P-wave window determination based on cardiac acceleration

Abstract

Systems and methods are disclosed for determining a P-wave window for a patient using cardiac acceleration information of the patient including a determined time of the S4 heart sound. A correlation between the S4 template and cardiac acceleration information in the S4 window having a longer duration than the S4 template may be determined. A S4 centroid may be determined as a peak of the determined plurality of correlations, and a P-wave window may be determined using the determined S4 centroid and electromechanical delay.

Description

[0001] Cross - Reference to Related Applications

[0002] This application claims the benefit of priority to U.S. Provisional Application No. 63 / 430,103, filed on December 5, 2022, which is incorporated herein by reference in its entirety. Technical Field

[0003] This invention document generally relates to medical devices, and more particularly to the determination of a P - wave window using cardiac acceleration information. Background Art

[0004] Heart failure (HF) is a decline in the heart's ability to pump enough blood to meet the body's needs. Patients with heart failure typically present with an enlarged heart and weakened myocardium, resulting in reduced contractility and poor cardiac output. Signs of heart failure include pulmonary congestion, edema, dyspnea, etc. Heart failure is usually a chronic disease, but can also occur suddenly, affecting the left side, right side, or both sides of the heart. Causes of heart failure include coronary artery disease, myocardial infarction, hypertension, atrial fibrillation, valvular heart disease, alcoholism, infection, cardiomyopathy, or one or more other conditions that reduce the efficiency of the heart's pumping.

[0005] Arrhythmia is an abnormal heart rhythm (e.g., too fast, too slow, irregular, etc.). Arrhythmias include bradycardia, tachycardia, premature beats, extra or skipped heartbeats, and atrial or ventricular fibrillation affecting one or more chambers of the heart. Atrial fibrillation (AF) is an abnormal heart rhythm characterized by rapid and irregular activity in the left or right atrium of the heart. Atrial fibrillation is usually associated with a reduction in cardiac output and an increased risk of heart failure, dementia, and stroke. Risk factors for atrial fibrillation include hypertension, heart failure, valvular heart disease, chronic obstructive pulmonary disease (COPD), obesity, and sleep apnea, etc.

[0006] An ambulatory medical device (AMD), including implantable, subcutaneous, wearable, or one or more other medical devices, etc., can monitor, detect, or treat various conditions, including heart failure, atrial fibrillation, etc. The ambulatory medical device can include a sensor for sensing physiological information from a patient, and one or more circuits for using the sensed physiological information to detect one or more physiological events or transmit the sensed physiological information or detected physiological events to one or more remote devices. Frequent patient monitoring can provide early detection of patient deterioration, including deteriorating heart failure or atrial fibrillation. Accurate identification of patients or patient groups at an elevated risk of future adverse events can control the mode or feature selection or resource management of one or more ambulatory medical devices, control notifications or messages to various users associated with a specific patient or patient group in a connected system, organize or schedule doctor or patient contacts or treatments, or prevent or reduce patient hospitalizations. Correctly identifying and safely managing the risk of patient deterioration can avoid unnecessary medical interventions, extend the service life of ambulatory medical devices, and reduce medical costs. Summary of the Invention

[0007] Systems and methods are disclosed for determining a P-wave window for a patient using the patient's cardiac acceleration information, including the time of the determined S4 heart sound. A correlation can be determined between an S4 template and cardiac acceleration information in an S4 window having a duration longer than that of the S4 template. The S4 centroid can be determined as the peak of the determined plurality of correlations, and the determined S4 centroid and electromechanical delay can be used to determine the P-wave window.

[0008] An example (e.g., "Example 1") of a subject matter (such as a medical device system) can include a signal receiver circuit configured to receive the patient's cardiac acceleration information; a cardiac acceleration assessment circuit configured to use the received patient's cardiac acceleration information to determine the time of the patient's S4 and determine a P-wave window for the patient based on the determined time of the S4; and a cardiac electrical feature detection circuit configured to use the determined P-wave window to detect or confirm one or more cardiac electrical features.

[0009] In Example 2, the subject matter described in Example 1 may optionally be configured such that the signal receiver circuit is configured to receive cardiac acceleration information of a patient from an S4 window of one or more cardiac cycles. To determine the time of S4, the cardiac acceleration evaluation circuit is configured to: determine a plurality of correlations of the S4 template with different portions of the cardiac acceleration information in the S4 window, the S4 window having a duration longer than the duration of the S4 template; use the peak amplitudes of the determined plurality of correlations to determine the S4 centroid for one or more cardiac cycles; and use the determined S4 centroid to determine the time of S4; and the cardiac acceleration evaluation circuit is configured to use the determined S4 centroid and the electromechanical delay to determine the P-wave window for the patient.

[0010] In Example 3, the subject matter described in any one or more of Examples 1 to 2 may optionally be configured such that the cardiac acceleration information includes heart sound information, and the cardiac acceleration evaluation circuit is configured to determine the time of S4 as the time of the peak amplitude of the determined plurality of correlations in the S4 window.

[0011] In Example 4, the subject matter described in any one or more of Examples 1 to 3 may optionally be configured such that the cardiac acceleration evaluation circuit is configured to determine a plurality of correlations of the S4 template, each of the plurality of correlations being with a different portion of the cardiac acceleration information along the S4 window.

[0012] In Example 5, the subject matter described in any one or more of Examples 1 to 4 may optionally be configured such that the different portions have different, non-overlapping times along the S4 window.

[0013] In Example 6, the subject matter described in any one or more of Examples 1 to 5 may optionally be configured such that the cardiac acceleration evaluation circuit is configured to detect S4 in the cardiac acceleration information using the peak amplitudes of the determined plurality of correlations of the S4 template, and the S4 template includes a non-atrial fibrillation S4 template.

[0014] In Example 7, the subject matter described in any one or more of Examples 1 to 6 may optionally be configured such that the received cardiac acceleration information includes cardiac acceleration information from a late diastolic signal portion in one or more cardiac cycles, the S4 window includes a first S4 window, the first S4 window includes a first sub-portion of the late diastolic signal portion, the cardiac acceleration evaluation circuit is configured to determine a plurality of correlations of the S4 template with different portions of the cardiac acceleration information in a plurality of S4 windows along the late diastolic signal portion, and the cardiac acceleration evaluation circuit is configured to determine the S4 centroid for one or more cardiac cycles as the peak amplitudes of the determined plurality of correlations.

[0015] In Example 8, the subject matter according to any one or more of Examples 1 to 7 may optionally be configured such that the one or more cardiac cycles include a first cardiac cycle, the cardiac acceleration assessment circuit is configured to determine the S4 centroid for the first cardiac cycle, and the cardiac electrical feature detection circuit is configured to use the determined S4 centroid for the first cardiac cycle to detect a P wave in a second cardiac cycle after the first cardiac cycle.

[0016] In Example 9, the subject matter according to any one or more of Examples 1 to 8 may optionally be configured such that the cardiac acceleration information of a patient from an S4 window of one or more cardiac cycles includes ensemble-averaged cardiac acceleration information of a plurality of cardiac cycles.

[0017] In Example 10, the subject matter according to any one or more of Examples 1 to 9 may optionally be configured such that the cardiac electrical feature detection circuit is configured to use the determined P wave window to detect the presence of a P wave event in the determined P wave window of one or more cardiac cycles.

[0018] In Example 11, the subject matter according to any one or more of Examples 1 to 10 may optionally be configured such that the cardiac electrical feature detection circuit is configured to use the determined P wave window to determine the confidence of an atrial fibrillation event in one or more cardiac cycles.

[0019] An example (e.g., "Example 12") of the subject matter (e.g., a method) may include receiving (e.g., using a signal receiver circuit) cardiac acceleration information of a patient; using the received cardiac acceleration information of the patient to determine (e.g., using a cardiac acceleration assessment circuit) the time of the patient's S4; determining (e.g., using a cardiac acceleration assessment circuit) a P wave window for the patient based on the determined time of the S4; and using the determined P wave window to detect or confirm (e.g., using a cardiac electrical feature detection circuit) one or more cardiac electrical features.

[0020] In Example 13, the subject matter according to Example 12 may optionally be configured such that receiving cardiac acceleration information of a patient includes receiving cardiac acceleration information from an S4 window of one or more cardiac cycles of the patient, determining the time of the S4 includes: determining a plurality of correlations of different portions of the S4 template with the cardiac acceleration information in the S4 window, the S4 window having a duration longer than the duration of the S4 template; using the peak amplitudes of the determined plurality of correlations to determine the S4 centroid for one or more cardiac cycles; and using the determined S4 centroid to determine the time of the S4, and determining a P wave window for the patient includes using the determined S4 centroid and the electromechanical delay.

[0021] In Example 14, the subject matter described in any one or more of Examples 12 to 13 may optionally be configured such that the cardiac acceleration information includes heart sound information, and determining the time of S4 includes determining the time of the peak amplitude of the determined plurality of correlations in the S4 window.

[0022] In Example 15, the subject matter described in any one or more of Examples 12 to 14 may optionally be configured such that the cardiac acceleration evaluation circuit is configured to determine a plurality of correlations of the S4 template, each of the plurality of correlations with respect to a different portion of the cardiac acceleration information along the S4 window.

[0023] In Example 16, the subject matter described in any one or more of Examples 12 to 15 may optionally be configured such that the different portions have different, non - overlapping times along the S4 window.

[0024] In Example 17, the subject matter described in any one or more of Examples 12 to 16 may optionally be configured to detect S4 in the cardiac acceleration information using the peak amplitudes of the determined plurality of correlations of the S4 template, wherein the S4 template includes a non - atrial fibrillation S4 template.

[0025] In Example 18, the subject matter described in any one or more of Examples 12 to 17 may optionally be configured such that the received cardiac acceleration information includes cardiac acceleration information from a late diastolic signal portion in one or more cardiac cycles, the S4 window includes a first S4 window, the first S4 window includes a first sub - portion of the late diastolic signal portion, determining the plurality of correlations of the S4 template includes: determining the plurality of correlations of the S4 template with respect to different portions of the cardiac acceleration information in a plurality of S4 windows along the late diastolic signal portion, and determining the S4 centroid for one or more cardiac cycles includes: determining the S4 centroid for one or more cardiac cycles as the peak amplitude of the determined plurality of correlations.

[0026] In Example 19, the subject matter described in any one or more of Examples 12 to 17 may optionally be configured such that the one or more cardiac cycles include a first cardiac cycle, determining the S4 centroid for one or more cardiac cycles includes determining the S4 centroid for the first cardiac cycle, and the method includes using the determined S4 centroid for the first cardiac cycle to detect the P wave in a second cardiac cycle after the first cardiac cycle.

[0027] In Example 20, the subject matter described in any one or more of Examples 12 to 19 may optionally be configured such that the cardiac acceleration information of a patient from the S4 window of one or more cardiac cycles includes ensemble - averaged cardiac acceleration information of a plurality of cardiac cycles.

[0028] In Example 21, the subject matter described in any one or more of Examples 12 to 20 may optionally be configured such that detecting one or more cardiac electrical features includes using the determined P-wave window to detect whether a P-wave event exists in the determined P-wave window of one or more cardiac cycles.

[0029] In Example 22, the subject matter described in any one or more of Examples 12 to 21 may optionally be configured such that detecting or confirming one or more cardiac electrical features includes using the determined P-wave window to determine the confidence level of an atrial fibrillation event in one or more cardiac cycles.

[0030] In Example 23, the subject matter (e.g., a system or device) may optionally be combined with any part or any combination of parts described in any one or more of Examples 1 to 22 to include a "device" or at least one "non-transitory machine-readable medium" for performing any part of the functions or methods described in any one or more of Examples 1 to 22, the non-transitory machine-readable medium including instructions that, when executed by a machine, cause the machine to perform any part of the functions or methods described in any one or more of Examples 1 to 22.

[0031] 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 disclosure. The detailed description is included to provide further information about the patent application. Other aspects of the disclosure will be apparent to those skilled in the art upon reading and understanding the following detailed description and referring to the drawings that form a part thereof, and each of the detailed description and the drawings should not be regarded as restrictive. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In the drawings, which are not necessarily to scale, like numerals may describe similar components in different views. Like numerals with different letter suffixes may represent different instances of similar components. By way of example and not limitation, the drawings generally illustrate the various embodiments discussed in the present invention.

[0033] Figure 1 The relationship between the measured patient physiological information (including patient heart sound information) and cardiac electrical information during a cardiac cycle is shown.

[0034] Figure 2 An example heart sound template is shown.

[0035] Figure 3 An example late diastolic information is shown.

[0036] Figure 4 An example process for determining the centroid of S4 is shown.

[0037] Figure 5 An example flow chart is shown for determining a P-wave window using the determined S4 centroid.

[0038] Figure 6 Different example S4 templates are shown.

[0039] Figure 7 An example system for determining an S4 centroid is shown.

[0040] Figure 8 An example patient management system and a portion of the environment in which the patient management system may operate are shown.

[0041] Figure 9 A block diagram of an example machine is shown on which any one or more of the techniques discussed herein may be performed. Detailed Description

[0042] Implantable and ambulatory medical devices may include one or more electrodes, or be configured to receive cardiac electrical information therefrom, which are located within, on, or near the heart, such as coupled to leads and located within one or more chambers of the heart or within the vasculature of the heart near one or more chambers. Additionally, ambulatory medical devices may include one or more accelerometer sensors, or be configured to receive mechanical acceleration information therefrom, to determine and monitor patient acceleration information, such as cardiac vibration information associated with blood flow or movement in the heart or patient vasculature (e.g., heart sounds, heart wall movement, etc.), patient body activity or position information (e.g., patient posture, activity, etc.), respiratory information (e.g., respiratory rate, respiratory phase, ventilation sounds, etc.), and the like.

[0043] Arrhythmia events (including potential arrhythmia events, such as atrial fibrillation events or potential events) can be detected using sensed or received cardiac electrical information, which includes, for example, detected atrial or ventricular events (such as beats, r-waves, p-waves, etc.) or intervals therebetween that occur within a detection window, which is typically between 30 seconds and 2 minutes, although it may be longer or shorter in some examples. A mobile medical device can, for example, use timing information between events (in some examples, in combination with one or more other detected events) to determine whether atrial fibrillation is present in each detection window, and can additionally determine, based on that determination, what sensed or detected information to store or transmit, such as for transmission to a remote device. In some examples, a mobile medical device can aggregate information from multiple sensors, use the information from each sensor individually or in combination to detect various events, update a detection status based on that information, and transmit a message or alert to one or more remote devices that a detection has been completed, information has been stored or transmitted, such that one or more additional processes or systems can use the stored or transmitted detection or information for one or more other examinations or processes.

[0044] Atrial fibrillation detection algorithms typically rely on cardiac electrical information features, such as the cardiac cycle interval between consecutive R waves, the rate variance between beats, etc. Examples of atrial fibrillation detection algorithms (including various atrial fibrillation detection parameters and criteria) can be found in the following commonly assigned U.S. patent applications: For example, U.S. Patent Application No. 14 / 825,669 to Krueger et al. entitled "Atrial Fibrillation Detection Using Ventricular Rate Variability" (hereinafter referred to as "'669"); U.S. Patent Application No. 15 / 082,440 to Perschbacher et al. entitled "Atrial Fibrillation Detection" (hereinafter referred to as the "'440 application"); U.S. Patent Application No. 15 / 341,565 to Krueger et al. entitled "Method and Apparatus for Enhancing Ventricular Based Atrial Fibrillation Detection Using Atrial Activity" (hereinafter referred to as the "'565 application"); and U.S. Patent Application No. 15 / 864,953 to Perschbacher et al. entitled "Atrial Fibrillation Discrimination Using Heart Rate Clustering" (hereinafter referred to as the "'953 application"), each of which is incorporated herein by reference in its entirety, and the disclosures of which include atrial fibrillation detection and atrial fibrillation detection algorithms, including, for example: atrial fibrillation detection using paired ventricular information detected from the ventricles (including rate changes and rate change characteristics), and the determination of valid heartbeats or intervals using various characteristics (including threshold rates, intervals, morphological criteria, etc.), such as disclosed in the '669 application; atrial fibrillation detection using the distribution of ventricular depolarization intervals, such as disclosed in the '440 application; atrial fibrillation detection using an atrial activity score from an atrial detection window prior to detected ventricular polarization, such as disclosed in the '565 application; atrial fibrillation discrimination using clustered depolarization information, for example, as disclosed in the '953 application, etc.

[0045] Heart sounds are recurring mechanical signals associated with heart vibrations or accelerations caused by blood flow through the heart or other cardiac movements during each cardiac cycle or interval, and can be separated and classified according to activities associated with such vibrations, accelerations, movements, pressure waves, or blood flow. Heart sounds include four main features: the first through fourth heart sounds (S1 to S4, respectively). The first heart sound (S1) is a vibratory sound emitted by the heart at the onset of systole (or ventricular contraction) during the closure of the atrioventricular (AV) valves (mitral and tricuspid valves) and the opening of the aortic valve. The second heart sound (S2) is a vibratory sound emitted by the heart at the onset of diastole (or ventricular relaxation) during the closure of the aortic and pulmonary valves. The third heart sound (S3) and fourth heart sound (S4) are related to the filling pressure of the left ventricle during diastole. A sudden halt in early diastolic filling can cause the third heart sound (S3). Vibrations caused by the late atrial kick can cause the fourth heart sound (S4). Valve closures, blood movements, and pressure changes in the heart can cause accelerations, vibrations, or movements of the heart wall, which can be detected using accelerometers or microphones to provide an output referred to herein as "heart acceleration information".

[0046] The S4 heart sound, which reflects atrial contraction during sinus rhythm, is generally absent during atrial fibrillation. Thus, in some examples, the determination of the presence or absence of the S4 heart sound can be used to improve the determination of atrial fibrillation. For example, the S4 morphology can be used to determine whether the S4 heart sound is present in the S4 window during a particular cardiac cycle, such as disclosed in the commonly assigned U.S. Patent Application No. 16 / 215,230 to Thakur et al. entitled "Systems And Methods For Detecting Atrial Tachyarrhythmia Using Heart Sounds" (hereinafter referred to as the "‘230 application"), which is incorporated herein by reference in its entirety, the disclosure of which includes comparing a fourth heart sound (S4) signal portion with an S4 template and determining whether its match score exceeds a threshold, and using the determined score to improve the determination of atrial fibrillation.

[0047] However, in some patients, during atrial fibrillation, there are at least some heart sound signals in the S4 window (in some examples, including at least some portions of the S4 signal), such that their presence or absence alone may not provide the most accurate determination of atrial fibrillation. Thus, to improve the sensitivity and specificity of atrial fibrillation detection, a separate and specific atrial fibrillation S4 signal template and a non-atrial fibrillation S4 signal template can be determined, and the S4 signal portion of the heart sound signal can be compared to the separate and specific atrial fibrillation S4 signal template and the non-atrial fibrillation S4 signal template, and the resulting atrial fibrillation determination can be made based on these two comparisons, such as, for example:

[0048] score = corr(data(t), nonAF_model) - corr(data(t), AF_model) (1)

[0049] The score can include a determination of whether the S4 signal portion more accurately represents the S4 signal portion during non-atrial fibrillation (e.g., normal sinus rhythm) or during atrial fibrillation, as compared to a crude determination of presence or absence alone. For example, a positive score can indicate a non-atrial fibrillation S4 heart sound, and a negative score can indicate an atrial fibrillation S4 heart sound. The term "corr" can be a correlation function configured to determine the similarity between two signals, "data(t)" can be the S4 signal portion of the heart sound signal,

[0050] "nonAF_model" can be the non-atrial fibrillation S4 signal template, and "AF_model" can be the atrial fibrillation S4 signal template.

[0051] In other examples, the determination can additionally include other fiducial points or patterns or spectral components of the S4 signal portion, such as those described herein. The improved sensitivity and specificity of the atrial fibrillation determination can improve the detection of false positive atrial fibrillation episodes, thereby more accurately controlling the active sensing mode or data storage mode (e.g., sampling time, sampling frequency, length of the stored episode, etc.) of a mobile medical device or sensor associated with such determination, reducing the storage of false positive atrial fibrillation episodes, reducing the data transmission of the stored episodes to one or more remote devices, reducing the manual review of such transmitted and determined events or episodes, or providing or changing one or more treatment parameters to a patient based on the detected events or determination. In some examples, the initial detection of an atrial fibrillation event can be negated or confirmed based on positive and negative scores, respectively. In other examples, based on the determined positive and negative scores, etc., data can be relabeled, triggered storage can be revoked, mode transitions can be revoked, etc.

[0052] In atrial fibrillation detection based solely on cardiac electrical information (e.g., ECG), such as without heart sound or P wave confirmation, P waves were detected in only 30 - 35% of false atrial fibrillation detections. While P wave confirmation can improve false positive atrial fibrillation detection compared to detection based solely on cardiac electrical information, and the presence of the S4 heart sound can provide a separate indication of the presence of P waves in view of false detections (such as those caused by artifacts, noise, vector or lead placement, or specific patient anatomy), determination of the separate correlation with a separate specific atrial fibrillation S4 signal template and a separate non - atrial fibrillation S4 signal template can further improve the performance of atrial fibrillation detection.

[0053] The inventors have further recognized additional improvements to cardiac inductive sensing and the use of heart sounds for cardiac event determination. One challenge in arrhythmia detection is the accurate sensing and classification of cardiac events. The time periods between cardiac features or events can be used to detect or determine different cardiac parameters, such as heart rate or the inter - beat interval between consecutive cardiac features, etc. False detections or misclassifications can lead to incorrect determination of arrhythmias or other cardiac events, triggering additional unnecessary use of device resources in aspects such as changing the detection mode, storing information about the false event, transmitting the information to one or more other devices, and in some examples affecting one or more detected CRM parameters, etc. For example, P wave oversensing (PWOS) is a situation where P waves are incorrectly detected as one or more other cardiac features, typically R waves, such that the determination of heart rate or the interval between consecutive R waves becomes irregular and rapid, often leading to misclassification of atrial fibrillation, etc. The inventors have recognized that, among other things, although P waves can be used to determine the expected time of the S window, the detected S4 heart sound can also be used to determine the expected P wave window, which can be used (among other things) to reduce P wave oversensing, thereby improving the detection of cardiac features and the detection of cardiac events, such as subsequent P waves after the detected S4 heart sound.

[0054] There are the following technical problems in medical devices, that is, in a low-power monitoring mode, a mobile medical device powered by one or more rechargeable or non-rechargeable batteries must make a certain compromise between battery life (or in the case of an implantable medical device with non-rechargeable batteries, the device replacement period which usually includes surgery) and sampling resolution, sampling period, and the processing, storage, and transmission of the sensed physiological information. The medical device may include a higher-power monitoring mode. Physiological information (such as physiological information indicating a potential adverse physiological event) can be used to switch from a low-power monitoring mode (such as a low-power mode) to a higher-power or higher-resolution monitoring mode (such as a high-power mode). In some examples, the low-power mode may include a low-resource mode, which is characterized by requiring less power, processing time, memory, or communication time or bandwidth (such as transmitting less data, etc.) than the corresponding high-power mode. The high-power mode may include a relatively high-resource mode, which is characterized by requiring more power, processing time, memory, or communication time or bandwidth than the corresponding low-power mode. However, when the physiological information detected in the low-power mode indicates a possible event, valuable information has been lost and thus cannot be recorded in the high-power mode.

[0055] Conversely, an incorrect or inaccurate determination that triggers the high-power mode does not necessarily unduly limit the available life of certain mobile medical devices. The change in mode can enable higher-resolution sampling, or sampling frequency, or an increase in the number or type of sensors used to sense physiological information before and during a potential event. For example, heart sounds and patient activity are typically detected using non-overlapping time periods of the same uniaxial or multi-axial accelerometer at different sampling frequencies and power costs. In one example, the transition to the high-power mode may include: using the accelerometer to continuously detect heart sounds throughout the high-power mode, or detecting heart sounds in the high-power mode for a larger percentage of time compared to the corresponding low-power mode. In addition, waveforms for medical events are typically recorded, stored in long-term memory, and often transmitted to a remote device for clinician review. In some examples, only a notification that the event has been stored or a summary of the event is transmitted. In response, the complete event may be requested for subsequent transmission and review. However, even in the case where the event is stored instead of transmitted, the resources for storing and processing the event are still provided by the medical device. Therefore, for many reasons, it is advantageous to accurately detect and determine physiological events (including reducing false positive device detections) to appropriately manage and utilize the resources of the medical device.

[0056] Figure 1Shows the relationship 100 between the measured patient physiological information (including patient heart sound information 101 (including first heart sound (S1) 103, second heart sound (S2) 104, third heart sound (S3) 105, fourth heart sound (S4) 106, ejection sound 107, systolic murmur 108, opening sound between S2 and S3, and diastolic murmur 109)) and cardiac electrical information 102 (including P wave 112, Q wave 113, R wave 114, S wave 115, and T wave 116 of an electrocardiogram signal) during a cardiac cycle (including periods of systole 110 and diastole 111).

[0057] In Figure 1 it, the horizontal axis is time and the scale is not labeled because the time of the cardiac cycle depends on the patient's heart rate, which varies widely (e.g., typically between 60 and 100 beats per minute (bpm), but more or less in some examples). Systole 110 typically begins with the appearance of the R wave 114 and S1 103 and ends at the T wave 116. Diastole 111 typically begins after the T wave 116 and the appearance of S2 104 and includes S3 105 and S4 106. The duration of diastole 111 is typically longer than the duration of systole 110, often being 2 times as long, etc.

[0058] Figure 2 Shows an example heart sound template 200 in the S4 window, which includes an atrial fibrillation S4 signal template 201 and a non - atrial fibrillation S4 signal template 202 (e.g., S4 signal template under normal sinus rhythm). In some examples, the atrial fibrillation and non - atrial fibrillation S4 signal templates 201, 202 can be population templates determined respectively based on the clinical determination of the S4 signal portion in the heart sound waveforms of patients showing atrial fibrillation and non - atrial fibrillation (e.g., normal sinus rhythm).

[0059] The atrial fibrillation signal template 201 and the non - atrial fibrillation signal template 202 can be generated as the mean or median of multiple pre - labeled signal portions (e.g., clinically labeled or determined as atrial fibrillation signal portion or non - atrial fibrillation signal portion, such as by a clinician, a separate detection algorithm, etc.). In some examples, the labeling can include an atrial fibrillation detection algorithm based on cardiac electrical information, which is collected and reviewed over time from a patient or a patient population, etc. In some examples, the corresponding signal template can be updated as more determinations are collected and provided.

[0060] In some examples, the late diastolic window of the heart sound information can include a period of time (e.g., 200 ms, etc.) starting from the end of diastole (marked by the occurrence of the R wave 114 or S1 103). In some examples, the late diastolic period can be longer or shorter depending on the patient's heart rate. For example, if the patient's heart rate is generally slower or faster than the average heart rate (e.g., slower if less than 60 bpm and faster if greater than 80 bpm), the period of the late diastolic window can be extended or shortened accordingly.

[0061] When present in the cardiac cycle, the S4 106 appears between the P wave 112 and the R wave 114 and can be used to provide an indication of the presence of the P wave 112 if the P wave is not otherwise detected or the detection confidence is very low. The inventors have recognized that the detected S4 in the first cardiac cycle can be used to verify, confirm, or determine the P wave sensing window in one or more subsequent cardiac cycles, or can otherwise be used to look back at the cardiac electrical information from the first cardiac cycle or one or more previous cardiac cycles to, for example, adjust the previous P wave detection or determination.

[0062] Figure 3 An example late diastolic information 300 is shown, including heart sound information 301 that occurs within approximately 200 ms of the R wave 114 and up to it in the cardiac cycle or in the aggregated information representing one or more cardiac cycles. In the example, a preliminary S4 window 303 can be determined as the first part (e.g., the first 40 ms) of the period of the late diastolic information 300. In some examples, the S4 window 303 is a sub - part (e.g., less than the whole part) of the late diastolic signal part. One or more additional S4 windows can be determined across the period, which may or may not overlap with one or more other windows (such as the preliminary S4 window 303, etc.).

[0063] Figure 4An example process 400 is shown for determining the S4 centroid 405 in heart sound information using a determined correlation 404 between an S4 model 402 and one or more time periods of heart sound information, such as a preliminary S4 window 403 or one or more other S4 windows, e.g., a time period across late diastolic information 300 or during that time period. The S4 model 402 can be a non-atrial fibrillation (e.g., normal sinus rhythm) S4 model, an atrial fibrillation S4 model, or one or more other S4 models determined using patient information (e.g., specific to the patient), population information, or a combination of patient information and population information, etc. In an example, a correlation (e.g., cross-correlation, etc.) between the S4 model 402 and the preliminary S4 window 403 or one or more other portions of the late diastolic information 300 can be determined, such as using one or more evaluation circuits or other processing circuits. In some examples, the determined correlation 404 can be plotted. The peak of the determined correlation 404 can be determined as the S4 centroid 405. In some examples, the peak of the determined correlation can be compared to one or more patient-specific thresholds or population thresholds to determine if an S4 is present in the preliminary S4 window 403. In some examples, detection using separate S4 windows along the late diastolic information can be used to confirm if a detected S4 is present in one or more cardiac cycles.

[0064] Figure 5 An example flowchart 500 is shown for determining a P wave window using cardiac acceleration information. For example, the received cardiac acceleration information of a patient can be used to determine the time of the S4, such as by determining a representative time of the S4 in the S4 window of the patient. In some examples, the S4 heart sound can be the S4 heart sound from an S4 window of one cardiac cycle, or a composite S4 heart sound determined or representative of the S4 heart sounds in multiple cardiac cycles. The P wave can be determined based on the time of the S4 determined in the S4 window, such as in combination with the electromechanical delay. The electromechanical delay can include a received population value, a value determined based on one or more patient-specific factors (e.g., a first value adjusted by the patient's heart rate or one or more other cardiac electrical or mechanical parameters, etc.), or a patient-specific value received or measured with respect to the patient.

[0065] In an example, the time of S4 can be determined based on the determined centroid of S4. In some examples, one or more steps in example flow chart 500 can be performed using an evaluation circuit or one or more other processing circuits. Although described herein with respect to determining the centroid of S4 based on morphological correlation with an S4 template, in other examples, one or more other S4 detections can be used, such as based on the position of one or more other detected heart sounds, such as a time period from an S2 heart sound, and in some examples also with respect to heart rate and the like. Additionally, the time of the S4 window can be determined based on one or more cardiac electrical parameters or cardiac mechanical parameters (such as the time of S2, etc.). However, the time of the S4 window can be separated from and different from the time of the determined S4.

[0066] At step 501, the S4 window can be isolated, such as in a first cardiac cycle, or in information representing one or more cardiac cycles (such as an ensemble average of multiple cardiac cycles, etc.). In some examples, the S4 window can be a part of the late diastolic window of heart sound information. At step 502, the correlation of the S4 window with an S4 model (such as a non - atrial fibrillation S4 model, etc.) can be used to detect whether an S4 exists in the S4 window. In some examples, the S4 model can be received, for example, from one or more other processing circuits, or the S4 model can be determined using patient - specific information or population information. The correlation between the S4 model and the heart sound information in the S4 window can be determined. In some examples, the correlation can include a supra - threshold correlation, which can indicate the presence of an S4 in the S4 window. If no S4 is detected at step 502, the process can return to step 501 to, for example, adjust the S4 window to one or more other parts of the late diastolic window of heart sound information, or a subsequent cardiac cycle or ensemble average, etc. If an S4 is detected at step 502, the process can proceed to step 503.

[0067] At step 503, the S4 centroid can be determined, such as using the time of the peak or median of the determined correlation of the detected S4. The timing of this centroid can be used to determine one or more other electromechanical time periods or windows.

[0068] At step 504, an electromagnetic delay can be applied to the determined S4 centroid to determine one or more parameters. The electromagnetic delay can include a fixed, generalized P - wave to S4 delay at step 505 (such as 145 ms from the detected P - wave onset to S4), or a patient - specific P - wave to S4 delay at step 506, such as determined using patient - specific information from a previously detected P - wave and S4 centroid or one or more other S4 timings.

[0069] At step 507, a P-wave window can be determined, for example, by applying one or more time periods to the one or more determined parameters. For example, the P-wave window can be determined as a function of the S4 centroid, the electromechanical delay, and a population or patient-specific P-wave width (such as 120 ms, etc.). For example, the P-wave onset can be determined by subtracting the electromechanical delay and half of the P-wave width from the time of the determined S4 centroid. The P-wave end can be determined by subtracting the electromechanical delay from the time of the determined S4 centroid and adding half of the P-wave width.

[0070] In some examples, the P-wave window determined at step 507 can be fed back into the electromechanical delay, such as patient-specific information, etc. At step 508, the determined P-wave window can be used to detect P-waves, such as in one or more subsequent cardiac cycles. In other instances, information from the determined P-wave window can be used to retrospectively view the P-wave window in the first cardiac cycle or one or more previous cardiac cycles to, for example, determine the confidence of detected or undetected P-waves.

[0071] Figure 6 A different example S4 template 600 is shown, which includes an example aggregated S4 signal partial composite signal, including true-negative atrial fibrillation detection 601, false-positive atrial fibrillation detection 602 (such as from atrial fibrillation detection based on cardiac electrical information), and positive atrial fibrillation detection 603. The positive atrial fibrillation detection 603 shows a substantial difference from the true-negative atrial fibrillation detection 601 and the false-positive atrial fibrillation detection 602. However, the true-negative atrial fibrillation detection 601 is more similar to the false-positive atrial fibrillation detection 602, showing more subtle changes in the cardiac mechanical signal.

[0072] Figure 7 An example system 700 is shown for determining the presence of an S4 in an S4 window, determining the S4 centroid (such as by determining the correlation between the S4 template and the heart sound information in the S4 window), and using the determined S4 centroid and electromechanical delay to determine a P-wave window.

[0073] The example system 700 can include a medical device system, a cardiac rhythm management (CRM) device, etc. In an example, one or more aspects of the example system 700 can be components of a mobile medical device (AMD), an implantable cardiac monitor, etc., or communicatively coupled to a mobile medical device (AMD), an implantable cardiac monitor, etc. The system 700 can be configured to monitor, detect, or treat various physiological conditions of the body, such as cardiac conditions associated with a reduced ability of the heart to pump blood to the body, including heart failure, arrhythmia, cardiac dyssynchrony, etc., or one or more other physiological conditions, and in some examples can be configured to provide electrical stimulation or one or more other therapies or treatments to a patient.

[0074] System 700 may include a single medical device or multiple medical devices implanted in or otherwise positioned on or around a patient to monitor the patient's physiological information using one or more sensors, such as sensor 701. In an example, sensor 701 may include one or more of the following: a respiratory sensor configured to receive respiratory information (e.g., respiratory rate, respiratory volume (tidal volume), etc.); an acceleration sensor (e.g., an accelerometer, a 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, body position information, etc.); an impedance sensor (e.g., an intrathoracic impedance sensor, a 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 level, number of steps, etc.); a body position sensor configured to receive body position or location information; a pressure sensor configured to receive pressure information; a plethysmography sensor (e.g., a photoplethysmography sensor, etc.); a chemical sensor (e.g., an electrolyte sensor, a pH sensor, an anion gap sensor, etc.); a temperature sensor; a skin elasticity sensor; or one or more other sensors configured to receive the patient's physiological information.

[0075] Example system 700 may include a signal receiver circuit 702 and an evaluation circuit 703. The signal receiver circuit 702 may be configured to receive the physiological information of a patient (or a group of patients) from the sensor 701. The evaluation circuit 703 may be configured to receive information from the signal receiver circuit 702 and use the received physiological information to determine one or more parameters (e.g., physiological parameters, stratification factors, etc.) or an existing or changing patient condition (e.g., an indication of patient dehydration, respiratory condition, cardiac condition (e.g., heart failure, arrhythmia), sleep disordered breathing, etc.), such as described herein. Among other aspects, the physiological information may include cardiac electrical information, impedance information, respiratory information, heart sound information, activity information, body position information, temperature information, or one or more other types of physiological information.

[0076] In certain examples, the evaluation circuit 703 may aggregate information from multiple sensors or devices, use the information from each sensor or device individually or in combination to detect various events, update the detection status for one or more patients based on the information, and transmit a message or alert to one or more remote devices that the detection for one or more patients has been completed or the information has been stored or transmitted, such that one or more additional processes or systems may use the stored or transmitted detection or information for one or more other examinations or processes.

[0077] The evaluation circuit 703 can be configured to provide an output to a user, such as to a display or one or more other user interfaces, the output including a score, a trend, a warning, or other indication. In other examples, the evaluation circuit 703 can be configured to provide an output to another circuit, machine, or process, such as a therapy circuit 904 (e.g., a cardiac resynchronization therapy (CRT) circuit, a chemotherapy circuit, etc.), to control, adjust, or stop the therapy of a medical device, a drug delivery system, etc., or otherwise change one or more processes or functions of one or more other aspects of a medical device system, such as one or more cardiac resynchronization therapy parameters, drug delivery, dose determination, or recommendation, etc. In an example, the therapy circuit 904 can include one or more of a stimulation control circuit, a cardiac stimulation circuit, a nerve stimulation circuit, a dose determination or control circuit, etc. In other examples, the therapy circuit 904 can be controlled by the evaluation circuit 703 or one or more other circuits, etc.

[0078] In certain examples, among other aspects, the evaluation circuit 703 can further include an atrial fibrillation detection circuit and a morphology circuit. The atrial fibrillation detection circuit can be configured to perform one or more atrial fibrillation detection algorithms, or alternatively determine one or more indications of atrial fibrillation in one or more cardiac cycles or in a time window including multiple cardiac cycles, such as to determine one or more measures and compare the one or more measures with a patient-specific threshold or a population threshold. The morphology circuit can be configured to determine the correlation (e.g., cross-correlation, correlation coefficient, correlation waveform analysis, etc.) between the shape of one or more signal features (such as the S4 signal portion of a heart sound signal of one or more cardiac cycles) and one or more templates (such as those described herein), such as to determine one or more measures and compare the one or more measures with a patient-specific threshold or a population threshold. In certain examples, one or more templates can be a patient-specific template or a population template. An indication of either an atrial fibrillation S4 heart sound or a non-atrial fibrillation S4 heart sound in the S4 signal portion can be determined based on the difference between the determined correlations between the S4 signal portion of the heart sound signal and a non-atrial fibrillation S4 template and an atrial fibrillation S4 template.

[0079] In other examples, the determination can additionally include other fiducial points or patterns or spectral components of the S4 signal portion. For example, the amplitude of the frequency components in the S4 window can be used to determine an indication of either an atrial fibrillation S4 heart sound or a non-atrial fibrillation S4 heart sound. Generally, the atrial fibrillation S4 heart sound will have fewer frequency components in the S4 window than the non-atrial fibrillation S4 heart sound. Thus, template frequency components can be determined for each of the atrial fibrillation S4 heart sound and the non-atrial fibrillation S4 heart sound, which is a population template or a patient-specific template, and such templates can be used as additional features in the determination described herein.

[0080] The change in the S4 signal component over time can indicate a change in ventricular stiffness. In an example, an increase in the S4 signal component over time can be used to detect a deteriorating cardiac condition. A relative change above a threshold can trigger an alert, notification, mode switch, or one or more other medical device changes or actions, such as those described herein.

[0081] In other examples, the evaluation circuit 703 can include a cardiac acceleration evaluation circuit 705 and a cardiac electrical feature detection circuit 706. The cardiac acceleration evaluation circuit 705 can be configured to: detect one or more cardiac acceleration events or features, determine one or more correlations between a template and a portion of the cardiac acceleration information, or use the cardiac acceleration information to determine one or more windows or parameters, such as those described herein. The cardiac electrical feature detection circuit 706 can be configured to use the determined P-wave window to detect one or more cardiac electrical features, including, in some examples, being configured to determine an indication of a P-wave event in one or more cardiac cycles, analyze one or more P-wave windows to indicate the presence or absence of a P-wave event, provide confirmation or negation as to whether a determined R-wave event is likely or highly likely to be a P-wave oversensing event (PWOS), or otherwise trigger additional sensing or analysis to, for example, improve the detection and determination of cardiac events in a patient, reduce false positive detections, increase device efficiency, reduce data storage and transmission associated with false positive events, or perform one or more other functions described herein.

[0082] Figure 8 An example patient management system 800 and portions of an environment in which the patient management system 800 can operate are shown. The patient management system 800 can perform a series of activities, including remote patient monitoring and disease condition diagnosis. Such activities can be performed near the patient 801, such as in the patient's home or office; by a central server, such as in a hospital, clinic, or doctor's office; or by a remote workstation, such as a secure wireless mobile computing device.

[0083] The patient management system 800 can include one or more mobile medical devices, an external system 805, and a communication link 811 that provides for communication between the one or more mobile medical devices and the external system 805. The one or more mobile medical devices can include an implantable medical device (IMD) 802, a wearable medical device 803, or one or more other implantable, leadless, subcutaneous, external, wearable, or mobile medical devices that are configured to monitor, sense, or detect information from the patient 801, determine physiological information about the patient 801, or provide one or more therapies to treat various conditions of the patient 801, such as one or more cardiac or non-cardiac conditions (e.g., dehydration, sleep apnea, etc.).

[0084] In an example, the implantable medical device 802 can include one or more conventional cardiac rhythm management devices implanted in a patient's chest, having a lead system that includes one or more transvenous, subcutaneous, or non-invasive leads or catheters to position one or more electrodes or other sensors (such as a heart sound sensor) within, on, or around the heart, or at one or more other locations in the patient 801's chest, abdomen, or neck. In another example, the implantable medical device 802 can include, for example, a monitor subcutaneously implanted in the patient 801's chest, the implantable medical device 802 including a housing containing circuitry, and in some examples, including one or more sensors (such as a temperature sensor, etc.).

[0085] Conventional cardiac rhythm management devices (such as an implantable cardiac monitor, a pacemaker, a defibrillator, or a cardiac resynchronizer) include an implantable or subcutaneous device having a hermetically sealed housing configured to be implanted in a patient's chest. The cardiac rhythm management device can include one or more leads to position one or more electrodes or other sensors at various locations within or near the heart, such as at one or more locations in the atria or ventricles of the heart, etc. Thus, the cardiac rhythm management device can include aspects that are subcutaneous, although near the distal end of the patient's skin, and aspects that are located near one or more organs of the patient, such as leads or electrodes. Separate from, or in addition to, the one or more electrodes or other sensors of the lead, the cardiac rhythm management device can include one or more electrodes or other sensors (such as a pressure sensor, an accelerometer, a gyroscope, a microphone, etc.) powered by a power source within the cardiac rhythm management device. The one or more electrodes or other sensors of the lead, the cardiac rhythm management device, or a combination thereof can be configured to detect physiological information from the patient, or to provide one or more therapies or stimuli to the patient.

[0086] The implantable device may additionally or alternatively include a leadless cardiac pacemaker (LCP), which is a small (e.g., smaller than traditional implantable cardiac rhythm management devices, having a volume of approximately 1 cc in some examples, etc.) self - contained device that includes one or more sensors, circuitry, 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 stimuli to the heart without the complications associated with traditional leads or implantable cardiac rhythm management devices (e.g., the required incisions and pockets, complications associated with lead placement, breakage, or displacement, etc.). In some examples, the leadless cardiac pacemaker may have more limited power and processing capabilities than traditional cardiac rhythm management devices; however, multiple leadless cardiac pacemakers may be implanted in or around the heart to detect physiological information from one or more chambers of the heart or to provide one or more therapies or stimuli to one or more chambers of the heart. The multiple leadless cardiac pacemakers may communicate with each other, or with one or more other implanted devices or external devices.

[0087] The implantable medical device 802 may include an evaluation circuit configured to detect or determine specific physiological information of the patient 801, or determine one or more conditions, or provide information or alerts to a user (such as the patient 801 (e.g., the patient), a clinician, or one or more other caregivers or processes) as described herein. The implantable medical device 802 may alternatively or additionally be configured as a treatment device configured to treat one or more medical conditions of the patient 801. The treatment may be delivered to the patient 801 via a lead system and associated electrodes or using one or more other delivery mechanisms. The treatment may include delivering one or more drugs to the patient 801, such as using the implantable medical device 802 or one or more other mobile medical devices, etc. In some examples, the treatment may include cardiac resynchronization therapy for correcting asynchrony and improving the cardiac function of heart failure patients. In other examples, the implantable medical device 802 may include a drug delivery system, such as a drug infusion pump for delivering drugs to the patient for managing arrhythmias or complications caused by arrhythmias, hypertension, hypotension, or one or more other physiological conditions. In other examples, the implantable medical device 802 may include one or more electrodes configured to stimulate the patient's nervous system or provide stimulation to the muscles of the patient's airway, etc.

[0088] The wearable medical device 803 may include one or more wearable or external medical sensors or devices (e.g., an automated external defibrillator (AED), a Holter monitor, a patch - based device, a smartwatch, a smart accessory, a wrist - worn or finger - worn medical device, such as a finger - based photoplethysmography sensor, etc.).

[0089] The external system 805 can include a dedicated hardware / software system, such as a programmer, a remote server-based patient management system, or alternatively a system primarily defined by software running on a standard personal computer. The external system 805 can manage the patient 801 by connecting to the implantable medical device 802 or one or more other portable medical devices via a communication link 811 that is connected to the external system 805. In other examples, the implantable medical device 802 can be connected to a wearable medical device 803, or the wearable medical device 803 can be connected to the external system 805 via the communication link 811. For example, this can include programming the implantable medical device 802 to perform one or more of acquiring physiological data, performing at least one self-diagnostic test (such as a self-diagnostic test for the device operating state), analyzing physiological data, or optionally delivering or adjusting therapy for the patient 801. Additionally, the external system 805 can send information to or receive information from the implantable medical device 802 or the wearable medical device 803 via the communication link 811. Examples of information can include real-time or stored physiological data from the patient 801, diagnostic data (such as detection of the patient's hydration status, hospitalization, response to therapy delivered to the patient 801), or the device operating state of the implantable medical device 802 or the wearable medical device 803 (e.g., battery state, lead impedance, etc.). The communication link 811 can be an inductive telemetry link, a capacitive telemetry link, or a radio frequency (RF) telemetry link, or a wireless telemetry based on, for example, the "strong" Bluetooth or IEEE 602.11 Wi-Fi interface standards. Other configurations and combinations of patient data source interfaces are possible.

[0090] The external system 805 can include an external device 806 near one or more mobile medical devices and a remote device 808 at a location relatively far from the one or more mobile medical devices that communicates with the external device 806 via a communication network 807. Examples of the external device 806 can include a medical device programmer. Among other possible functions, the remote device 808 can be configured to evaluate the collected patient or patient information and provide alert notifications. In an example, the remote device 808 can include a centralized server that serves as a central hub for storage and analysis of the collected data from multiple different sources. The combination of information from multiple sources can be used to make determinations and update the individual patient status, or adjust one or more alerts or determinations for one or more other patients. The server can be configured as a single, multi-, or distributed computing and processing system. The remote device 808 can receive data from multiple patients. The data can be collected by one or more mobile medical devices other than other data acquisition sensors or devices associated with the patient 801. The server can include a memory device to store the data in a patient database. The server can include an alert analyzer circuit to evaluate the collected data to determine if specific alert conditions are met. The satisfaction of the alert conditions can trigger the generation of an alert notification, such as an alert notification to be provided by one or more human-perceivable user interfaces. In some examples, the alert conditions can alternatively or additionally be evaluated by one or more mobile medical devices (such as an implantable medical device). For example, the alert notification can include a web page update, a phone or pager call, an email, an SMS, a text or "instant" message, a message to the patient, and a direct notification to emergency services and clinicians simultaneously. Other alert notifications are possible. The server can include an alert prioritizer circuit configured to prioritize the alert notifications. For example, alerts for detected medical events can be prioritized using a similarity metric between the physiological data associated with the detected medical event and the physiological data associated with historical alerts.

[0091] The remote device 808 may additionally include one or more locally configured clients or remote clients securely connected to the server via a communication network 807. Examples of clients may include personal desktop computers, laptop computers, mobile devices, or other computing devices. System users, such as clinicians or other qualified medical professionals, may use the clients to securely access the stored patient data compiled in the database in the server, and select patients and alerts and prioritize them for healthcare delivery. In addition to generating alert notifications, the remote device 808 (including the server and interconnected clients) may also execute a follow-up program by sending follow-up requests to one or more mobile medical devices, or by sending messages or other communications to the patient 801 (e.g., the patient), clinician, or authorized third party as compliance notifications.

[0092] The communication network 807 may provide wired or wireless interconnectivity. In an example, the communication network 807 may be based on Transmission Control Protocol / Internet Protocol (TCP / IP) network communication specifications, although other types or combinations of networking implementations are possible. Similarly, other network topologies and arrangements are possible.

[0093] One or more of the external device 806 or the remote device 808 may output a detected medical event to a system user (such as a patient or clinician) or to a process (such as an instance of a computer program executable in a microprocessor). In an example, the process may include automatically generating recommendations for antiarrhythmic treatment or recommendations for further diagnostic tests or treatment. In an example, the external device 806 or the remote device 808 may include a corresponding display unit for displaying physiological or functional signals, or for prompting alerts, alarms, emergency calls, or other forms of warnings indicating the detection of an arrhythmia. In some examples, the external system 805 may include an external data processor configured to analyze physiological or functional signals received by one or more mobile medical devices, and confirm or negate 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.

[0094] Portions of one or more mobile medical devices or external system 805 may be implemented using hardware, software, firmware, or a combination thereof. Portions of one or more mobile medical devices or external system 805 may be implemented using a dedicated circuit that may be constructed or configured to perform one or more functions, or may be implemented using a general-purpose circuit that may be programmed or otherwise configured to perform one or more functions. Such general-purpose circuits may include a microprocessor or a portion thereof, a microcontroller or a portion thereof, or programmable logic circuitry, memory circuitry, network interfaces, and various components for interconnecting these components. For example, among other things, a "comparator" may include an electronic circuit comparator that may be configured to perform a specific function of comparing two signals, or the comparator may be implemented as part of a general-purpose circuit that may be driven by code that instructs the portion of the general-purpose circuit to perform a comparison between two signals. A "sensor" may include an electronic circuit configured to receive information and provide an electronic output representative of the received information.

[0095] Treatment device 810 may be configured to send information to or receive information from one or more mobile medical devices or external system 805 using communication link 811. In an example, one or more mobile medical devices, external device 806, or remote device 808 may be configured to control one or more parameters of treatment device 810. External system 805 may allow programming of one or more mobile medical devices and may receive information about one or more signals acquired by one or more mobile medical devices, such as information that may be received via communication link 811. External system 805 may include a local external implantable medical device programmer. External system 805 may include a remote patient management system that may monitor a patient's status or adjust one or more treatments, for example, from a remote location.

[0096] In certain examples, heart sound morphology may be used to determine an atrial fibrillation event in a patient or to determine the presence or absence of S4 during a cardiac cycle, such as by analyzing the shape of heart sound information in a heart sound window, comparing or correlating the shape of the heart sound information with one or more templates, and the like. An indication of either an atrial fibrillation S4 heart sound or a non-atrial fibrillation S4 heart sound may be determined for the S4 signal portion of the patient's cardiac acceleration information based on a first correlation and a second correlation respectively determined between the morphology of the S4 signal portion and an atrial fibrillation S4 template and a non-atrial fibrillation S4 template. The patient's atrial fibrillation event may be determined using the patient's cardiac electrical information and the indication determined for the S4 signal portion.

[0097] In some examples, physiological information of a patient can be sensed, such as by one or more sensors located within the patient, on the patient's body surface, or near the patient, such as a cardiac sensor, a heart sound sensor, or one or more other sensors described herein. For example, a cardiac sensor can be used to sense cardiac electrical information of the patient. In other examples, a heart sound sensor can be used to sense cardiac acceleration information of the patient. The cardiac sensor and the heart sound sensor can be components of one or more (e.g., the same or different) medical devices (e.g., implantable medical devices, ambulatory medical devices, etc.).

[0098] A timing metric between a first cardiac feature and a second cardiac feature can be determined, such as by a processing circuit of the cardiac sensor or one or more other medical devices or medical device components, etc. In some examples, the timing metric can include: an interval or metric between the first cardiac feature and the second cardiac feature of a first cardiac cycle of the patient (e.g., the duration of a cardiac cycle or interval, QRS width, etc.), or an interval or metric between the first cardiac feature and the second cardiac feature of corresponding consecutive first and second cardiac cycles of the patient. In an example, the first cardiac feature and the second cardiac feature include: equivalent detected features in consecutive first and second cardiac cycles, such as consecutive R waves (e.g., R-R interval, etc.) or one or more other features of a cardiac electrical signal, etc.

[0099] An S4 signal portion can be determined, such as by a processing circuit of the heart sound sensor or one or more other medical devices or medical device components, etc. In some examples, the S4 signal portion can include a filtered signal from an S4 window of a cardiac cycle. In an example, the S4 interval can be determined as a set time period within a cardiac cycle relative to one or more other cardiac electrical or mechanical features, such as a set time period forward from one or more features of an R wave, a T wave, or a heart sound waveform (such as the first heart sound, the second heart sound, or the third heart sound (S1, S2, S3)), or a set time period backward from a detected S1 of a subsequent R wave or a subsequent cardiac cycle. In some examples, the length of the S4 window can depend on the heart rate or one or more other factors. In an example, the timing metric of the cardiac electrical information can be the timing metric of a first cardiac cycle, and the S4 signal portion can be the S4 signal portion of the same first cardiac cycle.

[0100] In an example, cardiac electrical information of the patient can be received, such as using a signal receiver circuit of a medical device, from a cardiac sensor (e.g., one or more electrodes, etc.) or a cardiac sensor circuit (e.g., including one or more amplifier or filter circuits, etc.). In an example, the received cardiac electrical information can include a timing metric between a first cardiac feature and a second cardiac feature of the patient.

[0101] In an example, cardiac acceleration information of a patient can be received from a heart sound sensor (such as an accelerometer, etc.) or a heart sound sensor circuit (such as including one or more amplifier or filter circuits, etc.) using the same or different signal receiver circuits of a medical device. In an example, the received cardiac acceleration information can include an S4 signal portion that occurs between a first cardiac feature and a second cardiac feature of the patient. In some examples, additional physiological information can be received from one or more other sensors or sensor circuits, such as one or more of heart rate information, activity information of the patient, or position information of the patient.

[0102] In some examples, a first correlation and a second correlation of the morphology or shape of the S4 signal portion with a corresponding non - atrial fibrillation S4 template and an atrial fibrillation S4 template can be determined—such as using an evaluation circuit to determine a measure of similarity between different signals. An indication of either an atrial fibrillation S4 heart sound or a non - atrial fibrillation S4 heart sound for the S4 signal portion can be determined based on the determined first correlation and second correlation—such as using an evaluation circuit or one or more other processing circuits to determine the difference between the determined first correlation and second correlation.

[0103] The received timing metric and the determined indication for the S4 signal portion (such as using an atrial fibrillation detection circuit) can be used to determine an atrial fibrillation event of the patient. In an example, an initial determination of atrial fibrillation can be made using only cardiac electrical information, such as based on the heart rate or the timing of consecutive cardiac cycles or intervals or the inter - cardiac cycle timing between groups of cardiac cycles. The initial determination of atrial fibrillation based on cardiac electrical information can trigger the determination of the S4 signal portion of the cardiac acceleration information, the sensing of the cardiac acceleration information (such as within an S4 window of one or more cardiac cycles), or the determination of the first correlation or the second correlation, or the determination of an indication of either an atrial fibrillation S4 heart sound or a non - atrial fibrillation S4 heart sound for the S4 signal portion based on the determined first correlation and second correlation.

[0104] In some examples, the determined atrial fibrillation event can include multiple cardiac cycles, and in some examples, these cardiac cycles occur within a specific time interval (such as a threshold inter - beat timing or rate change or pattern, etc. that occurs within a 2 - minute time window). In an example, an indication of either an atrial fibrillation S4 heart sound or a non - atrial fibrillation S4 heart sound for the S4 signal portion can be determined based on the determined first correlation and second correlation for each of the multiple cardiac cycles.

[0105] In an example, a composite S4 signal portion can be determined using S4 signal portions occurring over multiple cardiac cycles (e.g., combining multiple signal portions into a representative composite signal), and a first correlation between the composite S4 signal portion and a non-atrial fibrillation S4 template and a second correlation between the composite S4 signal portion and an atrial fibrillation S4 heart sound can be determined separately. An indication of either an atrial fibrillation S4 heart sound or a non-atrial fibrillation S4 heart sound can be determined for the composite S4 signal portion based on the determined first and second correlations.

[0106] In an example, an indication of either an atrial fibrillation S4 heart sound or a non-atrial fibrillation S4 heart sound for an S4 heart sound in an S4 signal portion can be determined based on a difference between a correlation of the S4 signal portion with a non-atrial fibrillation S4 template and a correlation of the S4 signal portion with an atrial fibrillation S4 template. In other examples, an indication of either an atrial fibrillation S4 heart sound or a non-atrial fibrillation S4 heart sound for an S4 heart sound in an S4 signal portion can be determined based on a difference of a correlation of the S4 signal portion with an atrial fibrillation S4 template from a correlation of the S4 signal portion with a non-atrial fibrillation S4 template.

[0107] In an example, an indication of either an atrial fibrillation S4 heart sound or a non-atrial fibrillation S4 heart sound for an S4 heart sound in an S4 signal portion can be determined additionally based on one or more heart sound parameters. In an example, the heart sound parameters can include one or more of an S1 value, an S2 value, an S3 value, or an S4 value, such as an amplitude value or an energy value (e.g., an energy value in a heart sound window defined by cardiac signal characteristics, one or more other heart sounds, or a combination thereof over one or more cardiac cycles among other things). In an example, the heart sound parameters can include information regarding one or more cardiac cycles or multiple identical heart sound parameters or different combinations of heart sound parameters over a specified time period (e.g., 1 minute, 1 hour, 1 day, 1 week, etc.). For example, the heart sound parameters can include a composite S1 parameter representative of multiple S1 parameters over a certain time period (e.g., multiple cardiac cycles, a representative time period, etc.).

[0108] In an example, the heart sound parameter can include an ensemble average of a specific heart sound on a heart sound waveform, such as that disclosed in U.S. Patent No. 7,115,096 to Siejko et al., commonly assigned, and titled "THIRD HEART SOUND ACTIVITY INDEX FOR HEART FAILURE MONITORING", or in U.S. Patent No. 7,853,327 to Patangay et al., commonly assigned, and titled "HEART SOUND TRACKING SYSTEM AND METHOD", each of these patents being incorporated herein by reference in its entirety, the disclosure of which includes their ensemble averaging of acoustic signals and determination of specific heart sounds of the heart sound waveform.

[0109] In an example, an operation of a medical device, such as from a low power mode to a high power mode, can be changed based on one or more of: an initial atrial fibrillation detection using cardiac electrical information, a confirmed atrial fibrillation detection using the determined indication of atrial fibrillation S4 heart sound for the S4 signal portion based on the determined first and second correlations, or a combined detection using cardiac electrical information and the determined indication of atrial fibrillation S4 heart sound for the S4 signal portion based on the determined first and second correlations. In some examples, the high power mode can be opposite to the low power mode and can include one or more of: enabling one or more additional sensors, switching from a low power sensor or sensor set to a higher power sensor or sensor set, triggering additional sensing from one or more additional sensors or the medical device, increasing the sensing frequency or sensing or storage resolution, increasing the amount of data to be collected, communicated (e.g., from a first medical device to a second medical device, etc.) or stored, triggering storage of current available information from a loop recorder in a long-term storage device, or increasing the storage capacity or time period of the loop recorder, or otherwise changing the device behavior to capture additional or higher resolution physiological information or perform more processing, etc.

[0110] In contrast, an initial atrial fibrillation detection can be negated using the determined indication of non-atrial fibrillation S4 heart sound (e.g., an S4 signal template under normal sinus rhythm, etc.).

[0111] Additionally or alternatively, event storage may be triggered, such as in response to detected or confirmed atrial fibrillation detection. Information sensed or recorded in a high-power mode may be transferred from a short-term storage device (such as in a loop recorder) to long-term or non-volatile memory, or in some examples, prepared for communication to an external device separate from the medical device. In an example, cardiac electrical or cardiac mechanical information that led to the detected atrial fibrillation event may be stored, and in some examples, includes the cardiac electrical or cardiac mechanical information of the detected atrial fibrillation event, such as to increase the specificity of detection. In an example, multiple loop recorder windows (such as 2-minute windows) may be stored sequentially. In systems without early detection, in order to record this information, a loop recorder with a longer time period would be required, which would require a significant additional cost (such as power, processing resources, component cost, storage capacity, etc.). Storing multiple windows using such early detection prior to a single event can provide a complete event evaluation while saving power and cost compared to a longer loop recorder window. Additionally, early detection may trigger additional parameter calculations or storage at different resolutions or sampling frequencies without overly consuming limited system resources.

[0112] In some examples, one or more alerts may be provided, such as to a patient, doctor, or one or more other caregivers (e.g., using a patient smartwatch, cellular or smartphone, computer, etc.), such as in response to a transition to a high-power mode, in response to a detected event or condition, or after updating information or transferring information from a first device to a remote device. In other examples, the medical device itself may provide an audible or tactile alert to alert the patient of the detected condition. For example, an alert may be issued to the patient in response to the detected condition so that they can perform corrective actions, such as sitting down, etc.

[0113] In some examples, treatment may be provided in response to a detected condition. For example, pacing treatment may be provided, enabled, or adjusted, such as to interrupt or reduce the impact of a detected atrial fibrillation event. In other examples, delivery of one or more drugs (e.g., vasoconstrictors, pressor drugs, etc.) may be triggered, provided, or adjusted (such as using a drug pump), either alone or in combination with pacing treatment (such as the pacing treatment described above), in response to a detected condition, such as to increase arterial pressure, maintain cardiac output, and interrupt or reduce the impact of a detected atrial fibrillation event.

[0114] Figure 9FIG. 0 shows a block diagram of an example machine 900 upon which any one or more of the technologies (such as methods) discussed herein may be executed. Portions of the description may apply to the computing framework of one or more of the medical devices (such as wearable medical devices, external programmers, etc.) described herein. Additionally, as described herein with respect to medical device components, systems, or machines, such components, systems, or machines may be subject to regulatory compliance that cannot be achieved by a general-purpose computer, component, or machine.

[0115] As described herein, an example may include logic or multiple components or mechanisms in, or operable by, machine 900. A circuit system (such as a processing circuit system, an evaluation circuit, etc.) is a collection of circuits implemented in a tangible entity of machine 900 that includes hardware (such as simple circuits, gates, logic, etc.). Circuit system membership can be flexible over time. A circuit system includes members that can perform the specified operations individually or in combination when operated. In an example, the hardware of the circuit system can be immutably designed to perform a particular operation (such as hardwired). In an example, the hardware of the circuit system can include physically components that are variably connected (such as execution units, transistors, simple circuits, etc.), which include computer-readable media that are physically modified (such as magnetically, electrically, movable placement of immutably aggregated particles, etc.) to encode instructions for a particular operation. When connecting the physical components, the underlying electrical properties of the hardware composition change, such as from an insulator to a conductor, or vice versa. The instructions enable the embedded hardware (such as an execution unit or a loading mechanism) to create members of the circuit system in the hardware via the variable connections to perform portions of the particular operation when operated. Thus, in an example, the computer-readable media element is part of the circuit system or communicatively coupled to other components of the circuit system when the device is operated. 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 by a third circuit in a second circuit system at a different time. The following are additional examples with respect to these components of machine 900.

[0116] In an alternative embodiment, machine 900 may operate as a stand-alone device or may be connected (e.g., networked) to other machines. In a networked deployment, machine 900 may operate in a server-client network environment as a server machine, a client machine, or both. In an example, machine 900 may act as a peer machine in a peer-to-peer (P2P) (or other distributed) network environment. Machine 900 may be a personal computer (PC), tablet PC, set-top box (STB), personal digital assistant (PDA), mobile phone, network appliance, network router, switch or bridge, or any machine capable of executing instructions (sequential or otherwise) specifying actions to be taken by that machine. Further, although only a single machine is shown, the term "machine" shall also be taken to include any collection of such machines that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methods discussed herein, such as cloud computing, software as a service (SaaS), other computer cluster configurations.

[0117] Machine 900 (e.g., a computer system) may include a hardware processor 902 (e.g., a central processing unit (CPU), graphics processing unit (GPU), hardware processor core, or any combination thereof), main memory 904, static memory 906 (e.g., a memory or storage device for firmware, microcode, basic input / output (BIOS), Unified Extensible Firmware Interface (UEFI), etc.), and mass storage device 908 (e.g., a hard disk drive, tape drive, flash storage device, or other block device), some or all of which may communicate with each other via an interconnection link 930 (e.g., a bus). Machine 900 may also include a display unit 910, an input device 912 (e.g., a keyboard) and a user interface (UI) navigation device 914 (e.g., a mouse). In an example, the display unit 910, input device 912, and UI navigation device 914 may be a touch screen display. Machine 900 may additionally include a signal generation device 918 (e.g., a speaker), a network interface device 920, and one or more sensors 916, such as a Global Positioning System (GPS) sensor, compass, accelerometer, or one or more other sensors. Machine 900 may include an output controller 928, such as a serial connection (e.g., Universal Serial Bus (USB)), parallel connection, 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., a printer, card reader, etc.).

[0118] The registers of the hardware processor 902, the main memory 904, the static memory 906, or the mass storage device 908 may be or include a machine-readable medium 922 on which one or more sets of data structures or instructions 924 (e.g., software) are stored, which data structures or instructions embody or are utilized by any one or more of the techniques or functions described herein. The instructions 924 may also reside, completely or at least partially, within any one of the registers of the hardware processor 902, the main memory 904, the static memory 906, or the mass storage device 908 during execution thereof by the machine 900. In an example, one or any combination of the hardware processor 902, the main memory 904, the static memory 906, or the mass storage device 908 may constitute a machine-readable medium. Although the machine-readable medium 922 is shown as a single medium, the term "machine-readable medium" may include a single medium or multiple media (e.g., a centralized database or a distributed database, and / or associated caches and servers) configured to store one or more instructions 924.

[0119] The term "machine-readable medium" may include any medium that can store, encode, or carry instructions for execution by the machine 900 and that cause the machine 900 to perform any one or more of the techniques in this disclosure, or that can store, encode, or carry data structures used by or associated with such instructions. Non-limiting examples of machine-readable media 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 having a plurality of particles that have an invariant (e.g., stationary) mass and are thus a composition of matter. Thus, a non-transitory machine-readable medium is a machine-readable medium that does not include transitory propagated signals. 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; magnetic disks such as internal hard disks and removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks.

[0120] Instruction 924 can also be transmitted or received over communication network 926 using a transmission medium via a network interface device 920 that utilizes any one of a variety of transmission protocols such as Frame Relay, Internet Protocol (IP), Transmission Control Protocol (TCP), User Datagram Protocol (UDP), Hypertext Transfer Protocol (HTTP), etc. Example communication networks can include local area networks (LANs), wide area networks (WANs), packet data networks (such as the Internet), mobile telephone networks (such as cellular networks), plain old telephone (POTS) networks, and wireless data networks (such as the Institute of Electrical and Electronics Engineers (IEEE) 802.11 standard series known as and the IEEE 802.16 standard series known as , the IEEE 802.15.4 standard series, peer-to-peer (P2P) networks, etc.). In an example, network interface device 920 can include one or more physical jacks (such as Ethernet jacks, coaxial jacks, or telephone jacks) or one or more antennas for connecting to communication network 926. In an example, network interface device 920 can include multiple antennas for wireless communication using at least one of single-input multiple-output (SIMO), multiple-input multiple-output (MIMO), or multiple-input single-output (MISO) techniques. The term "transmission medium" shall be deemed to include any non-tangible medium that is capable of storing, encoding, or carrying instructions for execution by machine 900, and includes digital or analog communication signals or other non-tangible media to facilitate the communication of such software. A transmission medium is a machine-readable medium.

[0121] Various embodiments are shown in the figures above. One or more features from one or more of these embodiments can be combined to form other embodiments. The method examples described herein can be at least partially machine or computer-implemented. Some examples can include a computer-readable medium or machine-readable medium encoded with instructions that are operable to configure an electronic device or system to perform the methods described in the examples above. Implementations of such methods can include code such as microcode, assembly language code, high-level language code, or the like. Such code can include computer-readable instructions for performing various methods. The code can form part of a computer program product. Additionally, the code can be tangibly stored on one or more volatile or non-volatile computer-readable media during execution or at other times.

[0122] The above detailed description is intended to be illustrative and not restrictive. Accordingly, the scope of the present disclosure should be determined with reference to the appended claims together with the full scope of equivalents to which such claims are entitled under the law.

Claims

1. A medical device system, comprising: A signal receiver circuit configured to receive cardiac acceleration information of a patient; A cardiac acceleration evaluation circuit configured to: Use the received cardiac acceleration information of the patient to determine the time of S4 of the patient; And Determine a P-wave window for the patient based on the determined time of S4; And A cardiac electrical feature detection circuit configured to detect or confirm one or more cardiac electrical features using the determined P-wave window.

2. The medical device system according to claim 1, wherein, The signal receiver circuit is configured to receive the cardiac acceleration information of the patient from an S4 window of one or more cardiac cycles, Wherein, to determine the time of S4, the cardiac acceleration evaluation circuit is configured to: Determine a plurality of correlations between the S4 template and different portions of the cardiac acceleration information in the S4 window, wherein the duration of the S4 window is longer than the duration of the S4 template; Use the peak amplitudes of the determined plurality of correlations to determine the S4 centroid for the one or more cardiac cycles; and Use the determined S4 centroid to determine the time of S4, and Wherein, the cardiac acceleration evaluation circuit is configured to determine a P-wave window for the patient using the determined S4 centroid and electromechanical delay.

3. The medical device system according to claim 2, wherein, The cardiac acceleration information includes heart sound information, and Wherein, the cardiac acceleration evaluation circuit is configured to determine the time of S4 as the time of the peak amplitude of the determined plurality of correlations in the S4 window.

4. The medical device system according to any one of claims 2 to 3, wherein, The cardiac acceleration evaluation circuit is configured to determine a plurality of correlations of the S4 template, each of the plurality of correlations being relative to a different portion of the cardiac acceleration information along the S4 window.

5. The medical device system according to claim 4, wherein, The different portions have different, non-overlapping times along the S4 window.

6. The medical device system according to any one of claims 2 to 5, wherein, The cardiac acceleration evaluation circuit is configured to: use the peak amplitudes of the determined plurality of correlations of the S4 template to detect S4 in the cardiac acceleration information, and Wherein, the S4 template includes a non-atrial fibrillation S4 template.

7. The medical device system according to any one of claims 2 to 6, wherein, The received cardiac acceleration information includes cardiac acceleration information from a late diastolic signal portion in the one or more cardiac cycles, Wherein, the S4 window includes a first S4 window, and the first S4 window includes a first sub-portion of the late diastolic signal portion, Wherein, the cardiac acceleration evaluation circuit is configured to: determine a plurality of correlations between the S4 template and different portions of the cardiac acceleration information in a plurality of S4 windows along the late diastolic signal portion, and Wherein, the cardiac acceleration evaluation circuit is configured to: determine the S4 centroid for the one or more cardiac cycles as the peak amplitudes of the determined plurality of correlations.

8. The medical device system according to any one of claims 2 to 7, wherein, The one or more cardiac cycles include a first cardiac cycle, Wherein, the cardiac acceleration evaluation circuit is configured to: determine the S4 centroid for the first cardiac cycle, and Wherein, the cardiac electrical feature detection circuit is configured to: use the determined S4 centroid for the first cardiac cycle to detect the P-wave in the second cardiac cycle after the first cardiac cycle.

9. The medical device system according to any one of claims 2 to 7, wherein, The cardiac acceleration information of the patient from the S4 window of the one or more cardiac cycles includes ensemble-averaged cardiac acceleration information of multiple cardiac cycles.

10. The medical device system according to any one of claims 1 to 9, wherein, The cardiac electrical feature detection circuit is configured to: detect whether a P-wave event exists in the determined P-wave window of the one or more cardiac cycles.

11. The medical device system according to any one of claims 1 to 9, wherein, The cardiac electrical feature detection circuit is configured to: use the determined P-wave window to determine the confidence level of an atrial fibrillation event in the one or more cardiac cycles.

12. A method, comprising: receiving, using a signal receiver circuit, cardiac acceleration information of a patient; determining, using a cardiac acceleration evaluation circuit, the time of S4 of the patient using the received cardiac acceleration information of the patient; determining, using the cardiac acceleration evaluation circuit, a P-wave window for the patient based on the determined time of S4; and detecting or confirming one or more cardiac electrical features using the determined P-wave window by a cardiac electrical feature detection circuit.

13. The method according to claim 12, wherein, Receiving the cardiac acceleration information of the patient includes receiving cardiac acceleration information from the S4 window of one or more cardiac cycles of the patient, wherein determining the time of S4 includes: determining a plurality of correlations of the S4 template with different portions of the cardiac acceleration information in the S4 window, wherein the duration of the S4 window is longer than the duration of the S4 template; using the peak amplitudes of the determined plurality of correlations to determine the S4 centroid for the one or more cardiac cycles; and using the determined S4 centroid to determine the time of S4, and wherein determining the P-wave window for the patient includes using the determined S4 centroid and electromechanical delay.

14. The method according to claim 13, wherein, The cardiac acceleration information includes heart sound information, and wherein determining the time of S4 includes determining the time of the peak amplitudes of the determined plurality of correlations in the S4 window.

15. The method according to any one of claims 13 to 14, wherein The cardiac acceleration evaluation circuit is configured to determine a plurality of correlations of the S4 template, each of the plurality of correlations being relative to a different portion of the cardiac acceleration information along the S4 window, and wherein the different portions have different, non-overlapping times along the S4 window.

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