waveform information, heart sound information, endocardial acceleration information, acceleration information, activity information, posture information, etc.); an impedance sensor (e.g., intrathoracic impedance sensor, transthoracic impedance sensor, etc.) configured to receive impedance information; a cardiac sensor configured to receive cardiac electrical information; an activity sensor configured to receive information about body movement (e.g., activity, steps, etc.); a posture sensor configured to receive posture or position information; a pressure sensor configured to receive pressure information; a plethysmography sensor (e.g., photoplethysmography sensor, etc.); or one or more other sensors configured to receive physiological information of the subject.

[0056] Conventional cardiac rhythm management (CRM) devices (such as pacemakers, defibrillators, or cardiac resynchronizers) include a subcutaneous device configured to be implanted in the chest of a subject, having one or more leads to position one or more electrodes or other sensors at various locations within or near the heart, such as at various locations in one or more of the atria or ventricles. Separately from or in addition to the one or more electrodes or other sensors of the leads, the CRM device may include one or more electrodes or other sensors (e.g., pressure sensors, accelerometers, gyroscopes, microphones, etc.) powered by a power source in the CRM device. The one or more electrodes or other sensors of the leads, the CRM device, or a combination thereof may be configured to detect physiological information from the subject, or to provide one or more therapies or stimulations to the subject.

[0057] Implantable devices may additionally include leadless cardiac pacemakers (LCPs), small (e.g., smaller than conventional implantable CRM devices, having a volume of about 1 cc in some examples, etc.) self-contained devices that include one or more sensors, circuits, or electrodes configured to monitor physiological information from the heart (e.g., heart rate, etc.), detect physiological conditions associated with the heart (e.g., tachycardia), or provide one or more therapies or stimulations to the heart without the complications of conventional leads or implantable CRM devices (e.g., required incisions and pockets, complications associated with lead placement, breakage, or migration, etc.). In some examples, LCPs may have more limited power and processing capabilities than conventional CRM devices; however, multiple LCP devices may be implanted in or around the heart to detect physiological information from one or more chambers of the heart, or provide one or more therapies or stimulations to one or more chambers of the heart. Multiple LCP devices may communicate among themselves, or with one or more other implanted or external devices.

[0058] Wearable or external medical sensors or devices can be configured to detect or monitor physiological information of a subject without requiring implantation or hospitalization procedures for placement, battery replacement, or repair. However, such sensors and devices may have reduced patient compliance, increased detection noise, or reduced detection sensitivity compared to implantable medical devices.

[0059] For each of the above-mentioned mobile medical devices (AMDs) (e.g., implantable medical devices (IMDs) or wearable medical devices (WMDs)), each additional sensor may increase system cost and complexity, reduce system reliability, or increase power consumption and reduce the service life of the mobile device. Therefore, it is beneficial to use a single sensor to determine multiple types of physiological information, or to use a smaller number of sensors to measure a large number of different types of physiological information.

[0060] In an example, an accelerometer, microphone, or acoustic sensor may sense or detect acceleration information of a subject, which acceleration information includes or indicates cardiac acceleration information of the subject (e.g., cardiac sound information, such as cardiac sound information from a pressure waveform caused by cardiac vibrations; endocardial acceleration information, such as acceleration information detected on or within the ventricles; cardiac vibration information, etc.). In some examples, the same or different accelerometer, microphone, acoustic sensor, or one or more other activity, posture, or force sensors may receive force information of the subject (e.g., activity information, posture information, etc.). The force information may include physical activity information of the subject that occurs at a frequency different from the cardiac acceleration information. Therefore, the sampling rate for detecting the physical activity information of the subject is typically much lower than the sampling rate required to detect cardiac acceleration information (e.g., force is typically detected at a sampling rate of 50 Hz or less, while cardiac acceleration information is typically detected at a sampling rate of 1 kHz or more).

[0061] In an example, a single sensor may detect acceleration information at a detection period and sampling rate such that both cardiac acceleration information and effort information may be determined based on the acceleration information detected during the same or overlapping time period. However, determining separate cardiac acceleration information and effort information based on the same acceleration information may require a large amount of processing time and resources. Therefore, when a single sensor is used to detect cardiac acceleration information and effort information, cardiac acceleration information and effort information are more often detected at different sampling rates and using different preprocessing (e.g., filtering, signal conditioning, etc.) during non-overlapping time periods (e.g., a single sensor detects one of the cardiac acceleration information or effort information at a time), thereby reducing the processing resources required to sense and process separate information in an AMD or medical device system with limited or different storage, processing, power, and performance capabilities.

[0062] In other examples, different sensors (or a single sensor with different physical sensing portions or components) can be used to detect cardiac acceleration information and effort information. For example, it may be advantageous to use a more rigid sensor to detect physical activity or effort information that is tuned to sense activities with higher amplitude and lower frequency response than cardiac acceleration information; while it may be advantageous to use a sensor with higher sensitivity and sampling frequency (e.g., a microphone instead of an accelerometer, etc.) to detect cardiac acceleration information. In some examples, separate axes of a multi-axis sensor can be used to detect different information at different sampling rates.

[0063] In some examples, the evaluation circuit can be configured to determine a change in cardiac acceleration information of the subject during exertion relative to cardiac acceleration information of the subject at rest. The evaluation circuit can use the determined change in cardiac acceleration information to determine an indication, risk, or stratification of the subject state or a worsening subject condition (e.g., HFpEF). The evaluation circuit can provide acute or chronic monitoring of the subject's condition, and can provide an alert or indication to the subject or clinician in response to the determined change that the subject seek medical care or hospitalization, or otherwise determine one or more treatment parameters, such as to be provided to a clinician for consideration, or to recommend, control, or otherwise manage one or more functions, modes, or operations of one or more treatments for the subject or one or more components of a medical device system.

[0064] Figure 5 An example system (e.g., a medical device, etc.) 500 is shown that includes a signal receiver circuit 502 and an evaluation circuit 504. The signal receiver circuit 502 can be configured to receive subject information, such as physiological information of a subject, a patient (or a group of subjects or patients), from one or more sensors. The evaluation circuit 504 can be configured to receive information from the signal receiver circuit 502 and determine one or more parameters (e.g., a composite physiological parameter, a stratifier, one or more pacing parameters, etc.), such as the parameters described herein.

[0065] The evaluation circuit 504 can be configured to provide an output to a user, such as to a display or one or more other user interfaces, including a score, trend, alarm, or other indication. In other examples, the evaluation circuit 504 can be configured to provide an output to another circuit, machine, or process, such as to control, adjust, or stop a treatment of a medical device, a drug delivery system, or the like, or otherwise change one or more processes or functions of a medical device system.

[0066] Figure 6 An exemplary patient management system 600 and a portion of an environment in which the system 600 may operate are shown. The patient management system 600 may perform a range of activities including remote patient monitoring and diagnosis of disease conditions. Such activities may be performed close to the patient 601 (such as in the patient's home or office), through a centralized server (such as in a hospital, clinic, or doctor's office), or through a remote workstation (such as a secure wireless mobile computing device).

[0067] The patient management system 600 may include one or more mobile devices, an external system 605, and a communication link 611 that provides communication between the one or more mobile devices and the external system 605. The one or more mobile devices may include an implantable medical device (IMD) 602, a wearable medical device 603, or one or more other implantable, leadless, subcutaneous, external, wearable, or mobile medical devices configured to monitor, sense, or detect information from the patient 601, determine information about the patient, or provide one or more therapies to treat various cardiac conditions of the patient, such as high blood pressure, the ability of the heart to adequately deliver blood to the body, including atrial fibrillation (AF), congestive heart failure (CHF), essential hypertension, or one or more other cardiac or non-cardiac diseases (e.g., dehydration, bleeding, renal dysfunction, etc.).

[0068] In an example, IMD 602 ​​may include one or more conventional cardiac rhythm management (CRM) devices (such as a pacemaker or defibrillator) implanted in the chest of a subject with a lead system including one or more transvenous, subcutaneous, or non-invasive leads or catheters to position one or more electrodes or other sensors (e.g., heart sound sensors) in, on, or around the heart or one or more other locations on the chest, abdomen, or neck of subject 601. In another example, IMD 602 ​​may include a monitor implanted, for example, subcutaneously in the chest of subject 601.

[0069] IMD 602 ​​may include an evaluation circuit configured to detect or determine specific physiological information of subject 601, or to determine one or more conditions, or to provide information or an alarm to a user, such as subject 601 (e.g., a patient), a clinician, or one or more other caregivers. IMD 602 ​​is alternatively or additionally configured as a therapeutic device configured to treat one or more medical conditions of subject 601. Therapy may be delivered to subject 601 via a lead system and associated electrodes or using one or more other delivery mechanisms. Therapy may include antiarrhythmic therapy to treat arrhythmias or to treat or control one or more complications caused by arrhythmias, such as syncope, congestive heart failure (CHF), or stroke, etc. In other examples, therapy may include delivering one or more drugs to subject 601 using one or more of IMD 602 ​​or other mobile devices. Examples of antiarrhythmic therapies include pacing, cardioversion, defibrillation, neuromodulation, medication or biological therapy, and other types of therapy. In other examples, treatment may include cardiac resynchronization therapy (CRT) for correcting desynchronization and improving cardiac function in CHF patients. In some examples, IMD 602 ​​may include a drug delivery system, such as a drug infusion pump for delivering drugs to a patient to manage arrhythmias or complications caused by arrhythmias, hypertension, or one or more other physiological conditions. In other examples, IMD 602 ​​may include a therapy circuit or module configured to treat hypertension (e.g., a neural stimulation therapy circuit, a drug delivery therapy circuit, a stimulation therapy circuit, etc.).

[0070] The wearable medical device 603 may include one or more wearable or external medical sensors or devices (e.g., an automatic external defibrillator (AED), a Holter monitor, a patch-based device, a smart watch, a smart accessory, a wrist-worn or finger-worn medical device (such as a finger-based photoplethysmographic sensor), etc.). The wearable medical device 603 may include an optical sensor configured to detect a photoplethysmographic (PPG) signal on the wrist, finger, or other location of the subject 601. In other examples, the wearable medical device 603 may include an acoustic sensor or accelerometer for detecting acoustic information (e.g., heart sounds) or sounds or vibrations of blood flow, an impedance sensor for detecting impedance changes associated with changes in blood flow or volume, a temperature sensor for detecting temperature changes associated with blood flow, a laser Doppler vibrometer or other pressure sensor, strain sensor, or physical sensor for detecting physical changes associated with blood flow, etc.

[0071] The patient management system 600 may include, in particular, a respiratory sensor configured to receive respiratory information (e.g., respiratory rate (RR), respiratory volume (tidal volume), etc.), a cardiac sound sensor configured to receive cardiac sound information, a chest impedance sensor configured to receive impedance information, a cardiac sensor configured to receive cardiac electrical information, an activity sensor configured to receive information about body movement (e.g., activity, posture, etc.), a plethysmography sensor, or one or more other sensors configured to receive physiological information of the subject 601.

[0072] The external system 605 may include a dedicated hardware / software system (such as a programmer), a patient management system based on a remote server, or alternatively a system defined primarily by software running on a standard personal computer. The external system 605 may manage the subject 601 through the IMD 602 ​​or one or more other mobile devices connected to the external system 605 via the communication link 611. In other examples, the IMD 602 ​​may be connected to the wearable device 603 via the communication link 611, or the wearable device 603 may be connected to the external system 605 via the communication link 611. This may include, for example, programming the IMD 602 ​​to perform one or more of acquiring physiological data, performing at least one self-diagnostic test (such as for device operating status), analyzing physiological data to detect arrhythmias, or optionally delivering or adjusting treatment to the subject 601. Additionally, the external system 605 may send information to or receive information from the IMD 602 ​​or the wearable device 603 via the communication link 611. Examples of information may include real-time or stored physiological data from subject 601, diagnostic data such as detection of arrhythmia or heart failure exacerbation events, response to therapy delivered to subject 601, or device operating status (e.g., battery status, lead impedance, etc.) of IMD 602 ​​or wearable device 603. Communication link 611 may be an inductive telemetry link, a capacitive telemetry link, or a radio-frequency (RF) telemetry link, or wireless telemetry based on, for example, "strong" Bluetooth or IEEE 802.11 Wireless Fidelity "WiFi" interface standards. Other configurations and combinations of patient data source interfaces are also possible.

[0073] By way of example and not limitation, external system 605 may include external device 606 proximate one or more mobile devices, and remote device 608 at a location relatively remote from one or more mobile devices that communicates with external device 606 via communication network 607. Examples of external device 606 may include a medical device programmer.

[0074] In addition to other possible functions, the remote device 608 can be configured to evaluate the collected subject or patient information and provide an alarm notification. In an example, the remote device 608 may include a centralized server that acts as a central hub for the collected data storage and analysis. The server may be configured as a single computing processing system, a multi-computing processing system, or a distributed computing processing system. The remote device 608 can receive data from multiple subjects or patients. In addition to other data acquisition sensors or devices associated with the subject 601, the data can be collected by one or more mobile devices. The server may include a memory device to store the data in a patient database. The server may include an alarm analyzer circuit to evaluate the collected data to determine whether a specific alarm condition is met. The satisfaction of the alarm condition can trigger the generation of an alarm notification, such as provided by one or more human-perceivable user interfaces. In some examples, the alarm condition can be evaluated alternatively or additionally by one or more mobile devices (such as IMDs). As an example, the alarm notification may include a web page update, a phone or pager call, an email, SMS, a text or "instant" message, and a message to the subject or patient and a direct notification to the emergency service and to the clinician at the same time. Other alarm notifications are also possible. The server may include an alarm prioritizer circuit configured to prioritize alarm notifications.For example, alarms for detected medical events may be prioritized using a similarity metric between physiological data associated with the detected medical event and physiological data associated with historical alarms.

[0075] The remote device 608 may additionally include one or more locally configured clients or remote clients securely connected to the server via the communication network 607. Examples of clients may include personal desktops, laptops, mobile devices, or other computing devices. System users (such as clinicians or other qualified medical experts) may use clients to securely access stored patient data collected in a database in the server, and select and prioritize patients and alarms for health care provision. In addition to generating alarm notifications, the remote device 608 including the server and interconnected clients may also execute a follow-up plan by sending a follow-up request to one or more mobile devices, or by sending a message or other communication as a compliance notification to a subject 601 (e.g., a patient), a clinician, or an authorized third party.

[0076] The communication network 607 can provide wired or wireless interconnectivity. In an example, the communication network 607 can be based on the Transmission Control Protocol / Internet Protocol (TCP / IP) network communication specification, but other types or combinations of networking implementations are also possible. Similarly, other network topologies and arrangements are also possible.

[0077] One or more of the external device 606 or remote device 608 may output the detected medical event to a system user (such as a patient or clinician), or to a process including an instance of a computer program that can be executed, for example, in a microprocessor. In an example, the process may include automatically generating a recommendation for antiarrhythmic therapy, or a recommendation for further diagnostic testing or treatment. In an example, the external device 606 or remote device 608 may include a corresponding display unit for displaying physiological or functional signals, or an alarm, an alarm, an emergency call, or other form of warning to signal the detection of an arrhythmia. In some examples, the external system 605 may include an external data processor configured to analyze physiological or functional signals received by one or more mobile devices and confirm or reject the detection of an arrhythmia. Computationally intensive algorithms (such as machine learning algorithms) may be implemented in the external data processor to retrospectively process data to detect arrhythmias.

[0078] Parts of one or more mobile devices or external systems 605 can be implemented using hardware, software, firmware or a combination thereof. Parts of one or more mobile devices or external systems 605 can be implemented using a dedicated circuit that can be constructed or configured to perform one or more functions, or can be implemented using a general-purpose circuit that can be programmed or otherwise configured to perform one or more specific functions. Such a general-purpose circuit can include a microprocessor or a portion thereof, a microcontroller or a portion thereof, or a programmable logic circuit, a memory circuit, a network interface, and various components for interconnecting these components. For example, a "comparator" can specifically include an electronic circuit comparator that can be constructed to perform a specific function of comparing two signals, or the comparator can be implemented as a part of a general-purpose circuit that can be driven by a code that indicates that a part of a general-purpose circuit performs a comparison between two signals. A "sensor" can include an electronic circuit that is configured to receive information and provide an electronic output representing such received information.

[0079] Patient management system 600 may include a therapeutic device, such as a drug delivery device, configured to provide therapy or therapeutic information (e.g., dosage information, etc.) to subject 601, such as using information from one or more of the mobile devices. In other examples, one or more of the mobile devices may be configured to provide therapy or therapeutic information to subject 601. The therapeutic device may be configured to send information to or receive information from one or more of the mobile devices or external systems 605 using communication link 611. In an example, one or more of the mobile devices, external devices 606, or remote devices 608 may be configured to control one or more parameters of therapeutic device 610.

[0080] The patient management system 600 may include a HF assessment circuit based on a patient chronic condition, such as that shown in the commonly assigned U.S. application Ser. No. 14 / 510,392 to Qi An et al., the entire contents of which are incorporated herein by reference. The HF assessment circuit based on a patient chronic condition may include a signal analyzer circuit and a risk stratification circuit. The signal analyzer circuit may receive a patient chronic condition indicator and one or more physiological signals from the patient, and select one or more patient-specific sensor signals or signal metrics from the physiological signals. The signal analyzer circuit may receive physiological signals from the patient using electrodes on one or more of the leads or physiological sensors deployed on or in the patient and communicating with one or more other components of the patient management system 600. The risk stratification circuit may generate a composite risk index, such as using the selected patient-specific sensor signals or signal metrics, that indicates the probability of the patient subsequently developing a HF exacerbation event (e.g., a HF decompensation event). The HF decompensation event may include one or more early precursors to the onset of HF compensation, or an event indicating HF progression (such as recovery or worsening of the HF state).

[0081] External system 605 may allow programming of one or more mobile devices and may receive information about one or more signals acquired by one or more mobile devices, such as information that may be received via communication link 611. External system 605 may include a local external IMD programmer. External system 605 may include a remote patient management system that may monitor patient status or adjust one or more therapies, such as from a remote location.

[0082] The HF assessment circuit based on the patient's chronic condition or other assessment circuit may be implemented at the external system 605, which may be configured to perform HF risk stratification, such as using data extracted from one or more mobile devices or data stored in a memory within the external system 605. Portions of the HF assessment circuit based on the patient's chronic condition or other assessment circuit may be distributed between the one or more mobile devices and the external system 605.

[0083] Figure 7 An example method 700 for controlling or otherwise changing the functionality of a medical device system is shown. At 702, force information is received from a force sensor, such as by a signal receiver circuit. The force information may include acceleration information indicating the activity of a subject. An evaluation circuit may be configured to use the received force information to determine a rest period of the subject or an exertion period of the subject. The exertion period of the subject may include activity information of the subject at or above a threshold, or an aggregate amount of activity of the subject over a given time period. The rest period of the subject may include activity information of the subject below a threshold.

[0084] In an example, the force sensor may include a posture sensor, or the signal receiver may be configured to receive information from a posture sensor. In some examples, the detected change in posture may be combined with the force or activity information to determine a rest period or an exertion period. For example, if the posture or activity information indicates that the subject is sitting or lying down, or is inactive, then the detected activity period is not possible without the change in posture. Therefore, the change in posture can be used in part to define transitions between activity levels, such as a transition from an exertion period or activity above a threshold to a rest period.

[0085] At 704, cardiac acceleration information (e.g., heart sound information) is received from an acceleration sensor (e.g., an accelerometer, a microphone, etc.), such as through a signal receiver circuit, such as during a determined rest period or exertion period. The cardiac acceleration information may include one or more heart sounds of the subject, such as one or more of the first, second, third, or fourth heart sounds (S1 to S4), and the acceleration sensor may include a heart sound sensor, such as a microphone or an accelerometer. In an example, cardiac acceleration information may be received periodically and stored based on exertion information (such as an activity level or a determined exertion period or rest period). In other examples, exertion information may be determined, and cardiac acceleration information may be received for a specific desired exertion period or rest period or activity level. For a determined rest period, cardiac acceleration information may be received, stored, or measured after transitioning from exertion to rest and waiting long enough for the patient's physiological information to reach a resting baseline (e.g., a few minutes or more after the transition). However, for the determined activity period, cardiac acceleration information may be received, stored, or measured immediately after the detected transition from exertion to rest, for example to detect physiological information indicative of peak exertion, or to detect cardiac acceleration information as close to peak exertion as possible when a single sensor is used to determine exertion and cardiac acceleration information. In some examples, during the sustained exertion period, the acceleration sensor may switch from detecting exertion information to detecting cardiac acceleration information and then switch back to detecting exertion information.

[0086] At 706, a change in cardiac acceleration information during exertion relative to rest is determined, such as by an evaluation circuit. The evaluation circuit may be configured to determine a measure of the cardiac acceleration information of the subject during the determined rest period, and to determine a measure of the cardiac acceleration information of the subject during the determined exertion period. In order to determine changes in the cardiac acceleration information of the subject, the evaluation circuit may be configured to determine changes in the determined measure of cardiac acceleration information of the subject during the determined rest period and exertion period. In some examples, the evaluation circuit may determine short-term, long-term, or daily values ​​(e.g., averages, maximums, minimums, counts in the form of specific percentages, etc.) of cardiac acceleration information at rest and during exertion. In other examples, the evaluation circuit may trend the measure of cardiac acceleration information at rest and during exertion, or trend the difference between the measure of cardiac acceleration information at rest and during exertion.

[0087] In an example, a measure of cardiac acceleration information (e.g., S3 amplitude or energy in an S3 window, etc.) can be trended at one or more exertion levels, such as at or above one or more activity levels. The measure of cardiac acceleration during exertion can be compared to the measure of cardiac acceleration information at rest or at or below one or more activity levels.

[0088] In some examples, transitions between activity levels can be detected, such as from exertion to rest, or vice versa. After (e.g., immediately after) the transition from exertion to rest, a measure of cardiac acceleration information can be determined and stored to the activity level before the transition. Measures of cardiac acceleration information at various activity levels throughout the day can be stored or recorded to create a daily trend of measures of cardiac acceleration information at a specific activity level. In an example, the measure of cardiac acceleration information can be adjusted by a coefficient, such as activity level (e.g., peak exercise intensity (E), etc.), time (T) between activity level and received cardiac acceleration information (e.g., 1 minute, 2 minutes, 5 minutes, etc.), or a ratio of time to activity level (e.g., T / E, etc.). The measure of cardiac acceleration information can include one or more of the amplitude, timing, or energy of S1 to S4, or such a ratio (e.g., S1 / S3, S3 / S4).

[0089] At 708, an indication of HFpEF is determined, such as by the evaluation circuit using the determined change in the cardiac acceleration information during exertion relative to rest, such as by comparing the determined change or the determined trend of the change to a threshold value (e.g., a HFpEF threshold value). In some examples, the indication of HFpEF can be used to provide a human-perceivable alarm, or to control or adjust the function of one or more components of the medical device system.

[0090] Figure 8 A block diagram of an example machine 800 is shown on which any one or more of the techniques (e.g., methods) discussed herein may be executed. Portions of this specification may be applied to a computing framework for one or more of the medical devices described herein, such as an IMD, an external programmer, etc. Further, as described herein with respect to a medical device component, system, or machine, this may require regulatory compliance that is not available to general-purpose computers, components, or machines.

[0091] Examples as described herein may include logic or multiple components or mechanisms in the machine 800, or may be operated by logic or multiple components or mechanisms. A circuit system (e.g., a processing circuit system) is a collection of circuits implemented in a tangible entity of the machine 800 including hardware (e.g., simple circuits, gates, logic, etc.). Over time, members of the circuit system may be flexible and changeable. The circuit system includes components that perform specific operations individually or in combination when operating. In an example, the hardware of the circuit system may be designed to perform specific operations (e.g., hard-wired) in an unchangeable manner. In an example, the hardware of the circuit system may include variably connected physical components (e.g., execution units, transistors, simple circuits, etc.), which include machine-readable media that are physically modified (e.g., magnetically, electrically, with movable placement of unchanged aggregated particles, etc.) to encode instructions for specific operations. When connecting physical components, the basic electrical properties of the hardware components are changed, such as from an insulator to a conductor, and vice versa. Instructions enable embedded hardware (e.g., execution units or loading mechanisms) to create members of the circuit system in hardware through variable connections to perform parts of specific operations when operating. Thus, in an example, when the device is operating, the machine-readable medium element is part of a circuit system or is communicatively coupled to other components of the circuit system. In an example, any of the physical components can be used in more than one member of more than one circuit system. For example, in operation, an execution unit can be used in a first circuit of a first circuit system at one point in time and reused by a second circuit in the first circuit system, or reused by a third circuit in the second circuit system at a different time. Additional examples of these components of the machine 800 are as follows.

[0092] In alternative embodiments, the machine 800 can operate as a standalone device, or can be connected (e.g., networked) to other machines. In a networked deployment, the machine 800 can operate as a server machine, a client machine, or both in a server-client network environment. In an example, the machine 800 can act as a peer machine in a peer-to-peer (P2P) (or other distributed) network environment. The machine 800 can be a personal computer (personal computer, PC), a tablet computer, a set-top box (set-top box, STB), a personal digital assistant (personal digital assistant, PDA), a mobile phone, a network device, a network router, a switch or a bridge, or any machine capable of executing instructions (sequential or other) specifying the actions to be taken by the machine. Further, although only a single machine is shown, the term "machine" should also be understood to include any machine collection that executes a set (or multiple sets) of instructions individually or collectively to perform any one or more of the methods discussed herein, such as cloud computing, software as a service (software as a service, SaaS), and other computer cluster configurations.

[0093] The machine (e.g., computer system) 800 may include a hardware processor 802 (e.g., a central processing unit (CPU), a graphics processing unit (GPU), a hardware processor core, or any combination thereof), a main memory 804, a static memory (e.g., memory or storage for firmware, microcode, basic-input-output (BIOS), unified extensible firmware interface (UEFI), etc.) 806, and a mass storage device 808 (e.g., a hard drive, a tape drive, a flash memory, or other block device), some or all of which may communicate with each other via an interconnection link (e.g., a bus 830). The machine 800 may also include a display unit 810, an alphanumeric input device 812 (e.g., a keyboard), and a user interface (UI) navigation device 814 (e.g., a mouse). In an example, the display unit 810, the input device 812, and the UI navigation device 814 may be a touch screen display. The machine 800 may additionally include a signal generating device 818 (e.g., a speaker), a network interface device 820, and one or more sensors 816, such as a global positioning system (GPS) sensor, a compass, an accelerometer, or other sensors. The machine 800 may include an output controller 828, such as a serial (e.g., universal serial bus (USB)), parallel or other wired or wireless (e.g., infrared (IR), near field communication (NFC), etc.) connection to communicate with or control one or more peripheral devices (e.g., printers, card readers, etc.).

[0094] The registers of the processor 802, main memory 804, static memory 806, or mass storage 808 may be or include a machine-readable medium 822 on which one or more sets of data structures or instructions 824 (e.g., software) are stored, which implement or are utilized by any one or more of the techniques or functions described herein. The instructions 824 may also reside, completely or at least partially, in any of the registers of the processor 802, main memory 804, static memory 806, or mass storage 808 during execution thereof by the machine 800. In an example, one or any combination of the hardware processor 802, main memory 804, static memory 806, or mass storage 808 may constitute the machine-readable medium 822. Although the machine-readable medium 822 is illustrated as a single medium, the term "machine-readable medium" may include a single medium or multiple media (e.g., a centralized or distributed database, and / or associated caches and servers) configured to store one or more instructions 824.

[0095] The term "machine-readable medium" may include any medium capable of storing, encoding or carrying instructions for execution by the machine 800 and causing the machine 800 to perform any one or more of the techniques of the present disclosure, or any medium capable of storing, encoding or carrying data structures used by or associated with these instructions. Non-limiting machine-readable medium examples may include solid-state memory, optical media, magnetic media, and signals (e.g., radio frequency signals, other photon-based signals, sound signals, etc.). In an example, a non-transitory machine-readable medium includes a machine-readable medium with multiple particles having a constant (e.g., static) mass, and is therefore a material component. Therefore, a non-transitory machine-readable medium is a machine-readable medium that does not include a temporary propagation signal. Specific examples of non-transitory machine-readable media may include: non-volatile memory, such as semiconductor memory devices (e.g., electrically programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM)) and flash memory devices, disks (such as internal hard disks and removable disks), CD-ROM disks, and DVD-ROM disks.

[0096] The instructions 824 may also be transmitted or received over a communication network 826 using a transmission medium via a network interface device 820 using any of a variety of transmission protocols (e.g., frame relay, internet protocol (IP), transmission control protocol (TCP), user datagram protocol (UDP), hypertext transfer protocol (HTTP), etc.). Example communication networks may include a local area network (LAN), a wide area network (WAN), a packet data network (e.g., the Internet), a mobile phone network (e.g., a cellular network), a plain old telephone (POTS) network, and a wireless data network (e.g., a wireless network called The Institute of Electrical and Electronics Engineers (IEEE) 802.11 series of standards, known as 802.16 series of standards), IEEE 802.15.4 series of standards, peer-to-peer (P2P) networks, etc. In an example, the network interface device 820 may include one or more physical sockets (e.g., Ethernet sockets, coaxial cable sockets, or telephone sockets) or one or more antennas to connect to the communication network 826. In an example, the network interface device 820 may include multiple antennas to wirelessly communicate using at least one of single-input multiple-output (SIMO), multiple-input multiple-output (MIMO), or multiple-input single-output (MISO) technologies. The term "transmission medium" should be understood to include any intangible medium capable of storing, encoding, or carrying instructions for execution by the machine 800, and includes digital or analog communication signals or other intangible media that facilitate the communication of such software. Transmission media are machine-readable media.

[0097] Various embodiments are shown in the above figures. One or more features from one or more of these embodiments can be combined to form other embodiments. The method examples described herein may be at least partially machine or computer implemented. Some examples may include a computer-readable medium or a machine-readable medium, which is encoded with instructions that can be operated to configure an electronic device or system to perform the methods described in the above examples. The implementation of this method may include code, such as microcode, assembly language code, high-level language code, etc. This code may include computer-readable instructions for performing various methods. The code may form parts of a computer program product. Further, the code may be tangibly stored on one or more volatile or non-volatile computer-readable media during execution or at other times.

[0098] The above detailed description is intended to be illustrative rather than limiting. The scope of the disclosure should, therefore, be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled.

Claims

1. A medical device system, comprising: a signal receiver circuit configured to receive exertion information of a subject and cardiac acceleration information of the subject, the cardiac acceleration information including third heart sound (S3) information of the subject; as well as An evaluation circuit, the evaluation circuit being configured to: using the received exertion information to determine a rest period for the subject; using the received exertion information to determine an exertion period of the subject; determining a measure of cardiac acceleration information of the subject during the determined rest period, including a measure of S3 information of the subject during the determined rest period; determining a measure of cardiac acceleration information of the subject during the determined period of exertion, including a measure of S3 information of the subject during the determined period of exertion; determining a determined measure of cardiac acceleration information of the subject during the determined exertion period, including a measure of S3 information of the subject during the determined exertion period, relative to a determined measure of cardiac acceleration information of the subject during the determined rest period, including a change in amplitude or energy of the measure of S3 information of the subject during the determined rest period; as well as Using the determined metrics, which include a metric of the subject's S3 information during a determined period of exertion and a metric of the subject's S3 information during a determined period of rest, the determined change in amplitude or energy is determined to be indicative of heart failure with preserved ejection fraction (HFpEF) in the subject.

2. The system of claim 1, wherein the cardiac acceleration information comprises S3 information of the subject and at least one of: first heart sound (S1) information of the subject, second heart sound (S2) information of the subject, or fourth heart sound (S4) information of the subject, wherein the measure of the cardiac acceleration information comprises a ratio of the S3 information to at least one of the S1 information, the S2 information, or the S4 information, and The S1 information, the S2 information, the S3 information and the S4 information include the amplitude or energy of the corresponding information.

3. The system of claim 1 , wherein the evaluation circuit is configured to: trending the determined measure of cardiac acceleration information of the subject for the determined resting period; trending the determined measure of cardiac acceleration information of the subject during the determined period of exertion; and Trending is used to determine the change in magnitude or energy of the determined measure of the subject's cardiac acceleration information during the determined period of exertion relative to the determined measure of the subject's cardiac acceleration information during the determined period of rest.

4. The system of claim 1 , wherein the signal receiver circuit is further configured to receive posture information of the subject, and The evaluation circuit is configured to: determining a rest period of the subject using the received effort information and the received posture information, and The received exertion information and the received posture information are used to determine an exertion period of the subject.

5. The system of claim 1 , wherein the evaluation circuit is configured to: trending the determined change in the determined measure of the subject's heart acceleration information during the determined period of exertion relative to the determined measure of the subject's heart acceleration information during the determined period of rest, and Trends are used to determine changes in the subject's heart acceleration information.

6. The system of any one of claims 1 to 5, wherein the signal receiver circuit is configured to receive the subject's heart acceleration information and the subject's exertion information at different times using the same acceleration sensor, and The evaluation circuit is configured to: using acceleration information from the acceleration sensor to determine an effort level, detecting a transition from a first exertion level to a second, lower exertion level, determining, after the detected transition from the first exertion level to the second exertion level, a first measure of subject cardiac acceleration information indicative of cardiac acceleration information of the subject at the first exertion level, and After a recovery period following the detected transition from the first exertion level to the second exertion level, a second measure of cardiac acceleration information of the subject is determined that is indicative of cardiac acceleration information of the subject at the second exertion level.

7. The system according to claim 6, comprising a posture sensor configured to sense posture information of the subject, Wherein the evaluation circuit is configured to detect a transition from the first exertion level to the lower second exertion level using exertion information of the subject and posture information of the subject.

8. The system according to claim 6, comprising an acceleration sensor configured to sense cardiac acceleration information of the subject and exertion information of the subject, wherein the signal receiver circuit is configured to receive the subject's heart acceleration information and the subject's exertion information from the acceleration sensor, and Wherein the second exertion level is resting.

9. The system according to any one of claims 1 to 5, comprising: a cardiac acceleration sensor configured to sense cardiac acceleration information of the subject; as well as an activity sensor configured to sense exertion information of the subject, The signal receiver circuit is configured to receive cardiac acceleration information of the subject from the cardiac acceleration sensor and to receive effort information of the subject from the activity sensor, wherein the cardiac acceleration information includes information indicating a third heart sound (S3) or a fourth heart sound (S4) of the subject.

10. The system of any one of claims 1 to 5, wherein the assessment circuit is configured to determine an indication of HFpEF in the subject using a determined change in cardiac acceleration information during exertion relative to cardiac acceleration information of the subject at rest that is greater than a HFpEF threshold.

11. The system of any one of claims 1 to 5, wherein to determine the indication of HFpEF in the subject, the evaluation circuit is configured to use the determined change in cardiac acceleration information to determine the indication of worsening HFpEF in the subject, the system further comprising: A user interface is configured to provide a human-perceptible alert to the subject or a clinician using the determined indication of worsening of HFpEF in the subject.

12. A method for controlling a medical device system, comprising: receiving, using a signal receiver circuit, exertion information of the subject and cardiac acceleration information of the subject, the cardiac acceleration information including third heart sound (S3) information of the subject; using the received exertion information to determine a rest period for the subject; using the received exertion information to determine an exertion period of the subject; determining a measure of cardiac acceleration information of the subject during the determined rest period, including a measure of S3 information of the subject during the determined rest period; determining a measure of cardiac acceleration information of the subject during the determined period of exertion, including a measure of S3 information of the subject during the determined period of exertion; determining a determined measure of cardiac acceleration information of the subject during the determined exertion period, including a measure of S3 information of the subject during the determined exertion period, relative to a determined measure of cardiac acceleration information of the subject during the determined rest period, including a change in amplitude or energy of the measure of S3 information of the subject during the determined rest period; as well as Using the determined metrics, which include a metric of the subject's S3 information during a determined period of exertion and a metric of the subject's S3 information during a determined period of rest, the determined change in amplitude or energy is determined to be indicative of heart failure with preserved ejection fraction (HFpEF) in the subject.

13. The method according to claim 12, wherein the cardiac acceleration information includes S3 information of the subject and at least one of: the subject's first heart sound (S1) information, the subject's second heart sound (S2) information, or the subject's fourth heart sound (S4) information.

14. The method according to claim 12, comprising: trending the determined measure of cardiac acceleration information of the subject for the determined resting period; as well as trending the determined measure of the subject's cardiac acceleration information for the determined period of exertion, in determining said change in magnitude or energy of said determined measure of said subject's cardiac acceleration information during said determined period of exertion relative to said determined period of rest comprises using a trend, and Wherein determining the indication of HFpEF in the subject comprises using the determined change in magnitude or energy of the determined metric.

15. The method of claim 12, wherein receiving the subject's cardiac acceleration information and the subject's exertion information comprises using the same acceleration sensor at different times, the method further comprising: using acceleration information from the acceleration sensor to determine an effort level, detecting a transition from a first exertion level to a second, lower exertion level, determining, after the detected transition from the first exertion level to a second exertion level, a first measure of subject cardiac acceleration information indicative of cardiac acceleration information of the subject at the first exertion level, and After a recovery period following the detected transition from the first exertion level to the second exertion level, a second measure of cardiac acceleration information of the subject is determined that is indicative of cardiac acceleration information of the subject at the second exertion level.

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