阅读说明：本技术 用于确定心房颤动和脉压变异性的系统和方法 (System and method for determining atrial fibrillation and pulse pressure variability ) 是由 巴伦·马斯卡巴 普拉莫德辛格·希拉辛格·塔库尔 安琪 戴维·J·特恩斯 斯蒂芬·B·鲁布尔 于 2018-05-14 设计创作，主要内容包括：本文档除其他事项外论述了用于接收患者的生理信息、从患者接收不同于接收到的生理信息的脉压信息以及使用接收到的生理信息和接收到的脉压信息来确定心房颤动(AF)的指示的系统和方法。(This document discusses, among other things, systems and methods for receiving physiological information of a patient, receiving pulse pressure information from the patient different from the received physiological information, and determining an indication of Atrial Fibrillation (AF) using the received physiological information and the received pulse pressure information.)

1. A system, comprising:

means for detecting physiological information from a patient;

means for detecting pulse pressure information from a patient; and

a first Ambulatory Medical Device (AMD) configured to determine an AF indication using detected physiological information and detected pulse pressure information.

2. The system of claim 1, wherein the means for detecting physiological information from the patient comprises a first Ambulatory Medical Device (AMD) configured to detect physiological information from the patient,

wherein the means for detecting pulse pressure information from the patient comprises a second AMD, different from the first AMD, configured to detect pulse pressure information from the patient, and

wherein the first AMD is configured to receive pulse pressure information from the second AMD.

3. The system of claim 2, wherein the first AMD comprises an Implantable Cardiac Monitor (ICM) configured to detect physiological information from a patient,

wherein the second AMD comprises a wearable medical device configured to detect pulse pressure information from the patient.

4. The system of claim 3, wherein the second AMD comprises at least one of:

an optical sensor;

a pressure sensor;

a sound sensor;

an impedance sensor;

a vibration sensor; or

A strain sensor.

5. The system of claim 3, wherein the wearable medical device comprises at least one of a wrist-worn medical device or a finger-worn medical device configured to detect a photoplethysmogram (PPG) signal from the patient.

6. The system according to any of claims 3-5, wherein the ICM is configured to use detected physiological information to determine the AF indication and to use received pulse pressure information to enhance the determined AF indication.

7. The system of claim 6, wherein the ICM is configured to confirm or deny the determined AF indication using received pulse pressure information from the wearable medical device.

8. The system of any of claims 3 to 7, wherein the first AMD comprises AF circuitry configured to determine an AF indication using detected physiological information and to enhance AF determination using received pulse pressure information.

9. The system of any of claims 3 to 8, wherein the ICM is configured to detect at least one of Electrocardiogram (ECG) information or Heart Sound (HS) information from the patient and determine an AF indication using the detected ECG information, the detected HS information, or the detected ECG and HS information.

10. A medical device, comprising:

an Atrial Fibrillation (AF) circuit configured to receive physiological information from a patient; and

a signal receiver circuit configured to receive pulse pressure information from a patient, the received pulse pressure information being different from the received physiological information,

wherein the AF circuit is configured to determine an AF indication using the received physiological information and the received pulse pressure information.

11. The medical apparatus of claim 10, wherein the AF circuit is configured to determine an AF indication using the received physiological information and to enhance the determined AF indication using the received pulse pressure information.

12. The medical apparatus of claim 11, wherein the AF circuitry is configured to confirm or deny the determined AF indication using the received pulse pressure information.

13. The medical apparatus of any one of claims 9-12, wherein the AF circuitry is configured to use the received pulse pressure information to enhance the AF determination.

14. The medical apparatus of claim 13, wherein the AF circuit is configured to determine the AF indication using the received physiological information and a threshold value,

wherein the AF circuit is configured to adjust the threshold using the received pulse pressure information.

15. The medical device of any one of claims 9-14, comprising:

an Implantable Cardiac Monitor (ICM) configured to detect physiological information from a patient, an

A wearable medical device configured to detect pulse pressure information from a patient,

wherein the ICM includes an AF circuit, and

wherein the wearable medical device comprises a signal receiver circuit.

Technical Field

This document relates generally to medical devices and, more particularly, but not by way of limitation, to systems, devices and methods for pulse pressure variability assessment.

Background

Atrial Fibrillation (AF) can be described as an abnormal heart rhythm characterized by rapid and irregular activity in the upper chamber, left atrium, and right atrium of the heart, affecting over 2500 million people in europe and north america alone. AF is often associated with reduced cardiac output, increased risk of Heart Failure (HF), dementia, and stroke. Risk factors for AF include hypertension, Heart Failure (HF), valvular heart disease, COPD, obesity, and sleep apnea, among others.

Disclosure of Invention

This document discusses, among other things, the following systems and methods: for receiving physiological information of a patient, receiving pulse pressure information from the patient different from the received physiological information, and determining an indication of Atrial Fibrillation (AF) using the received physiological information and the received pulse pressure information.

An example (e.g., "example 1") of a subject (e.g., a system) may include a first Ambulatory Medical Device (AMD) configured to detect physiological information from a patient, and a second AMD, distinct from the first AMD, configured to detect pulse pressure information from the patient, wherein the first AMD is configured to receive the pulse pressure information from the second AMD, and to determine an AF indication using the detected physiological information and the detected pulse pressure information. The second AMD can optionally include at least one of: an optical sensor; a pressure sensor; a sound sensor; an impedance sensor; a vibration sensor; or a strain sensor.

In example 2, the subject matter of example 1 can optionally be configured such that: the first AMD includes an Implantable Cardiac Monitor (ICM) configured to detect physiological information from a patient, and the second AMD includes a wearable medical device configured to detect pulse pressure information from the patient.

In example 3, the subject matter of any one or more of examples 1-2 can optionally be configured such that the wearable medical device comprises at least one of a wrist-worn medical device or a finger-worn medical device configured to detect a photoplethysmogram (PPG) signal from the patient.

In example 4, the subject matter of any one or more of examples 1-3 may optionally be configured such that the ICM is configured to determine an AF indication using the detected physiological information and to enhance the determined AF indication pulse pressure information using the received pulse pressure information.

In example 5, the subject matter of one or more of examples 1-4 may optionally be configured such that the ICM is configured to confirm or deny the determined AF indication using pulse pressure information received from the wearable medical device.

In example 6, the subject matter of any one or more of examples 1-5 may optionally be configured such that the first AMD includes AF circuitry configured to determine an AF indication using the detected physiological information and to enhance AF determination using the received pulse pressure information.

In example 7, the subject matter of any one or more of examples 1-6 can optionally be configured such that the ICM is configured to detect at least one of Electrocardiogram (ECG) information or Heart Sound (HS) information from the patient and determine the AF indication using the detected ECG information, the detected HS information, or the detected ECG and HS information.

An example (e.g., "example 8") of a subject (e.g., a medical device) may include an Atrial Fibrillation (AF) circuit configured to receive physiological information from a patient and a signal receiver circuit configured to receive pulse pressure information from the patient, the received pulse pressure information being different than the received physiological information, wherein the AF circuit is configured to determine an AF indication using the received physiological information and the received pulse pressure information.

In example 9, the subject matter of example 8 can optionally be configured such that: the AF circuit is configured to determine an AF indication using the received physiological information and to enhance the determined AF indication using the received pulse pressure information.

In example 10, the subject matter of any one or more of examples 8-9 can optionally be configured such that the AF circuitry is configured to confirm or deny the determined AF indication using the received pulse pressure information.

In example 11, any one or more of the subject matter of examples 8-10 can optionally be configured such that the AF circuitry is configured to use the received pulse pressure information to enhance AF determination.

In example 12, the subject matter of any one or more of examples 8-11 can optionally be configured such that the AF circuit is configured to determine the AF indication using the received physiological information and a threshold, wherein the AF circuit is configured to adjust the threshold using the received pulse pressure information.

Examples (e.g., "example 13") of a subject (e.g., a method) may include: receiving physiological information from a patient using an Atrial Fibrillation (AF) circuit; receiving pulse pressure information from the patient using a signal receiver circuit, the received pulse pressure information being different from the received physiological information; and determining, using an AF circuit, an AF indication using the received physiological information and the received pulse pressure information.

In example 14, the subject matter of example 13 can optionally be configured to include: detecting physiological information from a patient using a first Ambulatory Medical Device (AMD); and detecting pulse pressure information from the patient using a second AMD different from the first AMD.

In example 15, the subject matter of any one or more of examples 13-14 may optionally be configured such that the first AMD comprises an Implantable Cardiac Monitor (ICM) and the second AMD comprises a wearable medical device.

In example 16, the subject matter of any one or more of examples 13-15 may optionally be configured such that the wearable medical device comprises at least one of a wrist-worn medical device or a finger-worn medical device, and detecting the pulse pressure information comprises detecting a photoplethysmogram (PPG) signal from the patient using the wearable medical device.

In example 17, the subject matter of any one or more of examples 13-16 may optionally be configured such that detecting the physiological information comprises detecting at least one of Electrocardiogram (ECG) information or Heart Sound (HS) information from the patient using ICM, and determining the AF indication using the received physiological information comprises using the detected ECG information, the detected HS information, or the detected ECG and HS information.

In example 18, the subject matter of any one or more of examples 13-17 may optionally be configured such that determining the AF indication using the received physiological information and the received pulse pressure information comprises: the AF indication is determined using the received physiological information and the initial AF indication is enhanced using the received pulse pressure information.

In example 19, the subject matter of any one or more of examples 13-18 may optionally be configured such that enhancing the AF indication comprises confirming or denying the determined AF indication using the received pulse pressure information.

In example 20, the subject matter of any one or more of examples 13-19 may optionally be configured such that determining the AF indication using the received physiological information and the received pulse pressure information comprises: determining an AF indication using the received physiological information and enhancing the determined AF indication using the received pulse pressure information.

An example (e.g., "example 21") of subject matter (e.g., a system or apparatus) may optionally combine any portion of any one or more of examples 1-20, or any combination of portions, to include "means for" performing any portion of any one or more of the functions or methods of examples 1-20, or a "non-transitory machine-readable medium" including instructions that, when executed by a machine, cause the machine to perform any portion of any one or more of the functions or methods of examples 1-20.

This summary is intended to provide an overview of the subject matter of the present patent application. It is not intended to provide an exclusive or exhaustive explanation of the disclosure. Including the detailed description to provide more information about the present patent application. Other aspects of the disclosure will become apparent to those skilled in the art upon reading and understanding the following detailed description and viewing the drawings that form a part hereof, and each of the drawings is not to be taken in a limiting sense.

Drawings

In the drawings, which are not necessarily drawn to scale, like numerals may describe similar components in different views. Like numerals having different letter suffixes may represent different instances of similar components. The drawings illustrate generally, by way of example, and not by way of limitation, various embodiments discussed in this document.

Figure 1 illustrates an example patient management system.

Fig. 2-3 illustrate an example method of detecting Atrial Fibrillation (AF) in a patient.

FIG. 4 illustrates a block diagram of an example machine with which any one or more of the techniques discussed herein may be executed.

Detailed Description

The inventors of the present invention have recognized, among other things, the use of pulse pressure information from a patient to detect Atrial Fibrillation (AF). In one example, an Ambulatory Medical Device (AMD) may sense a pulsatile signal, such as a photoplethysmogram (PPG) or other pulsatile signal indicative of a change in blood volume of a patient, and the AMD or one or more other AMDs or external devices may use information from the sensed pulsatile signal to detect AF, or to alter or enhance AF detection.

In an example, the AMD can include a wearable, wrist-worn, or finger-worn medical device configured to detect PPG signals of the patient. The AMD or a device coupled with the AMD (e.g., one or more other AMDs such as an Implantable Cardiac Monitor (ICM), another AMD or external or wearable medical device, or an external medical device programmer or one or more other external devices configured to communicate with the ICM or other AMD using bluetooth or one or more other communication protocols, etc.) may use information from the AMD, such as information about the detected PPG signal, to determine the pulse pressure signal. Pulse pressure information, such as Pulse Pressure Variability (PPV) information, may be used to detect AF in a patient, alter or enhance AF detection in an ICM or one or more other AMDs or external devices, or alter or enhance information detected by an ICM or one or more other AMDs or external devices used to determine AF.

For example, when the ICM detects AF, information from the AMD (e.g., wrist or finger worn or other external medical device) may be used to confirm (confirm)/deny (deny) the original AF detection using pulse pressure information (e.g., PPG signal variability). If the ICM determines an indication of AF, and the pulse pressure information from the AMD also indicates AF, the determination of the ICM may be confirmed. If the ICM determines an indication of AF and the pulse pressure information from the AMD does not indicate AF, the determination of the ICM may be denied. Over time, the prevalence of confirmations or repudiations of AF detection by ICM (or AF detection using ICM information) may be used to refine AF detection in a particular patient or target population. In an example, a higher negative acknowledgement occurrence rate may be used to increase an AF detection threshold in or using ICM information, e.g., to improve detection specificity. Conversely, a higher incidence of acknowledgements may be used to lower the AF detection threshold in ICM or using ICM information, for example, to increase detection sensitivity.

In other examples, an AMD (e.g., a wrist-worn medical device) may be configured to receive patient assessment information (e.g., an AF symptom assessment), such as in response to a query for the AMD, and the received assessment information (e.g., "I can tell that an event is occurring, but can also"; "I is bad"; "the event is worsening"; etc.) may be used to enhance AF detection, for example, by enhancing an algorithm in the ICM or one or more other AMDs or external devices for detecting AF, or by enhancing information detected by the ICM or one or more other AMDs or external devices for determining or classifying AF. In one example, one or more AF features such as frequency, stability, duration, pulse pressure information, etc. may be used to classify AF. The received patient assessment information may be correlated or otherwise correlated with patient physiological information to improve or enhance patient-specific or population-based AF detection, treatment, or intervention.

The inventors of the present invention have recognized that pulse pressure may be used to detect R-waves, or R-wave detection (e.g., in ICM or other AMD, or using ICM or AMD information) may be improved, among other things. For example, ICM or AMD R-wave detection may be checked for beat detection using pulse pressure information (e.g., PPG signals) to confirm R-wave detection accuracy or to adjust one or more detection thresholds in ICM or AMD.

In some examples, the pulse pressure information may include information or changes regarding one or more of: pulse pressure or peak pulse pressure amplitude or variability; regions of pulse pressure or pulse pressure variability signals (e.g., relative to the mean of multiple beats, rolling the floor, etc.); timing between pulse pressure or a pulse pressure variability reference and one or more other references (e.g., an electrical, mechanical, or secondary pulse pressure reference, etc.); or the slope or other signal characteristic of the pulse pressure or peak pulse pressure amplitude or variability, or the correlation of a pulse pressure signal characteristic with one or more other physiological signal characteristics or references; and so on.

Fig. 1 illustrates an example patient management system 100 and a portion of an environment in which the system 100 may operate. The patient management system 100 may perform a series of activities including remote patient monitoring and diagnosis of disease conditions. Such activities may be performed near the patient 102, such as at the patient's home or office, through a centralized server, such as at a hospital, clinic, or physician's office, or through a remote workstation, such as a secure wireless mobile computing device.

The patient management system 100 can include a mobile system 105, an external system 125, and a communication link 115, the communication link 115 being used to communicate between the mobile system 105 and the external system 125.

Ambulatory system 105 may include an Implantable Medical Device (IMD)110, a wearable medical device 111, or one or more other implantable, leadless, subcutaneous, external, or wearable medical devices configured to monitor, sense, or detect information or provide one or more therapies to treat various heart conditions related to the heart's ability to adequately deliver blood to the body, such as Atrial Fibrillation (AF), Congestive Heart Failure (CHF), or one or more other heart conditions.

In an example, the IMD 110 may include one or more conventional Cardiac Rhythm Management (CRM) devices such as pacemakers, defibrillators, or cardiac monitors implanted in the chest of a patient and having a lead system 108 including one or more transvenous, subcutaneous, or non-invasive leads or catheters to position one or more electrodes or other sensors in, above, or around the heart, or one or more other locations in the chest, abdomen, or neck of the patient 102.

The IMD 110 may include a detector circuit 160, the detector circuit 160 configured to detect events or process physiological information received from the patient 102. In one example, the medical event includes a particular arrhythmia. Examples of cardiac arrhythmias may include atrial or ventricular bradycardias or tachycardias such as Atrial Fibrillation (AF), atrial flutter, atrial tachycardia, supraventricular tachycardia, ventricular tachycardia or ventricular fibrillation, and the like. In one example, arrhythmia detection circuit 160 is configured to detect a worsening of a chronic medical condition, such as Heart Failure (HF). In another example, the medical event may include a patient-triggered event.

The IMD 110 may alternatively be configured as a therapy device configured to treat cardiac arrhythmias or other cardiac disorders. The IMD 110 may additionally include a therapy unit that may generate and deliver one or more therapies. Therapy may be delivered to the patient 102 via the lead system 108 and associated electrodes, or using one or more other delivery mechanisms. The treatment may include an antiarrhythmic treatment to treat the arrhythmia or to treat or control one or more complications resulting from the arrhythmia, such as syncope, Congestive Heart Failure (CHF), or stroke, among others. Examples of anti-arrhythmic therapies include pacing, cardioversion, defibrillation, neuromodulation, drug therapy or biologic therapy, among other types of therapy. In other examples, the therapy may include Cardiac Resynchronization Therapy (CRT) to correct dyssynchrony and improve cardiac function in CHF patients. In some examples, the IMD 110 may include a drug delivery system, such as a drug infusion pump, to deliver drugs to a patient to address an arrhythmia or a complication due to an arrhythmia.

In other examples, the dynamic system 105 may include one or more Leadless Cardiac Pacemakers (LCPs) or other small (e.g., smaller than a conventional implantable CRM device) self-contained devices configured to detect physiological information therefrom or provide one or more therapies or stimuli to the heart without conventional leads or implantable CRM device complications (e.g., required incisions and pockets, complications related to lead placement, breakage, or migration, etc.). LCP can have more limited capabilities and processing power than traditional CRM devices; however, multiple LCP devices may be implanted in or around the heart to detect physiological information from one or more chambers of the heart, or to provide one or more treatments or stimuli to one or more chambers of the heart. Multiple LCP devices may communicate between them, or between one or more other implanted or external devices.

The wearable medical device 111 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 smart watch, a smart accessory, a wrist-worn or finger-worn medical device, etc.) configured to detect or monitor physiological information of a patient without the need for implantation or hospitalization procedures for placement, battery replacement, or repair. In an example, wearable medical device 111 may include an optical sensor configured to detect a photoplethysmogram (PPG) signal on a wrist, finger, or other location of a patient, the PPG signal including pressure changes from which pulse pressure information may be detected. In other examples, wearable medical device 111 may include any device configured to detect pulsatile pressure changes in a patient, including an acoustic sensor or accelerometer to detect sound or vibrations of blood flow, an impedance sensor to detect impedance changes associated with blood flow or changes in blood volume, a temperature sensor to detect temperature changes associated with blood flow, a laser doppler vibrometer or other pressure, strain or physical sensor to detect physical changes associated with blood flow, or the like. Wearable medical device 111 may be located on or around an artery, vein, or one or more other anatomical locations where blood flow information may be detected. In other examples, pulse pressure information may be detected using one or more implantable or other ambulatory medical devices.

Patient management system 100 may include, among other things, a respiration sensor configured to receive respiration information (e.g., Respiration Rate (RR), respiration volume (tidal volume), etc.), a heart sound sensor configured to receive heart sound information, a thoracic impedance sensor configured to receive impedance information, a heart sensor configured to receive cardiac electrical information, and an activity sensor configured to receive information about body motion (e.g., activity, posture, etc.), or one or more other sensors configured to receive physiological information of patient 102.

The external system 125 may comprise a dedicated hardware/software system, such as a programmer, a remote server-based patient management system, or alternatively a system defined predominantly by software running on a standard personal computer. The external system 125 may manage the patient 102 through the IMD 110 connected to the external system 125 via the communication link 115. In other examples, the IMD 110 may be connected to the wearable device 111, or the wearable device 111 may be connected to the external system 125 via the communication link 115. This may include, for example, programming the IMD 110 to perform one or more of the following: acquiring physiological data, performing at least one self-diagnostic test (e.g., for device operating status), analyzing the physiological data to detect arrhythmias, or alternatively delivering therapy or adjusting therapy to the patient 102. Further, the external system 125 may send information to or receive information 115 from the IMD 110 or wearable device 111 via a communication link. Examples of information may include real-time or stored physiological data from the patient 102, diagnostic data, events such as detection of cardiac arrhythmias or worsening heart failure, responses to therapy delivered to the patient 102, or device operating states (e.g., battery status, lead impedance, etc.) of the IMD 110 or wearable device 111. The communication link 115 may be an inductive telemetry link, a capacitive telemetry link, or a Radio Frequency (RF) telemetry link, or wireless telemetry based on, for example, "strong" bluetooth or IEEE 802.11 wireless fidelity "Wi-Fi" interface standards. Other configurations and combinations of patient data source interfacing are possible.

By way of example and not limitation, the external system 125 may include an external device 120 in proximity to the IMD 110, and a remote device 124 at a location relatively remote from the IMD 110 that communicates with the external device 120 via the telecommunications network 122. An example of the external device 120 may include a medical device programmer.

The remote device 124 may be configured to evaluate the collected patient information and provide alert notifications, among other possible functions. In one example, the remote device 124 may include a centralized server that acts as a central hub for the storage and analysis of collected patient data. The server may be configured as a single computing and processing system, a multiple computing and processing system, or a distributed computing and processing system. The remote device 124 may receive patient data from a plurality of patients including, for example, the patient 102. Patient data may be collected by the IMD 110 and other data acquisition sensors or devices associated with the patient 102. The server may include a memory device to store patient data in a patient database. The server may include an alarm analyzer circuit to evaluate the collected patient data to determine whether a particular alarm condition is satisfied. Satisfaction of the alarm condition may trigger generation of an alarm notification. In some examples, the alert condition may alternatively or additionally be evaluated by the IMD 110. By way of example, the alert notification may include a web page update, a telephone or pager call, an email, an SMS, a text or "instant" message, as well as a message to the patient and a simultaneous direct notification to emergency services and clinicians. Other alert notifications are also possible. The server may include alarm prioritization circuitry configured to prioritize alarm notifications. For example, the alarms of the detected medical event may be prioritized using a similarity metric between the physiological data associated with the detected medical event and the physiological data associated with the historical alarms.

Remote device 124 may additionally include one or more locally configured clients or remote clients securely connected to the server over network 122. Examples of clients may include personal desktops, notebook computers, mobile devices, or other computing devices. A system user (e.g., a clinician or other qualified medical professional) may use the client to securely access stored patient data compiled in a database in the server and select and prioritize patients and alarms for healthcare settings. Example systems are described in the commonly assigned U.S. application Ser. No. 11/121,593 "System and Method for Managing the associated Patient data in an Automated Patient Management System" filed on 3.5.2005 and in the commonly assigned U.S. application Ser. No. 11/121,594 "System and Method for Managing the Patient data in an Automated Patient Management System" filed on 3.5.2005, the entire contents of which are incorporated herein by reference. In addition to generating the alert notification, the remote device 124, including the server and interconnected clients, may also execute the tracking protocol by sending a tracking request to the IMD 110, or sending a message or other communication to the patient 102, clinician, or authorized third party as a compliance notification.

The network 122 may provide wired or wireless interconnection. In an example, the network 122 may be based on a transmission control protocol/internet protocol (TCP/IP) network communication specification, although other types or combinations of network implementations are possible. Similarly, other network topologies and arrangements are possible.

One or more of the external device 120 or the remote device 124 may output the detected medical event to a system user, such as a patient or clinician, or to a process including an instance of a computer program executable, for example, in a microprocessor. In one example, the process may include automatic generation of recommendations for anti-arrhythmic therapy, or for further diagnostic tests or therapy. In an example, the external device 120 or the remote device 124 may include a respective display unit for displaying physiological or functional signals, or an alarm, alert, emergency call, or other form of alert to signal detection of an arrhythmia. In some examples, the external system 125 may include an external data processor configured to analyze physiological or functional signals received by the IMD 110 and confirm or deny detection of an arrhythmia. A computationally intensive algorithm, such as a machine learning algorithm, may be implemented in the external data processor to retrospectively process the data to detect cardiac arrhythmias.

Portions of the IMD 110 or external system 125 may be implemented using hardware, software, firmware, or a combination thereof. Portions of the IMD 110 or the external system 125 may be implemented using dedicated circuitry that may be constructed or configured to perform one or more functions, or may be implemented using general-purpose circuitry that may be programmed or otherwise configured to perform one or more functions. Such general purpose circuitry may include a microprocessor or portion thereof, a microcontroller or portion thereof, or programmable logic circuitry, memory circuitry, a network interface, and various components for interconnecting these components. For example, a "comparator" may include, among other things, an electronic circuit comparator that may be configured to perform a particular function of a comparison between two signals, or the comparator may be implemented as part of a general purpose circuit that may be driven by a code that instructs a portion of the general purpose circuit to make a comparison between two signals.

In an example, the patient management system 100 may include a wrist-worn or finger-worn medical device instead of an implantable loop recorder or a Holter device or a patch device. When the body is ill-fitting, the patient 102 may be instructed to prompt, wear, or wear a wrist-worn or finger-worn medical device, rather than always carrying or wearing a Holter device or other patch device. The wrist-worn or finger-worn medical device may communicate with an external system 125 or an external device 120 (e.g., a mobile device) to send or receive patient input or information, receive information about or confirm patient status or patient symptoms, and the like.

Arterial pulse pressure has a significantly linear relationship with the preceding diastolic interval. A longer diastolic interval may indicate increased ventricular filling. Increased ventricular filling may provide for stronger contraction (e.g., Starling mechanism). The stronger contraction may provide greater stroke output. A larger stroke output may provide a larger arterial pulse pressure swing (swing). Thus, a high Heart Rate (HR) in AF may be associated with a lower arterial pulse pressure swing (e.g., reduced pulse pressure variability).

During certain Atrial Fibrillation (AF) treatments, such as Atrial Tachycardia Response (ATR) mode, a high heart rate may adversely affect filling time. As the HR increases, the time period between the Heart Sound (HS) (e.g., the first heart sound (S1), the second heart sound (S2), the third heart sound (S3), the fourth heart sound (S4), etc.) and the next R-wave may become disproportionately small with respect to the HR. In an example, as the heart rate increases, the time period (S2-R) between the second heart sound (S2) of the first cardiac cycle and the R-wave of the traveling cardiac cycle decreases disproportionately with respect to the heart rate, thereby negatively affecting filling. Thus, the present inventors have recognized, among other things, the need to closely monitor the impact on programming changes in response to AF. Further, measurements or characteristics of one or more Heart Sounds (HS) (e.g., S1, S2, S3, S4, etc.) may be used to detect AF, including HS amplitude, variability, timing (e.g., S4 timing, etc.), changes in HS amplitude or variability, or timing between two or more separate HS references or one HS reference and one or more other electrical signal characteristics or other signal characteristics (e.g., diastolic interval, etc.).

The pulse pressure information may be used to detect AF, enhance AF detection, or confirm/deny AF detection. Arterial pulsation during exercise may be similar or increased due to sustained diastolic filling and increased cardiac output. Arterial filling times during higher heart rates (e.g., higher epinephrine states) driven by the Sinoatrial (SA) are longer than in higher heart rates driven by AF. Thus, changes in pulse pressure information regarding changes in HR may be used to detect AF, or to enhance or confirm/deny AF.

In an example, the N beats may be classified based on HR. The peak-to-peak pressure change in a certain number or percentage of the first N/N beats (e.g., having a high HR) can be compared to the peak-to-peak pressure change in a certain number or percentage of the last N/N beats (e.g., having a low HR). In one example, AF may be detected or confirmed if the peak-to-peak pressure change in the first N/N beats is less than the peak-to-peak pressure change in the last N/N beats. Otherwise, motion may be detected or confirmed.

In other examples, beat-to-beat variability in arterial pulse pressure swing may be measured, and AF may be detected or confirmed if the beat-to-beat variability exceeds a threshold. In some examples, pulse pressure variability itself may be used to detect AF. In one example, pulse pressure variability may be used as a secondary screen after detecting a sharp HR or R-R variability change as the primary detection. The burden of measuring a high resolution primary signal may be alleviated for the use of primary and secondary screening measures or multiple sensor inputs in a single detection algorithm, for example if the primary measurement requires a large amount of energy or resources.

In one example, an HR (e.g., an increase in HR) or a Variability (e.g., a decrease in RR Variability) may be indicative of AF, such as "the atomic fiber Detection Using ventrial Rate Variability" described in commonly assigned U.S. patent application No. 14/825,669 filed on 13/8/2015, the entire disclosure of which is incorporated herein by reference. In one example, pulse pressure information may be used in conjunction with one or more other physiological metrics such as HR, R-R variability, HS, and the like to determine AF.

In one example, impedance measurements of the carotid artery or neck, such as those detected using cuff electrodes (cuff electrodes), may be used as a surrogate for arterial pressure. An Autonomous Modulation Therapy (AMT) system may be configured to detect or confirm AF using changes in arterial pressure to titrate HF therapy in the presence of AF. Neural therapy, or one or more other cardiac or drug therapies, may be tailored to target AF. For example, pulse pressure variability may be used to control mode switching between a first therapy mode (e.g., a chronic HF therapy mode) and an acute AF abrogation mode. Patients with high prevalence of chronic AF can be detected and arterial pressure information can be used to adjust AMT therapy.

In one example, implantable or external electrodes may be used to detect impedance changes on or around a blood vessel or artery (e.g., the descending aortic arch). Impedance changes, including Stroke Volume (SV), Cardiac Output (CO), or pulse pressure information using detected impedance changes, may indicate changes in the patient's blood volume.

In other examples, the detected pressure pulsations may reflect irregularities in the Right Ventricular (RV) output during AF. Thus, in patients with a unique Pulmonary Artery (PA) pressure sensor, AF can be detected using the detected pressure pulsations. Pulse pressure changes can be used for differential treatment strategies for patients with or without AF-guided HF. For example, the treatment may be adjusted to minimize pulse pressure variations within the treatment control range.

FIG. 2 shows an example method 200 of detecting Atrial Fibrillation (AF) in a patient. At 202, physiological information can be detected. At 204, pulse pressure information may be detected. In one example, the physiological information may be different from the pulse pressure information. Physiological information may be detected using a first Ambulatory Medical Device (AMD), and pulse pressure information may be detected using a second AMD that is different or separate from the first AMD. In one example, the first AMD can include an Implantable Cardiac Monitor (ICM) configured to be implanted within a patient. In other examples, the first AMD may include one or more other implanted or external medical devices configured for long-term patient monitoring. In an example, the second AMD may include a wearable medical device separate from the first AMD. The second AMD can include a wrist-worn or finger-worn medical device configured to sense or detect pulse pressure information from the patient, such as from a photoplethysmogram (PPG) signal from the wrist or finger of the patient.

At 206, an indication of AF may be determined using the detected physiological information and the detected pulse pressure information. In one example, an indication of AF may be determined using a comparison of one or more signal characteristics (e.g., short term average, etc.) or features to a threshold. In an example, the threshold may include a patient-specific baseline (e.g., a long-term average, etc.), a population baseline, a patient-specific or population-based template, or one or more other thresholds. In one example, the detected physiological information and a combination of the detected pulse pressure information and a threshold value may be used to determine an indication of AF. In other examples, the detected physiological information and a threshold may be used to determine an indication of AF, and the pulse pressure information may be used to enhance (e.g., confirm or deny) the determined indication. In one example, the enhancement may include adjusting physiological information used to determine an indication of AF, adjusting a threshold, or otherwise using detected pulse pressure information to adjust or change the determined indication of AF.

If AF is not determined at 206, process flow may return to 202. If AF is determined at 206, AF therapy can be provided to the patient at 208, such as using one or more leads or electrodes of an implantable medical device, and so forth. In other examples, an alert or notification of AF may be provided to a user, a machine or automated process, or a clinician or other caregiver, etc.

FIG. 3 shows an example method 300 of detecting Atrial Fibrillation (AF) in a patient. At 302, physiological information may be received from a patient, for example, at one or more mobile, external, or telemedicine devices or systems.

At 304, an indication of Atrial Fibrillation (AF) may be determined, such as by comparing one or more characteristics, metrics, or features of the received physiological information to a threshold, e.g., using AF circuitry in one or more mobile, external, or telemedicine devices or systems. If AF is not determined at 304, process flow may return to 302. If AF is determined at 304, pulse pressure information may be received from the patient at 306.

In one example, collection of pulse pressure information from the patient may be prompted by a machine or automated process, such as notifying the user to begin using a wrist-worn or hand-worn medical device to detect pulse pressure information after AF is detected using received physiological information. In other examples, the patient may be instructed to begin detecting pulse pressure information upon paresthesia. In such a case where the user prompts for AF detection, the pulse pressure information may use the received physiological information to trigger a higher resolution AF determination. The user may begin detecting pulse pressure information or prompt for AF determination by simply waking up or turning on a wearable device configured to detect pulse pressure information using one or more inputs.

At 308, the received pulse pressure information may be used to enhance an initial determination of AF, such as using received physiological information. In one example, the received pulse pressure information may be used to confirm or deny an initial determination of AF, or otherwise alter AF detection. If AF is not determined at 308, process flow may return to 302. If AF is determined at 308, one or more AF treatments or patient alerts or interventions may be provided.

Fig. 4 illustrates a block diagram of an example machine 400, where any one or more of the techniques (e.g., methods) discussed herein may be performed. Certain portions of this description may apply to the computing framework of one or more medical devices described herein, such as IMDs, external programmers, and the like.

As described herein, examples may include or be operated by logic or multiple components or mechanisms in the machine 400. A circuit (e.g., processing circuit) is a collection of circuits implemented in a tangible entity of machine 400 that includes hardware (e.g., simple circuits, gates, logic, etc.). The circuit members may be flexible over time. Circuits include members that can perform specified operations in isolation or in combination at the time of operation. In one example, the hardware of the circuit may be designed unchanged to perform certain operations (e.g., hardwired). In one example, the hardware of the circuit may include variably connected physical components (e.g., execution units, transistors, simple circuits, etc.), including a machine-readable medium that is physically modified (e.g., magnetically, electrically, and movably placement of a constant mass of particles, etc.) to encode instructions for a particular operation. When physical components are connected, the underlying electrical properties of the hardware components may change, for example, from an insulator to a conductor, and vice versa. The instructions enable embedded hardware (e.g., an execution unit or a loading mechanism) to create members of a circuit in the hardware through a variable connection to perform portions of a particular operation when operating. Thus, in an example, a machine-readable medium element is part of a circuit, or is communicatively coupled to other components of a circuit when the apparatus operates. In an example, any physical component may be used in more than one member of more than one circuit. For example, under operation, an execution unit may be used in a first circuit of a first circuitry (circuit) at one point in time and may be reused by a second circuit in the first circuitry or a third circuit in the second circuitry at a different time. Additional examples of these components relative to the machine 400 are as follows.

In alternative embodiments, the machine 400 may operate as a standalone device or may be connected (e.g., networked) to other machines. In a networked deployment, the machine 400 may operate in the capacity of a server machine, a client machine, or both, in server-client network environments. In one example, the machine 400 may operate in a peer-to-peer (P2P) (or other distributed) network environment as a peer machine. The machine 400 may be a Personal Computer (PC), a tablet PC, a set-top box (STB), a Personal Digital Assistant (PDA), a cellular telephone, a web appliance, a network router, switch or bridge, or any machine capable of executing instructions (sequential or otherwise) that specify operations to be performed by that machine. Further, while only a single machine is illustrated, the term "machine" shall also be taken to include any collection of machines that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein, such as cloud computing, software as a service (SaaS), other computer cluster configurations.

The machine (e.g., computer system) 400 may include a hardware processor 402 (e.g., a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), a hardware processor core, or any combination thereof), a main memory 404, a static memory (e.g., memory or storage for firmware, microcode, Basic Input Output (BIOS), Unified Extensible Firmware Interface (UEFI), etc.) 406, and a mass storage memory 408 (e.g., a hard disk drive, tape drive, flash memory, or other block device), some or all of which may communicate with each other via an interconnect (e.g., bus) 430. The machine 400 may also include a display unit 410, an alphanumeric input device 412 (e.g., a keyboard), and a User Interface (UI) navigation device 414 (e.g., a mouse). In an example, the display unit 410, the input device 412, and the UI navigation device 414 may be a touch screen display. The machine 400 may additionally include a signal generation device 418 (e.g., a speaker), a network interface device 420, and one or more sensors 416, such as a Global Positioning System (GPS) sensor, compass, accelerometer, or other sensor. The machine 400 may include an output controller 428, such as a serial (e.g., Universal Serial Bus (USB), parallel or other wired or wireless (e.g., Infrared (IR), Near Field Communication (NFC), etc.) connection to communicate or control one or more peripheral devices (e.g., a printer, card reader, etc.).

The registers of the processor 402, the main memory 404, the static memory 406, or the mass storage 408 may be or include a machine-readable medium 422, on which is stored one or more sets of data structures or instructions 424 (e.g., software), embodied or utilized by any one or more of the techniques or functions described herein. The instructions 424 may also reside, completely or at least partially, within any register of the processor 402, the main memory 404, the static memory 406, or the mass storage 408 during execution thereof by the machine 400. In one example, one or any combination of the hardware processor 402, the main memory 404, the static memory 406, or the mass storage 408 may constitute the machine-readable medium 422. While the machine-readable medium 422 is shown to be a single medium, the term "machine-readable medium" can include a single medium or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers) configured to store the one or more instructions 424.

The term "machine-readable medium" may include any medium that is capable of storing, encoding or carrying instructions for execution by the machine 400 and that cause the machine 400 to perform any one or more of the techniques of this disclosure, or that is capable of storing, encoding or carrying data structures used by or associated with such instructions. Non-limiting examples of machine-readable media may include solid-state memories, optical media, magnetic media, and signals (e.g., radio frequency signals, other photon-based signals, acoustic signals, etc.). In an example, the non-transitory machine-readable medium includes a machine-readable medium having a plurality of particles with an invariant (e.g., stationary) mass, and thus is a composition of matter. Thus, a non-transitory machine-readable medium is a machine-readable medium that does not include a transitory propagating signal. Particular examples of non-transitory machine-readable media may include: non-volatile memories 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.

The instructions 424 may also be transmitted or received over a communication network 426 using a transmission medium via the network interface device 420 utilizing any one of a number of transmission protocols (e.g., frame relay, Internet Protocol (IP), Transmission Control Protocol (TCP), User Datagram Protocol (UDP), hypertext transfer protocol (HTTP), etc.). Example communication networks can include a Local Area Network (LAN), a Wide Area Network (WAN), a packet data network (e.g., the internet), a mobile telephone network (e.g., a cellular network), a Plain Old Telephone (POTS) network, and a wireless data network (e.g., referred to as a "POTS") networkOf the Institute of Electrical and Electronics Engineers (IEEE)802.11 family of standards, referred to asIEEE 802.16 family of standards), IEEE 802.15.4 family of standards, peer-to-peer (P2P) networks, and the like. In an example, the network interface device 420 may include one or more physical jacks (e.g., ethernet, coaxial, or telephone jacks) or one or more antennas to connect to the communication network 426. In an example, network interface device 820 may include multiple antennas to wirelessly communicate using at least one of single-input multiple-output (SIMO), multiple-input multiple-output (MIMO), or multiple-input single-output (MISO) techniques. The term "transmission medium" shall be taken to include any medium that is capable of storing, encoding or carrying instructions for execution by machine 400Tangible media, and include digital or analog communications signals or other intangible media to facilitate communication of such software. A transmission medium is a machine-readable medium.

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

The above detailed description is intended to be illustrative and not restrictive. The scope of the disclosure should, therefore, be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled.