Identification of false asystole detection

Abstract

The present disclosure relates to techniques for identifying false asystole detection in a cardiac electrogram, the techniques comprising determining whether at least one of a plurality of false asystole detection criteria is satisfied. In some examples, the plurality of false asystole detection criteria comprises: a first false asystole detection criterion comprising a reduced amplitude threshold for detecting cardiac depolarization in the cardiac electrogram; and a second false asystole detection criterion for detecting attenuated noise in the cardiac electrogram.

Description

Technical Field

[0001] The present disclosure relates generally to medical systems and, more particularly, to medical systems configured to detect cardiac arrest based on a cardiac electrogram. Background Art

[0002] Some types of medical devices can monitor a patient's cardiac electrogram (EGM) to monitor the electrical activity of the patient's heart. The cardiac EGM is an electrical signal sensed by electrodes. In some instances, the medical device monitors the cardiac EGM to detect one or more types of arrhythmias, such as bradycardia, tachycardia, fibrillation, or cardiac arrest (e.g., caused by sinus pause or AV block). Summary of the invention

[0003] In addition to the signal representing the electrical activity of the heart, the cardiac EGM may also contain noise. Additionally, the amplitude of the signal representing the electrical activity of the heart within the cardiac EGM may vary over time, for example, due to movement of the electrodes relative to the heart tissue. Noise and signal amplitude variations may confound the use of the cardiac EGM to detect arrhythmias, such as cardiac arrest.

[0004] In general, the present disclosure relates to techniques for identifying false asystole detection in a cardiac electrogram. The techniques include analyzing the cardiac EGM to determine whether at least one of a plurality of false asystole detection criteria is met. In some instances, a processing circuit system of a medical device system performs this analysis in response to an asystole detection criterion being met, and can determine whether to provide or withhold an indication (e.g., to a clinician or other user) that a patient is experiencing asystole based on the analysis. In this manner, the techniques of the present disclosure can advantageously achieve improved accuracy in the identification of true asystole and, therefore, achieve a better assessment of the patient's condition.

[0005] In one example, a medical system includes a plurality of electrodes configured to sense a cardiac electrogram of a patient; and a processing circuit system. The processing circuit system is configured to determine that an asystole detection criterion is satisfied based on the cardiac electrogram, and based on the determination that the asystole detection is satisfied, determine whether a plurality of false asystole detection criteria are satisfied based on the cardiac electrogram signal. The processing circuit system is further configured to deny an indication of an asystole episode to the patient based on a determination that at least one of the plurality of false asystole detection criteria is satisfied. The plurality of false asystole detection criteria include a first false asystole detection criterion including a reduced amplitude threshold for detecting cardiac depolarization in the cardiac electrogram; and a second false asystole detection criterion for detecting attenuated noise in the cardiac electrogram.

[0006] In another example, a method includes: sensing a cardiac electrogram of a patient through a plurality of electrodes of a medical system, and determining, by a processing circuit system of the medical system, that an asystole detection criterion is satisfied based on the cardiac electrogram. The method further includes: determining, by the processing circuit system, based on the cardiac electrogram signal, that at least one of a plurality of false asystole detection criteria is satisfied based on the determination that the asystole detection is satisfied; and denying, by the processing circuit system, an indication of an asystole episode to the patient based on the determination that at least one of the plurality of false asystole detection criteria is satisfied. The plurality of false asystole detection criteria include a first false asystole detection criterion including a reduced amplitude threshold for detecting cardiac depolarization in the cardiac electrogram; and a second false asystole detection criterion for detecting attenuated noise in the cardiac electrogram.

[0007] In another example, a non-transitory computer-readable storage medium includes program instructions that, when executed by a processing circuit system of a medical system, cause the processing circuit system to determine that asystole detection criteria are satisfied based on a cardiac electrogram sensed by a plurality of electrodes of the medical system. Based on the determination that asystole detection is satisfied, the program instructions cause the processing circuit system to determine whether a plurality of false asystole detection criteria are satisfied based on the cardiac electrogram signal, and to deny an indication of an asystole episode to the patient based on the determination that at least one of the plurality of false asystole detection criteria is satisfied. The plurality of false asystole detection criteria include a first false asystole detection criterion including a reduced amplitude threshold for detecting cardiac depolarization in the cardiac electrogram; and a second false asystole detection criterion for detecting attenuated noise in the cardiac electrogram.

[0008] This summary is intended to provide an overview of the subject matter described in this disclosure. This summary is not intended to provide an exclusive or exhaustive explanation of the systems, devices, and methods described in detail in the following figures and specification. Further details of one or more examples of the present disclosure are set forth in the following figures and specification. Other features, objects, and advantages will become apparent from the description and drawings, as well as from the claims. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 The environment of an example healthcare system is presented in conjunction with patients.

[0010] Figure 2 It is shown Figure 1A functional block diagram of an example configuration of an implantable medical device (IMD) for a medical system.

[0011] Figure 3 It is shown Figure 1 and 2 Conceptual side view of an example configuration of an IMD.

[0012] Figure 4 It is shown Figure 1 A functional block diagram of an example configuration of an external device.

[0013] Figure 5 is a block diagram illustrating an example system including an access point, a network, an external computing device such as a server, and one or more other computing devices that can communicate with Figure 1-4 The IMD is coupled to an external device.

[0014] Figure 6 is a flow chart illustrating example operations for determining whether an identification of an asystole episode is false based on whether a plurality of false asystole detection criteria are met.

[0015] Figure 7 is a diagram illustrating a cardiac EGM associated with an identified asystole episode and an example technique for determining whether example false asystole detection criteria are met based on the cardiac EGM.

[0016] Figure 8 is a flow chart illustrating example operations for determining whether example false asystole criteria including a reduced amplitude threshold for depolarization detection are met.

[0017] Fig. 9 is a graph showing a cardiac EGM containing attenuated noise.

[0018] Fig.10 is a diagram illustrating a cardiac EGM including attenuated noise and an example technique for determining whether example false asystole detection criteria are met based on the cardiac EGM.

[0019] Fig.11 is a flow chart illustrating example operations for determining whether example false asystole criteria for detecting attenuated noise are met.

[0020] Fig.12 is a diagram illustrating a differential signal of a cardiac EGM including attenuated noise and an example technique for determining whether example false asystole detection criteria are met based on the cardiac EGM.

[0021] Fig.13 is a flow chart illustrating another example operation for determining whether example false asystole criteria for detecting decaying noise are met.

[0022] Fig.14 is a diagram illustrating a cardiac EGM associated with an identified asystole episode and an example technique for determining whether another example false asystole detection criterion is met based on the cardiac EGM.

[0023] Fig.15 is a flow chart illustrating another example operation for determining whether example false asystole criteria are met.

[0024] Fig.16 is a diagram illustrating a cardiac EGM associated with an identified asystole episode and an example technique for determining whether another example false asystole detection criterion is met based on the cardiac EGM.

[0025] Fig.17 is a flow chart illustrating another example operation for determining whether example false asystole criteria are met.

[0026] Fig.18A is a conceptual diagram showing a front view of a patient with another example medical system.

[0027] Fig.18B It shows that Fig.18A Conceptual illustration of a side view of an example medical system for a patient.

[0028] Fig.18C It shows that Fig.18A Conceptual illustration of an example medical system with a lateral view of a patient.

[0029] Like reference numerals refer to like elements throughout the specification and drawings. DETAILED DESCRIPTION

[0030] Various types of medical devices sense cardiac EGMs. Some medical devices that sense cardiac EGMs are non-invasive, such as using multiple electrodes placed in contact with external portions of the patient, such as at various locations on the patient's skin. As an example, the electrodes used to monitor cardiac EGMs in these non-invasive procedures can be attached to the patient using an adhesive, a cloth tape, a belt, or a vest, and electrically coupled to a monitoring device, such as an electrocardiograph, a Holter monitor, or other electronic device. The electrodes are configured to sense electrical signals associated with the electrical activity of the patient's heart or other cardiac tissue, and provide these sensed electrical signals to an electronic device for further processing and / or display of the electrical signals. Non-invasive devices and methods can be utilized on a temporary basis, such as to monitor a patient during a clinical visit, such as during a doctor's appointment, or, for example, over a predetermined period of time, such as a day (twenty-four hours), or a period of several days.

[0031] External devices that can be used to non-invasively sense and monitor cardiac EGMs include wearable devices having electrodes configured to contact the patient's skin, such as a patch, watch, or necklace. An example of a wearable physiological monitor configured to sense cardiac EGMs is the SEEQ, commercially available from Medtronic plc of Dublin, Ireland. TM Mobile cardiac telemetry systems. Such external devices can facilitate relatively long-term monitoring of patients during normal daily activities and can periodically transmit the collected data to a web service such as Medtronic's Carelink TM network.

[0032] Implantable medical devices (IMDs) can also sense and monitor cardiac EGMs. Electrodes used by an IMD to sense cardiac EGMs are typically integrated with the housing of the IMD and / or coupled to the IMD via one or more elongated leads. Example IMDs that monitor cardiac EGMs include pacemakers and implantable cardioverter-defibrillators that can be coupled to intravascular or extravascular leads, as well as pacemakers having a housing configured for implantation within the heart, which housing can be leadless. An example of a pacemaker configured for intracardiac implantation is the Micra TM Transcatheter pacing system, available from Medtronic. Some IMDs that do not provide therapy, such as implantable patient monitors, sense cardiac EGMs. An example of such an IMD is the Reveal LINQ TM Insertable cardiac monitors, available from Medtronic. This type of IMD can facilitate relatively long-term monitoring of patients during normal daily activities and can periodically transmit collected data to a web service such as Medtronic's Carelink TM network.

[0033] Regardless of which type or types of devices are used, noise signals, which may be referred to as artifacts, may appear in the cardiac EGM. The duration of the noise signal may extend over a portion of the normal time frame of the heart's cardiac cycle, or may extend over a time span over which multiple cardiac cycles might be expected to have occurred. Such noise signals may be more prevalent when the cardiac EGM is sensed using cutaneous, subcutaneous, or extravascular electrodes, for example, due to relative motion of the electrodes and tissue causing a temporary change in contact between at least one of the electrodes and the tissue on which the electrode is positioned. In some instances, the noise signal manifests as a baseline drift of the cardiac EGM, and may include a portion that decays back toward a steady-state baseline.

[0034] The presence of a noise signal in a sensed cardiac EGM may cause a circuit system used to detect depolarizations, such as R waves, to mistakenly detect the noise signal as a depolarization. The noise signal may also cause the circuit system to then fail to sense multiple subsequent depolarizations because the amplitude of the noise signal may be much larger than the subsequent depolarizations, and in some cases, because the high amplitude noise may cause the adjustable sensing threshold used by the circuit system to be adjusted to a level greater than the true depolarization amplitude. Additionally, the amplitude of a cardiac signal, such as a depolarization, within the sensed cardiac EGM may vary over time, for example due to breathing. Such cardiac signal amplitude variations may also be more common in cardiac EGMs sensed using skin, subcutaneous, or extravascular electrodes. Changes in cardiac signal amplitude may also cause depolarizations to temporarily fall below the sensing threshold and therefore not be detected.

[0035] These types of incorrect sensing of depolarization may result in an incorrect analysis of the actual cardiac activity occurring with respect to the monitored patient. For example, these types of incorrect sensing of depolarization may potentially trigger a false positive indication of a cardiac event, such as cardiac arrest, which did not actually occur in the patient. Such false positive indications may result in an erroneous assessment of the patient's condition, including providing therapy and / or sending false alarms to medical personnel responsible for the care of the monitored patient. Low pass filtering of cardiac EGMs generally does not help resolve these issues because these types of noise signals and amplitude variations may occur at frequencies close to or below the frequency of the cardiac signal.

[0036] Medical systems according to the present disclosure implement techniques for identifying false asystole detection in cardiac EGMs by, for example, detecting the presence of noise signals and changes in cardiac signal amplitude. In some instances, the system's processing circuitry analyzes the cardiac EGM associated with an identified asystole episode to determine whether one or more of a plurality of false asystole detection criteria are met. Each of the false asystole detection criteria can be configured to detect one or more indicators of noise and / or amplitude changes in the cardiac EGM.

[0037] In some instances, processing circuitry of a medical system performs this analysis in response to asystole detection criteria being met, and may determine whether to provide or withhold an indication (e.g., to a clinician or other user) that the patient is experiencing asystole based on the analysis. The processing circuitry may perform the techniques of the present disclosure in substantially real time, in response to detection of asystole, or during a later review of cardiac EGM data identified as an episode of asystole. In either case, the processing circuitry may include processing circuitry of the medical device that detected the episode of asystole and / or processing circuitry of another device, such as a local or remote computing device that retrieves the episode data from the medical device. In this manner, the techniques of the present disclosure may advantageously enable improved accuracy in identification of true asystole, and thereby enable better assessment of the patient's condition.

[0038] Figure 1 An example medical system 2 environment incorporating a patient 4 according to one or more techniques of the present disclosure is shown. The example techniques may be used with an IMD 10 that may be used with an external device 12 and Figure 1 In some examples, IMD 10 may be implanted outside the chest of patient 4 (e.g., subcutaneously). Figure 1 The IMD 10 may be positioned near the sternum at or just below the level of the patient's 4 heart, for example at least partially within the outline of the heart. The IMD 10 includes a plurality of electrodes ( Figure 1 10 is not shown in the figure) and is configured to sense cardiac EGM via a plurality of electrodes. In some examples, the IMD 10 adopts LINQ TM The form of ICM.

[0039] External device 12 may be a computing device having a display viewable by a user and an interface (i.e., a user input mechanism) for providing input to external device 12. In some examples, external device 12 may be a laptop computer, a tablet computer, a workstation, one or more servers, a cellular telephone, a personal digital assistant, or another computing device that may run an application that enables the computing device to interact with IMD 10.

[0040] External device 12 is configured to communicate with IMD 10 and optionally with another computing device ( Figure 1 For example, the external device 12 may communicate via near field communication technology (e.g., inductive coupling, NFC, or other communication technology that can operate at a range of less than 10-20 cm) and far field communication technology (e.g., according to 802.11 or The wireless communication system may communicate using radio frequency (RF) telemetry or other communication technologies that may operate at a range greater than near field communication technologies.

[0041] External device 12 may be used to configure operating parameters of IMD 10. External device 12 may be used to retrieve data from IMD 10. The retrieved data may include values ​​of physiological parameters measured by IMD 10, indications of arrhythmias or other disease episodes detected by IMD 10, and physiological signals recorded by IMD 10. For example, external device 12 may retrieve a cardiac EGM segment recorded by IMD 10 during which IMD 10 determined that cardiac arrest or another disease episode occurred. As will be described below with respect to Figure 5 As discussed in greater detail, one or more remote computing devices may interact with IMD 10 over a network in a manner similar to external device 12 , such as to program IMD 10 and / or retrieve data from IMD 10 .

[0042] Processing circuitry of a medical system 2, such as an IMD 10, an external device 12, and / or processing circuitry of one or more other computing devices, may be configured to perform example techniques of the present disclosure for identifying false asystole detection. In some instances, the processing circuitry of the medical system 2 analyzes a cardiac EGM sensed by the IMD 10 and associated with an identified asystole episode to determine whether one or more of a plurality of false asystole detection criteria are met. Each of the false asystole detection criteria may be configured to detect one or more indicators of noise and / or amplitude variations in the cardiac EGM. Although described in the context of an example in which the IMD 10 that senses the cardiac EGM includes an insertable cardiac monitor, example systems that include any type of one or more implantable or external devices configured to sense the cardiac EGM may be configured to implement techniques of the present disclosure.

[0043] Figure 2 is a method that demonstrates one or more of the techniques described herein. Figure 1 1 is a functional block diagram of an example configuration of an IMD 10. In the example shown, IMD 10 includes electrodes 16A and 16B (collectively, "electrodes 16"), antenna 26, processing circuitry 50, sensing circuitry 52, communication circuitry 54, storage device 56, switching circuitry 58, and sensor 62. Although the example shown includes two electrodes 16, in some examples, an IMD that includes or is coupled to more than two electrodes 16 may implement the techniques of this disclosure.

[0044] Processing circuit system 50 may include fixed function circuit system and / or programmable processing circuit system. Processing circuit system 50 may include any one or more of the following: a microprocessor, a controller, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or an equivalent discrete or analog logic circuit system. In some examples, processing circuit system 50 may include multiple components such as any combination of one or more microprocessors, one or more controllers, one or more DSPs, one or more ASICs, or one or more FPGAs, as well as other discrete or integrated logic circuit systems. The functions attributed to processing circuit system 50 herein may be embodied as software, firmware, hardware, or any combination thereof.

[0045] The sensing circuit system 52 can be selectively coupled to the electrode 16 via the switching circuit system 58, for example, to select the electrode 16 and polarity for sensing the cardiac EGM, referred to as a sensing vector, as controlled by the processing circuit system 50. The sensing circuit system 52 can sense signals from the electrode 16, for example, to generate a cardiac EGM, so as to monitor the electrical activity of the heart. As an example, the sensing circuit system 52 can also monitor signals from the sensor 62, which can include one or more accelerometers, pressure sensors, and / or optical sensors. In some instances, the sensing circuit system 52 can include one or more filters and amplifiers for filtering and amplifying signals received from the electrode 16 and / or the sensor 62.

[0046] The sensing circuit system 52 and / or the processing circuit system 50 can be configured to detect cardiac depolarization (e.g., P wave or R wave) when the cardiac EGM amplitude crosses a sensing threshold. In some instances, the sensing threshold can be automatically adjusted over time using any of a variety of automatic sensing threshold adjustment techniques known in the art. For example, in response to the detection of cardiac depolarization, the sensing threshold for detecting subsequent cardiac depolarization can decay from an initial value over a certain period of time. The sensing circuit system 52 and / or the processing circuit system 50 can determine the initial value based on the amplitude of the detected cardiac depolarization. The initial value and decay of the adjustable sensing threshold can be configured so that the sensing threshold is relatively high shortly after the detected cardiac depolarization when subsequent depolarization is not expected, and decays to a relatively low value over time as the occurrence of cardiac depolarization becomes more likely. In some instances, for cardiac depolarization detection, the sensing circuit system 52 can include a rectifier, a filter, an amplifier, a comparator, and / or an analog-to-digital converter.

[0047] In some examples, sensing circuitry 52 may output an indication to processing circuitry 50 in response to sensing of cardiac depolarization. In this manner, processing circuitry 50 may receive detected cardiac depolarization indicators corresponding to the occurrence of detected R and P waves in corresponding chambers of the heart. Processing circuitry 50 may use the indication of detected R and P waves to determine heart rate and detect cardiac arrhythmias, such as tachyarrhythmias and asystole.

[0048] Processing circuit system 50 may detect an episode of cardiac arrest based on determining that the cardiac electrogram meets an asystole detection criterion. The asystole detection criterion may be the absence of cardiac depolarization within a threshold time period. In such instances, processing circuit system 50 may determine that the cardiac EGM meets the asystole detection criterion based on reaching a predetermined time interval from the detection of the cardiac depolarization without receiving another indication of cardiac depolarization from sensing circuit system 52.

[0049] The sensing circuit system 52 may also provide one or more digitized cardiac EGM signals to the processing circuit system 50 for analysis, for example, for cardiac rhythm differentiation, and / or for analysis to determine whether one or more false asystole detection criteria are met in accordance with the techniques of the present disclosure. In some instances, based on the satisfaction of the asystole detection criteria, the processing circuit system 50 may store a segment of the digitized cardiac EGM corresponding to the suspected asystole as episode data in the storage device 56. The digitized cardiac EGM segment may include samples of the cardiac EGM spanning a time period during which the sensing circuit system 52 did not indicate detection of a depolarization, as well as time periods before and / or after such time period during which depolarization was detected. In accordance with the techniques of the present disclosure, the processing circuit system 50 of the IMD 10 and / or the processing circuit system of another device that retrieves episode data from the IMD 10 may analyze the cardiac EGM segment to determine whether one or more false asystole detection criteria are met.

[0050] Communication circuitry 54 may include any suitable hardware, firmware, software, or any combination thereof, for communicating with another device, such as external device 12, another networked computing device, or another IMD or sensor. Communication circuitry 54 may receive downlink telemetry from external device 12 or another device and send uplink telemetry to it under the control of processing circuitry 50 via an internal or external antenna such as antenna 26. In addition, processing circuitry 50 may communicate with an external device (e.g., external device 12) and Medtronic The antenna 26 and the communication circuit system 54 can be configured to transmit and / or receive signals via inductive coupling, electromagnetic coupling, near field communication (NFC), radio frequency (RF) communication, Bluetooth, WiFi or other proprietary or non-proprietary wireless communication schemes.

[0051] In some examples, storage device 56 includes computer-readable instructions that, when executed by processing circuit system 50, cause IMD 10 and processing circuit system 50 to perform various functions attributed to IMD 10 and processing circuit system 50 herein. Storage device 56 may include any volatile, nonvolatile, magnetic, optical, or electrical medium, such as random access memory (RAM), read-only memory (ROM), nonvolatile RAM (NVRAM), electrically erasable programmable ROM (EEPROM), flash memory, or any other digital medium. As an example, storage device 56 may store programmed values ​​for one or more operating parameters of IMD 10 and / or data collected by IMD 10 for transmission to another device using communication circuit system 54. The data stored by storage device 56 and transmitted by communication circuit system 54 to one or more other devices may include data of an episode of suspected cardiac arrest and / or an indication that the suspected cardiac arrest meets one or more false cardiac arrest detection criteria.

[0052] Figure 3 It is shown Figure 1 and 2 A conceptual side view of an example configuration of an IMD 10. Figure 3 In the example shown, IMD 10 may include a leadless subcutaneous implantable monitoring device having housing 15 and insulating cover 76. Electrodes 16A and 16B may be formed or placed on an outer surface of cover 76. Figure 2 The described circuit systems 50-62 can be formed or placed on the inner surface of the cover 76 or within the housing 15. In the illustrated example, the antenna 26 is formed or placed on the inner surface of the cover 76, but in some examples, it can be formed or placed on the outer surface. In some examples, the insulating cover 76 can be positioned over the open housing 15 so that the housing 15 and the cover 76 surround the antenna 26 and the circuit systems 50-62 and protect the antenna and the circuit systems from fluids such as body fluids.

[0053] One or more of the antenna 26 or the circuit system 50-62 can be formed on the inner side of the insulating cover 76, such as by using flip chip technology. The insulating cover 76 can be flipped onto the housing 15. When flipped and placed onto the housing 15, the components of the IMD 10 formed on the inner side of the insulating cover 76 can be positioned in the gap 78 defined by the housing 15. The electrode 16 can be electrically connected to the switching circuit system 58 through one or more through holes (not shown) formed through the insulating cover 76. The insulating cover 76 can be formed of sapphire (i.e., corundum), glass, poly-p-xylene and / or any other suitable insulating material. The housing 15 can be formed of titanium or any other suitable material (e.g., biocompatible material). The electrode 16 can be formed of any one of stainless steel, titanium, platinum, iridium, or an alloy thereof. In addition, the electrode 16 can be coated with materials such as titanium nitride or fractal titanium nitride, but other suitable materials and coatings for such electrodes can be used.

[0054] Figure 4 is a block diagram showing an example configuration of components of the external device 12. Figure 4 In the example of , external device 12 includes processing circuitry 80 , communication circuitry 82 , storage 84 , and user interface 86 .

[0055] Processing circuit system 80 may include one or more processors configured to implement functions and / or processing instructions for execution within external device 12. For example, processing circuit system 80 may be capable of processing instructions stored in storage device 84. Processing circuit system 80 may include, for example, a microprocessor, a DSP, an ASIC, an FPGA, or an equivalent discrete or integrated logic circuit system or a combination of any of the foregoing devices or circuit systems. Thus, processing circuit system 80 may include any suitable structure, whether in hardware, software, firmware, or any combination thereof, to perform the functions attributed to processing circuit system 80 herein.

[0056] Communication circuit system 82 may include any suitable hardware, firmware, software, or any combination thereof, for communicating with another device, such as IMD 10. Under the control of processing circuit system 80, communication circuit system 82 may receive downlink telemetry from IMD 10 or another device, and send uplink telemetry to it. Communication circuit system 82 may be configured to transmit and / or receive signals via inductive coupling, electromagnetic coupling, NFC, RF communication, Bluetooth, WiFi, or other proprietary or non-proprietary wireless communication schemes. Communication circuit system 82 may also be configured to communicate with devices other than IMD 10 via any of various forms of wired and / or wireless communications and / or network protocols.

[0057] The storage device 84 may be configured to store information within the external device 12 during operation. The storage device 84 may include a computer-readable storage medium or a computer-readable storage device. In some instances, the storage device 84 includes one or more of a short-term memory or a long-term memory. The storage device 84 may include, for example, RAM, DRAM, SRAM, a magnetic disk, an optical disk, a flash memory, or various forms of EPROM or EEPROM. In some instances, the storage device 84 is used to store data indicating instructions executed by the processing circuit system 80. The storage device 84 may be used by software or applications running on the external device 12 to temporarily store information during program execution.

[0058] The data exchanged between the external device 12 and the IMD 10 may include operating parameters. The external device 12 may transmit data including computer-readable instructions that, when implemented by the IMD 10, may control the IMD 10 to change one or more operating parameters and / or export collected data. For example, the processing circuit system 80 may transmit instructions to the IMD 10 requesting the IMD 10 to export collected data (e.g., asystole episode data) to the external device 12. In turn, the external device 12 may receive the collected data from the IMD 10 and store the collected data in the storage device 84. The processing circuit system 80 may implement any of the techniques described herein to analyze the cardiac EGM received from the IMD 10, for example, to determine whether asystole and pseudo-asystole criteria are met.

[0059] A user, such as a clinician or patient 4, can interact with the external device 12 through a user interface 86. The user interface 86 includes a display (not shown), such as a liquid crystal display (LCD) or a light emitting diode (LED) display or other type of screen, wherein the processing circuit system 80 can present information related to the IMD 10, such as a cardiac EGM, a detection indication of an arrhythmic episode, and a determination indication that one or more pseudo asystole detection criteria are met. In addition, the user interface 86 can include an input mechanism configured to receive input from a user. The input mechanism can include, for example, a button, a keypad (e.g., an alphanumeric keypad), a peripheral pointing device, or a touch screen, or another input mechanism that allows a user to navigate a user interface presented by the processing circuit system 80 of the external device 12 and provide input. In other instances, the user interface 86 also includes an audio circuit system for providing auditory notifications, instructions, or other sounds to the user, receiving voice commands from the user, or both.

[0060] Figure 51 is a block diagram illustrating an example system including an access point 90, a network 92, an external computing device such as a server 94, and one or more other computing devices 100A-100N (collectively, “computing devices 100”) that may be coupled to IMD 10 and external device 12 via network 92, in accordance with one or more techniques described herein. In this example, IMD 10 may communicate with external device 12 via a first wireless connection using communication circuitry 54, and communicate with access point 90 via a second wireless connection. Figure 5 In the example, the access point 90, the external device 12, the server 94 and the computing device 100 are connected to each other and can communicate with each other through the network 92.

[0061] The access point 90 may include a device connected to the network 92 via any of a variety of connections, such as a telephone dial-up, a digital subscriber line (DSL), or a cable modem connection. In other instances, the access point 90 may be coupled to the network 92 via different forms of connections, including wired connections or wireless connections. In some instances, the access point 90 may be a user device that may be co-located with the patient, such as a tablet or a smartphone. The IMD 10 may be configured to transmit data to the access point 90, such as cardiac arrest episode data and an indication of satisfying one or more pseudo-cardiac arrest detection criteria. The access point 90 may then transmit the retrieved data to the server 94 via the network 92.

[0062] In some cases, server 94 may be configured to provide a secure storage site for data that has been collected from IMD 10 and / or external devices 12. In some cases, server 94 may compile the data in a web page or other document for viewing by a trained professional (e.g., a clinician) via computing device 100. Figure 5 One or more aspects of the illustrated system may be similar to those provided by Medtronic The network is implemented using the general network technologies and functions provided by the network.

[0063] In some examples, one or more computing devices in computing 100 may be tablet computers or other smart devices located with a clinician, which the clinician may program to receive alerts and / or query IMD 10 therefrom. For example, a clinician may access data collected by IMD 10 through computing device 100, such as when patient 4 is between clinician visits, to check the status of a medical condition. In some examples, a clinician may enter instructions for medical intervention for patient 4 into an application executed by computing device 100, such as based on the status of the patient's condition determined by IMD 10, external device 12, server 94, or any combination thereof, or based on other patient data known to the clinician. Device 100 may then transmit instructions for medical intervention to another computing device in computing device 100 located with patient 4 or a caregiver of patient 4. For example, such instructions for medical intervention may include instructions for changing medication dosage, timing, or selection, for scheduling a visit with a clinician, or for seeking medical attention. In further examples, computing device 100 may generate an alert to patient 4 based on the status of patient 4's medical condition, which may enable patient 4 to proactively seek medical attention before receiving instructions for medical intervention. In this way, patient 4 may be empowered to take action as needed to address his or her medical condition, which may help improve patient 4's clinical outcomes.

[0064] In by Figure 5 In the example shown, server 94 includes, for example, a storage device 96 and processing circuitry 98 for storing data retrieved from IMD 10. Figure 5 Not shown, computing device 100 may similarly include storage devices and processing circuit systems. Processing circuit system 98 may include one or more processors configured to implement functions and / or processing instructions for execution within server 94. For example, processing circuit system 98 may be capable of processing instructions stored in storage device 96. Processing circuit system 98 may include, for example, a microprocessor, DSP, ASIC, FPGA, or equivalent discrete or integrated logic circuit system or a combination of any of the foregoing devices or circuit systems. Therefore, processing circuit system 98 may include any suitable structure, whether in hardware, software, firmware, or any combination thereof, to perform the functions attributed to processing circuit system 98 herein. Processing circuit system 98 of server 94 and / or processing circuit system of computing device 100 may implement any of the techniques described herein to analyze cardiac EGMs received from IMD 10, for example, to determine whether cardiac arrest and pseudo-cardiac arrest criteria are met.

[0065] Storage device 96 may include a computer-readable storage medium or a computer-readable storage device. In some examples, storage device 96 includes one or more of short-term memory or long-term memory. Storage device 96 may include, for example, RAM, DRAM, SRAM, magnetic disk, optical disk, flash memory, or various forms of EPROM or EEPROM. In some examples, storage device 96 is used to store data indicating instructions executed by processing circuit system 98.

[0066] Figure 6 is a flow chart illustrating example operations for determining whether an identification of an asystole episode is false based on whether a plurality of false asystole detection criteria are met. Figure 6 In the illustrated example, processing circuitry 50 of IMD 10 determines that at least one asystole detection criterion is satisfied based on the cardiac EGM sensed by sensing circuitry 52 of IMD 10 (120). Figure 2 Discussed in more detail, the processing circuitry 50 may determine that a threshold time interval, such as 2-3 seconds, has elapsed since the sensing circuitry 52 identified a cardiac depolarization, such as an R-wave, within the cardiac EGM.

[0067] Based on determining that the asystole detection criteria are met, the processing circuit system 50 determines whether one or more of a plurality of false asystole detection criteria are met. In the illustrated example, the processing circuit system 50 determines whether the false asystole detection criteria including an asystole detection count criteria are met (122). For example, the processing circuit system 50 may determine whether the asystole detection criteria are met at least a threshold number of times within a predetermined time period extending back from the most recent asystole detection criteria being met, e.g., at least twice within the past thirty days. As another example, the processing circuit system may determine whether the asystole detection criteria are met at a threshold rate, e.g., one asystole every thirty days, within a certain time period. The time period may be the entire time that the IMD 10 has been active since implantation, or since the start time of a time period other than implantation, e.g., a time period beginning a fixed number of days, weeks, or months after implantation or upon a power-on reset or other reset of the IMD 10.

[0068] Based on determining that the asystole detection count criteria are not met (NO of 122), Figure 6The example operation ends (124). Based on the determination that the asystole detection count criterion is satisfied (yes at 122), the processing circuit system 50 proceeds to determine whether one or more of the other false asystole detection criteria are satisfied. The implementation of such asystole detection count criteria is based on the observation that false asystole detections tend to occur in devices that frequently detect asystole and do not occur in devices that infrequently detect heartbeats. It is required that the asystole detection count criterion be satisfied before applying the other false asystole detection criteria, such as in Figure 6 In the example operation of , misclassification of suspected cardiac arrest as false by false cardiac arrest detection criteria can be avoided.

[0069] Noise signals may be present in the cardiac EGM intermittently or at varying frequencies based on changes in the condition of, for example, the IMD 10 or the patient 4. The likelihood that a given asystole detection is false (e.g., caused by noise) may be greater during periods when the frequency of asystole detections is greater (indicating that noise may be present in the EGM) than periods when the frequency of asystole detections is lower. Implementing asystole detection count criteria to selectively activate and deactivate evaluation of cardiac EGMs for suspected asystole episodes using the false asystole detection criteria described herein may achieve a different emphasis on sensitivity versus specificity of asystole detections based on the most recent asystole frequency, and, therefore, the likelihood that the most recent asystole episode was false.

[0070] During periods in which the asystole frequency is below a threshold such that the asystole count criteria are not met, the processing circuit system 50 may not activate evaluation of the cardiac EGM for suspected asystole episodes using the false asystole detection criteria, thereby maintaining sensitivity of asystole detection. During periods in which the asystole frequency is above a threshold such that the asystole count criteria are not met, the processing circuit system 50 may activate evaluation of the cardiac EGM for suspected asystole episodes using the false asystole detection criteria, thereby improving specificity of asystole detection. Thus, selectively (e.g., intermittently) activating and deactivating evaluation of the cardiac EGM for suspected asystole episodes using the false asystole detection criteria may provide a desired balance between sensitivity and specificity for the current condition of the cardiac EGM (e.g., the level of noise in the cardiac EGM).

[0071] In the illustrated example, based on determining that the asystole detection count criterion is met (YES of 122), processing circuit system 50 proceeds to determine whether a threshold number of depolarizations are detected within the time interval of the cardiac EGM using the reduced amplitude threshold for which no depolarizations are detected using the asystole detection criterion amplitude threshold (126). Based on the depolarizations meeting the reduced amplitude threshold criterion (YES of 126), processing circuit system 50 may determine that the suspected asystole episode is a false asystole (128). Based on the depolarizations not meeting the reduced amplitude threshold criterion (NO of 126), processing circuit system 50 may proceed to consider another false asystole detection criterion.

[0072] In the illustrated example, based on determining that the depolarization at the reduced amplitude threshold criterion is not met (NO of 126), processing circuitry 50 proceeds to determine whether the cardiac EGM associated with meeting the asystole detection criterion also meets the attenuated noise criterion (130). Based on meeting the attenuated noise criterion (YES of 130), processing circuitry 50 may determine that the suspected asystole episode is a false asystole (128). Based on not meeting the attenuated noise criterion (NO of 130), processing circuitry 50 may proceed to consider another false asystole detection criterion.

[0073] In the illustrated example, based on determining that the attenuated noise criterion is not met (NO of 130), processing circuit system 50 proceeds to determine whether the cardiac EGM associated with the suspected asystole episode meets a previous depolarization variability criterion (132). Based on meeting the previous depolarization variability criterion (YES of 132), processing circuit system 50 may determine that the suspected asystole episode is a false asystole (128). Based on not meeting the previous depolarization variability criterion (NO of 132), processing circuit system 50 may proceed to consider another false asystole detection criterion.

[0074] In the illustrated example, based on determining that the previous depolarization variability criteria are not met (No of 132), processing circuit system 50 proceeds to determine whether the cardiac EGM associated with the suspected asystole episode meets the energy pattern criteria (134). Based on the energy pattern criteria being met (Yes of 134), processing circuit system 50 may determine that the suspected asystole episode is a pseudo asystole (128). Based on the energy criteria not being met (No of 134), Figure 6 The example operation ends (124).

[0075] based on Figure 6The example operation of ends (124), for example, because none of the false asystole detection criteria were met, or an insufficient number or combination of false asystole detection criteria were met, processing circuit system 50 may classify the suspected asystole episode as a true asystole episode. Based on the classification of the asystole episode as real, processing circuit system 50 may use the asystole episode in additional operations such as calculating statistics, determining patient status, or transmitting real episode data to other devices. Based on determining that the suspected asystole episode is a false asystole (128), processing circuit system 50 may use the false asystole episode in additional operations such as calculating statistics for false episodes and transmitting false episode data to other devices, for example, for the user to consider modifying the operation of IMD 10 to avoid additional false asystole detections.

[0076] Figure 6 The order and flow of operations shown are an example. In other examples according to the present disclosure, more or fewer false asystole detection criteria may be considered, false asystole detection criteria may be considered in a different order, or a different number or combination of false asystole detection criteria may need to be met to determine that a suspected asystole episode is false. Further, in some examples, as directed by a user, the processing circuit system may or may not perform the processing, for example, via external device 12 or computing device 100. Figure 6 For example, a patient, clinician, or other user can turn on or off a feature for identifying false asystole detection remotely (e.g., using Wi-Fi or cellular service) or locally (e.g., using an application provided on the patient's cell phone or using a medical device programmer).

[0077] Additionally, although described in the context of examples of each of the portions in which IMD 10 and processing circuitry 50 of IMD 10 perform example operations, Figure 6 Example operations and this article about Figure 7-17 The example operations described may be performed by any processing circuitry of any one or more devices of the medical system, such as any combination of one or more of processing circuitry 50 of IMD 10, processing circuitry 80 of external device 12, processing circuitry 98 of server 94, or processing circuitry of computing device 100. In some instances, processing circuitry 50 of IMD 10 may determine whether asystole detection criteria are met and provide episode data of a suspected asystole episode to another device. In such instances, processing circuitry of the other device (e.g., external device 12, server 94, or computing device 100) may apply one or more false asystole detection criteria to the episode data.

[0078] Figure 7 is a diagram illustrating a cardiac EGM 148 associated with an identified episode of suspected cardiac asystole and an example technique for determining whether example false asystole detection criteria are satisfied based on cardiac EGM 148. In some examples, cardiac EGM 148 is a digitized segment of the cardiac EGM sensed by sensing circuitry 52 of IMD 10 via electrodes 16 and corresponds to the application of one or more asystole detection criteria to the cardiac EGM identified by processing circuitry 50.

[0079] Figure 7 Cardiac depolarizations 150A-150H (in this example, R-waves) are shown as being identified by the IMD 10, such as by comparing the cardiac EGM 148 to an amplitude threshold, which may be automatically adjustable as described herein. Figure 7 Also shown is an asystole interval 152. Asystole interval 152 represents a time interval between adjacent depolarizations 150F and 150G identified by IMD 10. As described herein, processing circuitry 50 may have determined that asystole detection criteria are satisfied when asystole interval 152 reaches a predetermined threshold amount of time. Based on satisfaction of asystole detection criteria, processing circuitry 50 may have stored in storage device 52 cardiac EGM 148 (including time periods before and after asystole interval 152) and an indication of detection (e.g., timing) of depolarizations 150A-150H.

[0080] As reference Figure 6 As described in item 126 of , a false asystole detection criterion may include using a reduced amplitude threshold 154 to determine whether a threshold amount of depolarization is detected within the cardiac EGM 148 during the asystole interval 152. Figure 7 In the example shown, processing circuitry 50 detects depolarizations 150I-150K during interval 152 by comparing cardiac EGM 148 to a reduced amplitude threshold 154. The threshold number of depolarizations detected during interval 152 using threshold 154 required to meet the reduced amplitude threshold criteria may be any integer greater than or equal to one, including two or three detected depolarizations.

[0081] In some instances, processing circuit system 50 determines reduced amplitude threshold 154 based on the amplitude of a predetermined number of depolarizations 150A-150F preceding asystole interval 152. In some instances, processing circuit system 50 determines the amplitude of depolarizations 150A-150F by determining the amplitude of cardiac EGM 148 at samples corresponding to zero crossings in the differential signal of cardiac EGM 148. In some instances, processing circuit system 50 determines a representative value of the amplitude of depolarizations 150A-150F, such as a median or mean value of the amplitude, and determines reduced amplitude threshold 154 as a predetermined portion, such as a fraction or percentage, of the representative amplitude. As examples, the predetermined portion may be 1 / 10, 1 / 8, 1 / 5, 1 / 3, or 1 / 2. Any number of previous depolarizations may be used to determine threshold 154, such as two to eight previous depolarizations, including six previous depolarizations in some instances.

[0082] In one example, if the median amplitude of the six previous R waves is 80 microvolts (μV), the reduced amplitude threshold 154 of 1 / 8 of the median amplitude would be 10 μV. In such an example, if a 15 μV signal is present in the cardiac EGM 148 during the interval 152, the processing circuit system 50 would determine that the false asystole detection criteria are met. Applying the reduced amplitude threshold 154 during the asystole interval 152 may also obscure AV block with a 15 μV P wave. However, based on the asystole detection count criteria ( Figure 6 The satisfaction of 122) and the low probability that this false asystole detection criterion will be satisfied by a cardiac EGM with a relatively high R wave amplitude reduce the likelihood of misclassification of an episode by applying this false asystole detection criterion.

[0083] Figure 8 1 is an example operation for determining whether an example false asystole criteria including a reduced amplitude threshold for depolarization detection is satisfied (e.g., corresponding to Figure 6 Flowchart of item 126 in . Figure 7 The cardiac EGM 148 and other data are shown to describe Figure 8 Example operation of .

[0084] according to Figure 8 In the illustrated example, processing circuitry 50 of IMD 10 identifies a predetermined number "N" of depolarizations 150 prior to an asystolic interval 152, such as the most recent N depolarizations prior to the asystolic interval (160). Processing circuitry 50 determines amplitudes of the N prior depolarizations 150 (162). Processing circuitry 50 determines a reduced amplitude threshold 154 (164) based on the amplitudes of the N prior depolarizations 150, such as based on a predetermined fraction or other portion of a median or other representative value of the determined amplitudes of the N prior depolarizations 150.

[0085] The processing circuit system 50 compares the reduced amplitude threshold 154 to the cardiac EGM 148 within the asystole interval 152 (e.g., a portion of the cardiac EGM 148 within the entire asystole interval or within a portion of the asystole interval) (166). The processing circuit system 50 determines whether a threshold number of depolarizations 150 are identified within the asystole interval 152 based on the comparison, such as based on the cardiac EGM 148 being equal to or greater than the reduced amplitude threshold 154 within the asystole interval (168). As examples, the threshold number of depolarizations can be one, two, or three depolarizations. Based on detecting the threshold number of depolarizations (yes of 168), the processing circuit system 50 can determine that the suspected asystole episode is a false asystole (128). Based on not detecting the threshold number of depolarizations (no of 168), the processing circuit system 50 can proceed to apply another false asystole detection criterion, such as reference Figure 6 The attenuation noise standard (170) described in block 130 of FIG.

[0086] Fig. 9 is a diagram showing a cardiac EGM 181 including attenuated noise. The cardiac EGM 181 may be a digitized cardiac EGM segment including episode data that is a suspected asystole episode.

[0087] The cardiac EGM 181 includes a pattern of somewhat consistent peaks and variations in amplitude that repeat at relatively consistent time intervals over the time span generally indicated by bracket 182. During the time span generally indicated by bracket 183, the cardiac EGM 181 does not continue to provide the consistent pattern previously provided during the time span indicated by bracket 182, but instead provides a large amplitude spike 184 having an amplitude and duration that is much greater than any of the peaks provided in the cardiac EGM 181 during the time span indicated by bracket 182.

[0088] After the amplitude spike 184, and during the time span indicated generally by bracket 185, the cardiac EGM 181 contains greater variations in signal amplitude and may contain more negative peaks and / or lower overall mean or median amplitude values ​​than if these same parameters were measured within the time span indicated by bracket 182. In some examples of false asystole detection criteria, the processing circuitry 50 may analyze the amplitude spike 184 and / or the variations exhibited during the time span indicated by bracket 185 after the amplitude spike 184 to determine whether these portions of the cardiac EGM 181 represent noise signals, such as decaying noise.

[0089] Fig.10is a diagram illustrating a cardiac EGM 191 including attenuated noise and an example technique for determining whether example false asystole detection criteria are met based on the cardiac EGM. The cardiac EGM 191 may be a digitized cardiac EGM segment containing episode data for a suspected asystole episode by the IMD 10, e.g., based on a determination by the processing circuitry 50 of the IMD 10 that the asystole detection criteria are met.

[0090] like Fig.10 As shown, the cardiac EGM 191 contains an amplitude spike 202 in the portion of the cardiac EGM 191 after a time indicated as "0" (zero) seconds. Using a set of detection windows, such as those provided by Fig.10 As illustratively shown in the example of detection windows 194 and 196 , processing circuitry 50 may analyze one or more portions of cardiac EGM 191 to determine whether cardiac EGM 191 contains noise signals, such as amplitude spikes 202 or other attenuated noise.

[0091] In various examples, analyzing the cardiac EGM 191 to determine if a noise signal is present includes determining a sampling time 192 as a basis for setting detection windows 194 and 196. In some examples, determining the sampling time 192 includes setting the sampling time equal to a time at which a depolarization 203, such as an R wave, has been detected within the cardiac EGM 191. In some examples, the depolarization 203 may be during the asystole interval 152 ( Figure 7 ) before the most recent depolarization.

[0092] Once processing circuitry 50 selects sampling time 192, processing circuitry 50 may set baseline window 194 such that it includes a time span 195 extending from sampling time 192 and some amount of time before sampling time 192. The width of time span 195 is not limited to any particular time span, and in some examples may be a time span in the range of 0.5 to 5 seconds. Fig.10 In the example of , the baseline window 194 extends from the sampling time 192 and includes an illustrative time span 195 of approximately 1 second, extending to include a portion of the cardiac EGM 191 ranging from the sampling time 192 to a time up to one second prior to the sampling time 192 .

[0093] In various examples, processing circuitry 50 determines a baseline amplitude value 199 based on sampling time 192 and baseline window 194. Processing circuitry 50 may calculate the value of baseline amplitude 199 by determining the amplitude of samples of cardiac EGM 191 that fall within baseline window 194 and determining baseline amplitude 199 based on these determined amplitude values. In some examples, the value of baseline amplitude 199 may be an average or median of the amplitude values ​​of cardiac EGM 191 during baseline window 194.

[0094] Processing circuitry 50 also sets measurement window 196 to include a time span 197 extending from sampling time 192 and a certain amount of time after sampling time 192. Time span 197 is not limited to any particular duration, and in some examples may be in the range of 0.5 to 5 seconds. Fig.10 In the example of FIG. 1 , the time span is approximately 1 second in duration and includes the portion of the cardiac EGM 191 ranging from the sampling time 192 to a time of up to one second after the sampling time 192. In various examples, the width of the time span 197 of the measurement window 196 is equal to or different than the width of the time span 195 set for the baseline window 194. In the example where the depolarization 203 is the most recent depolarization prior to the asystole interval 152, the measurement window 196 includes at least a portion of the asystole interval.

[0095] Processing circuitry 50 may determine amplitude values ​​for samples of cardiac EGM 191 within measurement window 196. Processing circuitry 50 may determine an area under the curve value for a portion of cardiac EGM 191 based on these sampled amplitude values ​​within measurement window 196 and a baseline amplitude value 199 determined based on baseline window 194.

[0096] For example, the processing circuit system 50 can determine a set of differences between the amplitude value of the cardiac EGM 191 that falls within the measurement window 196 and the baseline amplitude value 199. In some instances, the processing circuit system 50 determines the area under the curve value by calculating the area 198 contained below the portion of the cardiac EGM 191 that falls within the measurement window 196 and is higher than the baseline amplitude value 199. The calculation of the area under the curve value is not limited to any particular technique for calculating this area, and can include any technique for calculating the area under the curve, as will be understood by a person of ordinary skill in the art. Once the area under the curve value has been calculated for the area 198, the processing circuit system 50 can compare the area under the curve value with a noise signal threshold. In some instances, if the area under the curve value exceeds or equals the noise signal threshold, the processing circuit system 50 determines that a noise signal has been detected within the cardiac EGM 191 and the false asystole detection criteria are met.

[0097] Despite Fig.10In the example of baseline window 194 extending backward in time and measurement window 196 extending forward in time from the most recent previous depolarization 203, processing circuit system 50 may set baseline window 194 and measurement window 196 to have other temporal relationships to depolarization 203. For example, processing circuit system 50 may set baseline window 194 to extend forward in time from depolarization 203 and set measurement window 196 to extend forward in time from the end of baseline window 194. In such examples, baseline window 194 may correspond to a period after detection of depolarization 203 during which IMD 10 is prevented from detecting subsequent depolarizations, referred to as a blanking period. In such examples, measurement window 196 may have a greater duration than baseline window 194, e.g., to capture the expected duration of amplitude spike 202. In some examples, baseline window 194 and measurement window 196 need not be continuous or contiguous.

[0098] Typically, P waves are relatively narrower and / or more evenly distributed above and below the baseline amplitude, and therefore have smaller area-under-the-curve measurements, then decay, such as exponentially decaying noise signals. Therefore, area-under-the-curve measurements may be an effective discriminator between P waves occurring during true asystole and decaying noise that results in false asystole detection.

[0099] Fig.11 is an example operation for determining whether an example false asystole criterion for detecting attenuated noise is satisfied (eg, corresponding to Figure 6 Flowchart of item 130). Figure 7 The cardiac EGM 148 and other data displayed and Fig.10 The cardiac EGM 191 and other data presented are described Fig.11 Example operation of .

[0100] according to Fig.11 In the example of FIG. 1 , processing circuitry 50 identifies a last depolarization 203 before asystole interval 152 (220). Processing circuitry 50 further sets baseline window 194 and measurement window 196 based on the time of last depolarization 203 (222). Processing circuitry 50 determines baseline amplitude 199 based on the amplitude of cardiac EGM 191 within baseline window 194, e.g., as an average or median of the amplitudes within baseline window 194 (224).

[0101] The processing circuitry 50 further determines an area under the curve measurement of the portion of the cardiac EGM 191 within the measurement window 196 relative to the baseline amplitude 199 (226). For example, the processing circuitry 50 may determine the area under the curve measurement based on the sum of the differences between the amplitudes of the samples of the cardiac EGM 191 within the measurement window 196 and the baseline amplitude 199. Any known technique for area under the curve measurement may be employed.

[0102] Processing circuitry 50 determines whether the area under the curve measurement satisfies a threshold, such as being equal to or greater than a threshold (228). Based on the area under the curve measurement satisfying the threshold (yes of 228), processing circuitry 50 may determine that the suspected asystole episode is a false asystole (128). Based on the area under the curve measurement not satisfying the threshold (no of 228), processing circuitry 50 may proceed to apply another false asystole detection criterion, such as reference Figure 6 The previous depolarization variability criteria (170) described in box 132.

[0103] Fig.12 is a diagram illustrating a differential signal 241 of a cardiac EGM including attenuated noise and an example technique for determining whether an example false asystole detection criteria are met based on the cardiac EGM. The processing circuit system 50 of the IMD 10 can determine the differential signal 241 based on a digitized cardiac EGM segment containing episode data as a suspected asystole episode by the IMD 10, for example, based on the processing circuit system 50 determining that the asystole detection criteria are met. In some examples, the processing circuit system 50 determines the value of each sample "y" of the differential signal 241 by obtaining the amplitude value of the corresponding sample "y" of the cardiac EGM and subtracting the amplitude value of the cardiac EGM at the sample "yn" from the amplitude value, where n is a predetermined number of samples.

[0104] like Fig.12 As shown, some of the values ​​of the differential signal 241 are below the "zero" value line 237, and some of the signal values ​​within the differential signal 241 are above the "zero" value line 237. Noise signals in the cardiac EGM, such as Fig.10 The illustrated amplitude spike 202 may result in the differential signal having one or more spikes, such as spike 242 in differential signal 241 , followed by the differential signal 241 gradually returning to zero value line 237 .

[0105] The processing circuit system 50 can set the measurement window 246 based on the detection of an event such as an R wave of other depolarizations 243 in the cardiac EGM. In the illustrated example, the time span 245 begins at the time of the detection of the depolarization 243. Fig.12In the example of , time span 245 extends over a time period of 0.5 seconds. The time period contained within time span 245 is not limited to any particular time span, and in some examples may be in the range of 0.2 to 1 second. In some examples, time span 245 may correspond to a period after detection of depolarization 243 during which IMD 10 is prevented from detecting a subsequent depolarization, referred to as a blanking period.

[0106] Measurement window 246 begins at the time when time span 245 expires, as illustrated by vertical dashed line 247, and extends within time span 248, ending when time span 248 expires. Fig.12 In the example of , time span 248 extends over a time period of 1.5 seconds. The time period included in time span 248 is not limited to any particular time span, and in some examples may range from one second to five seconds.

[0107] The processing circuit system 50 determines a sign for samples of the differential signal 241 within the measurement window 246, i.e., positive above the zero line 237, negative below the zero line 237, or on the zero line. The processing circuit system 50 determines a count of one or more of the signs and determines whether the count meets, e.g., equals, exceeds, or is below a threshold. The count may take the form of a percentage or fraction of the total number of samples considered. Typically, when attenuation noise is present in the cardiac EGM, the sign of the differential signal 241 within the measurement window 246 will be unbalanced, e.g., Fig.12 In some examples, more signs are negative. Although in some examples, negative signs may be counted or quantified, other examples may include counting or quantifying the number of positive sample values, the number of non-negative sample values ​​(e.g., the count of zero sample values ​​plus positive sample values), or the number of non-positive sample values ​​(e.g., the count of zero sample values ​​plus negative sample values).

[0108] Using an imbalance in the sign of the differential signal within the measurement window after the last depolarization to detect the presence of decaying noise may involve simpler calculations for processing circuitry 50 of IMD 10, then calculating the area under the curve to detect decaying noise. Further, P waves or thermal noise occurring during asystole intervals during true asystole will have a substantially equal distribution of signs of the differential signal within the measurement window (occurring during asystole intervals), whereas exponential or other decaying noise may have more than 70% of the samples having a notable sign, such as negative.

[0109] Fig.13 is a flow chart illustrating another example operation for determining whether example false asystole criteria for detecting attenuated noise are met. Fig.12 The cardiac differential signal 241 and other data are shown to describe Fig.13 Example operation of .

[0110] according to Fig.13 In an example, the processing circuit system 50 identifies the asystole interval, for example Figure 7 The processing circuit system 50 further sets a measurement window 246 (262) that begins at a time period 245 after the last depolarization and determines the differential signal 241 within the measurement window 246 (264). The processing circuit system 50 further determines the signs of the samples of the differential signal 241 within the measurement window 246 and, for at least one of the symbols, counts or otherwise quantifies the number of samples having the sign (266).

[0111] Processing circuitry 50 determines whether the count of one of the symbols satisfies a common symbol threshold, e.g., is equal to or greater than a threshold (268). Based on the common symbol threshold being satisfied (yes of 268), processing circuitry 50 may determine that the suspected asystole episode is a false asystole (128). Based on the common symbol threshold not being satisfied (no of 268), processing circuitry 50 may proceed to apply another false asystole detection criterion, such as reference Figure 6 The previous depolarization variability criteria (270) described in box 132 of FIG.

[0112] Fig.14 2 is a diagram illustrating a cardiac EGM 290 associated with an identified asystole episode and an example technique for determining whether another example false asystole detection criterion is satisfied based on the cardiac EGM. The cardiac EGM 290 may be a digitized cardiac EGM segment that contains episode data as a suspected asystole episode by the IMD 10, e.g., based on a determination by the processing circuitry 50 of the IMD 10 that the asystole detection criterion is satisfied.

[0113] Fig.14 Cardiac depolarizations 292A- 292G (in this example, R-waves) are shown as being identified by IMD 10 , for example, by comparing cardiac EGM 290 to an amplitude threshold, which may be automatically adjustable as described herein. Fig.14Also shown is an asystole interval 294. Asystole interval 294 represents a time interval between adjacent (in time) depolarizations 292F and 292G identified by IMD 10. As described herein, processing circuitry 50 may have determined that asystole detection criteria have been satisfied when asystole interval 294 reaches a predetermined threshold amount of time. Based on satisfaction of asystole detection criteria, processing circuitry may have stored in storage device 52 an indication of the detection (e.g., timing) of depolarizations 292A-292G (collectively, "depolarizations 292").

[0114] As reference Figure 6 As described in Item 132 of , a false asystole detection criterion may include determining whether the variability of N depolarizations 292 preceding an asystole interval 294 satisfies a variability threshold. The number "N" of depolarizations preceding an asystole interval 294 may be any integer greater than one, such as four, six, or eight. The N depolarizations 292 may, but need not, include the last depolarization 292F preceding an asystole interval 294. For example, the processing circuit system 50 may determine the variability of the six depolarizations 292A-292F preceding an asystole interval 292.

[0115] The variability may be of the amplitude or other characteristic of depolarizations 292. Processing circuitry 50 may measure or otherwise characterize the variability of multiple values ​​using any known technique to determine the variability of previous depolarizations 292. In some examples, processing circuitry 50 compares, for example, determines a difference between a maximum amplitude and a median amplitude of previous depolarizations. In such examples, processing circuitry 50 may determine whether the difference or other comparison satisfies, for example, exceeds, a predetermined threshold.

[0116] Electrical noise can cause false asystole detections. In some instances, a cardiac EGM of an asystole episode falsely detected due to electrical noise looks like a flat line with random peaks ranging from 40uV to 2000uV added. A true cardiac EGM may not contain such a wide range of R-wave amplitudes over several seconds. Variability in the preceding depolarization, such as the difference between the maximum and the median, can be very sensitive and specific to false asystole detections caused by electrical noise. Although such criteria may falsely reject a true asystole detection if the electrical noise occurs just prior to a true asystole detection, such a convergence is unlikely to occur, particularly in IMDs where the asystole detection frequency is below the asystole count detection threshold ( Figure 6 122).

[0117] Fig.15 is a flow chart illustrating another example operation for determining whether example false asystole criteria are met. Fig.14 The cardiac EGM 290 and other data are shown to describe Fig.15 Example operation of .

[0118] according to Fig.15 In an example of a cardiac arrest, processing circuit system 50 identifies N depolarizations 292 that precede an asystole interval 294 (300). Processing circuit system 50 determines a variability of N prior depolarizations 292. For example, processing circuit system 50 may determine the amplitudes of N prior depolarizations 292, determine a maximum amplitude of the N prior depolarizations 292, and determine a representative value of the amplitudes of the N prior depolarizations 292, such as a median or mean value of the amplitudes (302). Processing circuit system 50 further determines a comparison metric, such as a difference or ratio, between the maximum amplitude and the representative amplitude (304).

[0119] Processing circuitry 50 determines whether the comparison metric satisfies a threshold, e.g., is equal to or greater than a threshold (306). Based on the comparison metric satisfying the threshold (yes of 306), processing circuitry 50 may determine that the suspected asystole episode is a false asystole (128). Based on the comparison metric not satisfying the threshold (no of 306), processing circuitry 50 may proceed to apply another false asystole detection criterion, such as reference 128. Figure 6 The energy mode criteria (308) described in block 134 of FIG.

[0120] Fig.16 is a diagram illustrating a cardiac EGM 320 associated with an identified asystole episode and an example technique for determining whether another example false asystole detection criterion is satisfied based on the cardiac EGM. The cardiac EGM 320 may be a digitized cardiac EGM segment that contains episode data as a suspected asystole episode by the IMD 10, e.g., based on a determination by the processing circuitry 50 of the IMD 10 that the asystole detection criterion is satisfied.

[0121] Fig.16 Cardiac depolarizations 322A- 322E (in this example, R-waves) are shown as being identified by IMD 10 , for example, by comparing cardiac EGM 320 to an amplitude threshold, which may be automatically adjustable as described herein. Fig.16Also shown is an asystole interval 323. Asystole interval 323 represents a time interval between adjacent depolarizations 322D and 322E identified by IMD 10. As described herein, processing circuitry 50 may have determined that asystole detection criteria are satisfied when asystole interval 323 reaches a predetermined threshold amount of time. Based on satisfaction of asystole detection criteria, processing circuitry 50 may have stored in storage device 52 an indication of the detection (e.g., timing) of depolarizations 322A-322E (collectively, “depolarizations 322”) and cardiac EGM 320 (including time periods before and after asystole interval 323).

[0122] As reference Figure 6 As described in Item 134 of , a false asystole detection criterion can include evaluating an energy pattern of the cardiac EGM 320 during an asystole interval 323. When a physician views a cardiac EGM such as a graphical representation of the cardiac EGM 320 to determine whether a suspected asystole is true or false, the physician can measure or estimate the RR interval prior to the asystole interval 323 and determine whether there is a visible small peak within the asystole interval 323 that is the same speed or in phase with, for example, an RR interval that would have been similar to a previous RR interval. Such a pattern can indicate to the physician that the asystole detection is false and is caused by, for example, a drop in R-wave amplitude. In contrast, during a true asystole caused by AV block, a small peak within the asystole interval 323 that is out of phase with a previous RR interval may be a P wave.

[0123] In some instances, the processing circuit system 50 identifies N depolarizations 322 preceding an asystole interval 323, such as N consecutive depolarizations 322 including a last depolarization 322D preceding the asystole interval 323. Based on the N prior depolarizations 322, the processing circuit system 50 may determine N-1 intervals between the prior depolarizations 322, including intervals 324A and 324B (collectively referred to as "inter-depolarization intervals 324"). N may be any integer, such as seven or thirteen. Within the asystole interval 323, the processing circuit system 50 sets expected depolarization windows 326A-326C (collectively referred to as "expected depolarization windows 326") and expected inter-depolarization windows 328A-328C (collectively referred to as "expected inter-depolarization windows 328") based on the inter-depolarization intervals 324. Although in Fig.16 While the example shown has three of each type of window, other examples may employ more or fewer of each type of window, and / or different numbers of windows for the two types of windows.

[0124] In some examples, processing circuit system 50 determines a median or other representative value of inter-depolarization intervals 324. Processing circuit system 50 may set windows 326 and 328 within asystole interval 323 based on the representative value of inter-depolarization intervals 324. For example, processing circuit system 50 may set each of expected depolarization windows 326 to occur, e.g., centered in time, i.e., at a different integer multiple of the representative interval after the last prior depolarization 322D. In one such example, processing circuit system 50 may set expected depolarization window 326A to the representative interval after depolarization 322D, set expected depolarization window 326B to twice the representative interval after depolarization 322D, and set expected depolarization window 326C to three times the representative interval after depolarization 322D. Processing circuit system 50 may set each of expected inter-depolarization windows 328 to occur, for example, centered in time, i.e., at a different non-integer, e.g., fractional, multiple of the representative interval after the last prior depolarization 322D. In one such example, processing circuit system 50 may set expected inter-depolarization window 328A to one-half of the representative interval after depolarization 322D, expected inter-depolarization window 328B to one and a half times the representative interval after depolarization 322D, and expected inter-depolarization window 328C to two and a half times the representative interval after depolarization 322D. The width of windows 326 and 328 may be set to a predetermined portion, e.g., a fraction or percentage, or a representative interval, and the predetermined portion may be the same or different between window 326 and window 328.

[0125] Processing circuit system 50 determines a first energy value for expected depolarization window 326 and a second energy value for expected inter-depolarization window 328. In some examples, processing circuit system 50 determines an energy value for each of window 326 and window 328, and then determines a first mean, median, or other representative energy value for the energy values ​​of window 326, and a second representative energy value for the energy values ​​of window 328. Processing circuit system 50 may employ any known technique to determine the energy of the signal within the window. In some examples, as the energy value for each of windows 326 and 328, processing circuit system 50 determines a difference, ratio, or other comparison measure between the maximum amplitude of cardiac EGM 320 and the minimum amplitude of cardiac EGM 320 within the window.

[0126] Processing circuit system 50 further determines a difference, ratio, or other comparison metric between the first representative energy value of expected depolarization window 326 and the second representative energy value of expected inter-depolarization window 328. Processing circuit system 50 determines whether the comparison metric meets, e.g., equals or exceeds, a threshold. A relatively high first representative energy value compared to the second energy level may indicate the presence of a low amplitude depolarization, e.g., an R wave, within asystole interval 323 that is in phase with the rhythm preceding asystole interval 323, and that the suspected asystole is a false asystole detection.

[0127] Fig.17 is a flow chart illustrating another example operation for determining whether example false asystole criteria are met. Fig.16 The cardiac EGM 320 and other data are shown to describe Fig.17 Example operation of .

[0128] according to Fig.17 In the example of FIG. 1 , processing circuitry 50 identifies N depolarizations 322 (340) preceding asystole interval 323. Processing circuitry 50 determines intervals 324 (342) between N preceding depolarizations 322. Processing circuitry 50 further sets an expected depolarization window 326 and an expected inter-depolarization window 328 within asystole interval 323 based on intervals 324, e.g., based on integer and non-integer multiples of a mean or median of intervals 324, respectively (344).

[0129] Processing circuitry 50 determines respective energy values ​​for expected depolarization windows 326 and expected inter-depolarization windows 328, e.g., the difference between the maximum amplitude and the minimum amplitude of cardiac EGM 320 within each window (346). Processing circuitry 50 further determines a comparison metric between the energy of window 326 and the energy of window 328 (348). For example, processing circuitry 50 may determine the difference between the average value of the energy of window 326 and the average value of the energy of window 328.

[0130] Processing circuitry 50 determines whether the comparison metric satisfies a threshold, e.g., is equal to or greater than a threshold (350). Based on the comparison metric satisfying the threshold (yes of 350), processing circuitry 50 may determine that the suspected asystole episode is a false asystole (128). Based on the comparison metric not satisfying the threshold (no of 350), processing circuitry 50 may proceed to apply another false asystole detection criterion or, if there is no another false asystole detection criterion to apply, Fig.17 and 6 The operation can end (124).

[0131] Figures 18A-18C is a conceptual diagram of another example medical system 410 implanted within a patient 408 . Fig.18A is a front view of medical system 410 implanted in patient 408. Fig.18B is a side view of medical system 410 implanted in patient 408 . Fig.18C is a lateral view of medical device system 410 implanted in patient 408 .

[0132] In some examples, the medical system 410 is an extravascular implantable cardioverter-defibrillator (EV-ICD) system implanted in the patient 408. The medical system 410 includes an IMD 412, which is implanted subcutaneously or submuscularly on the left mid-axillary of the patient 408 in the illustrated example, so that the IMD 412 can be positioned above the left thorax of the patient 408. In some other examples, the IMD 412 can be implanted at other subcutaneous locations on the patient 408, such as at a chest location or an abdominal location. The IMD 412 includes a housing 420 that can form an airtight seal that protects the components of the IMD 412. In some examples, the housing 420 of the IMD 412 can be formed of a conductive material such as titanium or a combination of conductive and non-conductive materials that can be used as housing electrodes. IMD 412 may also include a connector assembly (also referred to as a connector block or plug) that includes electrical feedthroughs through which electrical connections are made between leads 422 and electronic components contained within the housing.

[0133] IMD 412 may provide cardiac EGM sensing, asystole detection, and other functionality described herein with respect to IMD 10, and housing 420 may house circuitry 50-62 and antenna 26 ( Figure 2 and 3 ). Housing 420 may also house therapy delivery circuitry configured to generate therapeutic electrical signals, such as cardiac pacing and anti-tachyarrhythmia shocks, for delivery to patient 408. System 410 may include external device 12 that may work with IMD 412, as described herein with respect to IMD 10 and system 2.

[0134] In the illustrated example, the IMD 412 is connected to at least one implantable cardiac lead 422. The lead 422 includes an elongated lead body having a proximal end and a distal portion, the proximal end including a connector (not shown) configured to be connected to the IMD 412, the distal portion including electrodes 432A, 432B, 434A, and 434B. The lead 422 extends subcutaneously above the thorax from the IMD 412 toward the center of the torso of the patient 408. At a location near the center of the torso, the lead 422 bends or turns and extends upward within the thorax below / under the sternum 424. Thus, the lead 422 can be at least partially implanted in the substernal space, such as at a target site between the thorax or sternum 424 and the heart 418. In one such configuration, the proximal portion of lead 422 can be configured to extend subcutaneously from IMD 12 toward sternum 24, and the distal portion of lead 22 can be configured to extend superiorly in anterior mediastinum 426 below or beneath sternum 424 ( Fig.18C ).

[0135] For example, lead 422 can extend upward in the thoracic cavity below / below sternum 424 in anterior mediastinum 426. Anterior mediastinum 426 can be considered to be defined by pericardium 416 in the rear, defined by pleura 428 in the lateral direction, and defined by sternum 424 in the front. In some instances, the anterior wall of anterior mediastinum 426 can also be formed by transverse pectoralis muscle and one or more costal cartilages. Anterior mediastinum 426 contains a certain amount of loose connective tissue (such as honeycomb), some lymphatic vessels, lymph glands, substernal muscle tissue (e.g., transverse pectoralis muscle) and small blood vessels or vascular branches. In one instance, the distal portion of lead 422 can be substantially implanted in the loose connective tissue and / or substernal muscle tissue of anterior mediastinum 426. In such instances, the distal portion of lead 422 can be physically isolated from pericardium 416 of heart 418. The lead substantially implanted in anterior mediastinum 426 is an example of a substernal lead or, more generally, an extravascular lead.

[0136] The distal portion of the lead 422 is described herein as being implanted substantially within the anterior mediastinum 426. Thus, some of the distal portion of the lead 422 may extend beyond the anterior mediastinum 426 (e.g., the proximal end of the distal portion), but the majority of the distal portion may be positioned within the anterior mediastinum 426. In other embodiments, the distal portion of the lead 422 may be implanted intrathoracically at other non-vascular extrapericardial locations, including spaces, tissues, or other anatomical features surrounding the periphery of and adjacent to but not attached to the pericardium 416 or other portions of the heart 418 and not above the sternum 424 or thorax. The lead 422 may be implanted anywhere within the "substernal space" defined by the lower surface between the sternum and / or thorax and the body cavity, but not including the pericardium 416 or other portions of the heart 418. The substernal space may alternatively be referred to by the terms "retrosternal space" or "mediastinum" or "substernal" known to those skilled in the art and include the anterior mediastinum 426. The substernal space may also include the anatomical region described in Baudoin, YP et al., entitled "The superior epigastric artery does not pass through Larrey's space (trigonum sternocostale)" Surg. Radiol. Anat. 25.3-4 (2003): 259-62. In other words, the distal portion of the lead 422 may be implanted in an area around the outer surface of the heart 418, but not attached to the heart 418. For example, the distal portion of the lead 422 may be physically isolated from the pericardium 416.

[0137] Lead 422 may include an insulated lead body having a proximal end including a connector 430 configured to connect to IMD 412 and a distal portion including one or more electrodes. Fig.18A As shown, the one or more electrodes of lead 422 can include electrodes 432A, 432B, 434A, and 434B, but in other examples, lead 422 can include more or fewer electrodes. Lead 422 also includes one or more conductors that form a conductive path within the lead body and interconnect the electrical connector to the corresponding electrodes in the electrodes.

[0138] Electrodes 432A, 432B may be defibrillation electrodes (individually or collectively, "defibrillation electrodes 432"). Although electrodes 432 may be referred to herein as "defibrillation electrodes 432", electrodes 432 may be configured to deliver other types of anti-tachyarrhythmia shocks, such as cardioversion shocks. Although for clarity, defibrillation electrodes 432 are referred to herein as "defibrillation electrodes 432". Figures 18A-18C 424. The defibrillation electrode 432 is depicted as a coil electrode, but it should be understood that the defibrillation electrode 432 can be other configurations in other examples. The defibrillation electrode 432 can be positioned on the distal portion of the lead 422, wherein the distal portion of the lead 422 is the portion of the lead 422 that is configured to be implanted outside the blood vessel below the sternum 424.

[0139] Lead 422 can be implanted at a target location beneath or along the sternum 424 so that the therapy vector substantially spans the ventricles of heart 418. In some instances, a therapy vector (e.g., a shock vector for delivering an anti-tachyarrhythmia shock) can be between defibrillation electrode 432 and a housing electrode formed by or on IMD 412. In one instance, the therapy vector can be viewed as a line extending from a point on defibrillation electrode 432 (e.g., the center of one of defibrillation electrodes 432) to a point on the housing electrode of IMD 412. As such, it can be advantageous to increase the amount of area over which defibrillation electrode 432 (and the distal portion of lead 422 therein) extends across heart 418. Thus, lead 422 can be configured to define a region such as Fig.18A In some instances, the curved distal portion of lead 22 can help improve the efficacy and / or efficiency of IMD 412 pacing, sensing, and / or defibrillation of heart 418.

[0140] Electrodes 434A, 434B may be pacing / sensing electrodes (individually or collectively, "pacing / sensing electrodes 434") positioned on a distal portion of lead 422. Electrodes 434 are referred to herein as pacing / sensing electrodes because they are generally configured for delivery of pacing pulses and / or sensing of cardiac electrical signals. In some instances, electrodes 434 may provide only pacing functionality, only sensing functionality, or both pacing functionality and sensing functionality. Fig.18A and Fig.18B In the illustrated example, the pacing / sensing electrodes 434 are separated from each other by the defibrillation electrode 432B. However, in other examples, the pacing / sensing electrodes 434 may all be distal to the defibrillation electrode 432B or all be proximal to the defibrillation electrode 432B. In examples where the lead 422 includes more or fewer electrodes 432, 434, such electrodes may be positioned at other locations on the lead 422.

[0141] exist Fig.18AIn some examples, the distal portion of lead 422 is a serpentine shape that includes two "C"-shaped curves that together can resemble the Greek letter epsilon, "epsilon". Defibrillation electrodes 432 are each carried by one of the two corresponding C-shaped portions of the distal portion of the lead body. The two C-shaped curves extend or bend in the same direction away from the central axis of the lead body. In some examples, the pacing / sensing electrode 434 can be approximately aligned with the central axis of the straight proximal portion of lead 422. In such examples, the midpoint of defibrillation electrode 432 is laterally offset from pacing / sensing electrode 434. Other examples of cardiovascular external leads that include one or more defibrillation electrodes carried by a curved, meandering, wavy, or zigzag-shaped distal portion of lead 422 and one or more pacing / sensing electrodes 434 can also be implemented using the techniques described herein. In some examples, the distal portion of lead 422 can be straight (e.g., straight or nearly straight).

[0142] Deploying the lead 422 so that the electrodes 432, 434 are at the peaks and valleys of the depicted serpentine shape can provide access to preferred sensing or therapy vectors. Orienting the serpentine shaped lead so that the pacing / sensing electrodes 434 are closer to the heart 418 can provide better electrical sensing of cardiac signals and / or lower pacing capture thresholds than if the pacing / sensing electrodes 434 were oriented farther from the heart 418. The serpentine or other shape of the distal portion of the lead 422 can increase fixation of the patient 408 because the shape provides resistance to adjacent tissue when axial force is applied. Another advantage of the shaped distal portion is that the electrodes 432, 434 can obtain a larger surface area over a shorter length of the heart 418 relative to a lead having a straighter distal portion.

[0143] In some examples, the elongated lead body of lead 422 can include one or more elongated electrical conductors (not shown) that extend within the lead body from a connector at the proximal lead end to electrodes 432, 434 positioned along a distal portion of lead 422. The one or more elongated electrical conductors included within the lead body of lead 422 can engage with corresponding ones of electrodes 432, 434. The conductors can be electrically coupled to circuitry of IMD 412, such as therapy delivery circuitry and sensing circuitry 52, through connections in the connector assembly. The electrical conductors transmit therapy from the therapy delivery circuitry to one or more of electrodes 432, 434, and transmit sensed cardiac EGMs from one or more of electrodes 432, 434 to sensing circuitry 52 within IMD 412.

[0144] In general, the IMD 412 may sense the cardiac EGM, such as by one or more sensing vectors including a combination of the pacing / sensing electrodes 434 and / or the housing electrodes of the IMD 412. In some instances, the IMD 412 may sense the EGM using sensing vectors including one of the defibrillation electrodes 432 or both defibrillation electrodes and / or one of the defibrillation electrodes 432 and one of the pacing / sensing electrodes 434 or the housing electrodes of the IMD 412. The medical system 410, including the processing circuitry of the IMD 412 and / or the external device 12, may perform any of the techniques described herein for determining whether asystole detection and pseudo asystole detection criteria are met, for example, based on the cardiac EGM sensed by the extravascular electrodes 432, 434. The cardiac EGM sensed by the extravascular electrodes may include noise, for example, due to contact with tissue and / or changes in orientation relative to the heart, in a manner similar to that described herein with respect to subcutaneous electrodes. Typically, when the electrodes are not directly fixed to the myocardium, motion such as respiratory motion can cause changes in the amplitude of depolarizations and other noise that can lead to false asystole detection. The techniques described herein can be implemented with cardiac EGMs sensed by subcutaneous electrodes, skin electrodes, substernal electrodes, extravascular electrodes, intramuscular electrodes, or any electrodes positioned in (or in contact with) any tissue of the patient.

[0145] The techniques described in the present disclosure may be implemented, at least in part, in hardware, software, firmware, or any combination thereof. For example, various aspects of these techniques may be implemented in one or more processors, DSPs, ASICs, FPGAs, or any other equivalent integrated or discrete logic QRS circuit systems, and any combination of such components, which are embodied in an external device (such as a physician or patient programmer, simulator, or other device). The terms "processor" and "processing circuit system" may generally refer to any of the aforementioned logic circuit systems, alone or in combination with other logic circuit systems, or any other equivalent circuit system, alone or in combination with other digital or analog circuit systems.

[0146] For various aspects implemented in software, at least some of the functionality attributed to the systems and devices described in this disclosure may be embodied as instructions on a computer-readable storage medium, such as RAM, DRAM, SRAM, magnetic disk, optical disk, flash memory, or various forms of EPROM or EEPROM. The instructions may be executed to support one or more aspects of the functionality described in this disclosure.

[0147] Additional project descriptions are as follows:

[0148] Item 1. A method comprising:

[0149] sensing a cardiac electrogram of the patient via a plurality of electrodes of the medical system; determining, by processing circuitry of the medical system, based on the cardiac electrogram, that an asystole detection criterion is satisfied; determining, by the processing circuitry based on the cardiac electrogram signal, that at least one false asystole detection criterion of a plurality of false asystole detection criteria is satisfied based on the determination that the asystole detection is satisfied; and

[0150] and withholding, by the processing circuitry, an indication of an asystole episode from the patient based on a determination that at least one of the plurality of asystole detection criteria is satisfied, wherein the plurality of asystole detection criteria comprises:

[0151] a first false asystole detection criterion comprising a reduced amplitude threshold for detecting cardiac depolarization in the cardiac electrogram; and

[0152] A second false asystole detection criterion is provided, wherein the second false asystole detection criterion is used to detect attenuated noise in the cardiac electrogram.

[0153] Item 2. A method according to Item 1, wherein determining that the asystole detection criteria are met includes determining that the asystole detection criteria are met based on the absence of identification of cardiac depolarization in the cardiac electrogram during a time interval.

[0154] Item 3. A method according to Item 1 or 2, wherein determining whether the first false cardiac arrest detection criterion is met includes: comparing the reduced amplitude threshold with the cardiac electrogram within the time interval; and determining based on the comparison that a threshold number of cardiac depolarizations are identified in the cardiac electrogram during the time interval.

[0155] Item 4. According to the method described in any one of the preceding items, it further includes the processing circuit system: identifying one or more cardiac depolarizations occurring in the cardiac electrogram before the time interval; determining the amplitude of each of the one or more identified cardiac depolarizations; and determining the reduced amplitude threshold based on the determined amplitude of the one or more identified cardiac depolarizations.

[0156] Item 5. A method according to Item 4, wherein the one or more identified cardiac depolarizations include a plurality of identified cardiac depolarizations, and determining the reduced amplitude threshold comprises: determining a representative amplitude based on the amplitude of each identified cardiac depolarization in the plurality of identified cardiac depolarizations; and

[0157] The reduced amplitude threshold is determined as a predetermined fraction of the representative amplitude.

[0158] Item 6. A method according to Item 1, 2, 3 or 4, wherein determining whether the second false cardiac arrest detection criterion is met includes: calculating the area under the curve value of the cardiac electrogram during at least a portion of the time interval; and determining that the area under the curve value meets the area under the curve threshold.

[0159] Item 7. The method of item 1, 2, 3, or 4, wherein determining that the second false asystole detection criterion is satisfied comprises:

[0160] Determine a difference signal of the cardiac electrogram during at least a portion of the time interval; for each sample of a plurality of samples of the difference signal, determine whether the sign of the sample is positive or negative; and determine that a quantity of samples having one of the signs satisfies a common sign threshold.

[0161] Item 8. A method according to Item 1, 2, 3 or 4, wherein the multiple false cardiac arrest detection criteria further include a third false cardiac arrest detection criterion, wherein determining whether the third false cardiac arrest detection criterion is met includes: identifying multiple cardiac depolarizations occurring in the cardiac electrogram before the time interval; determining the amplitude of each identified cardiac depolarization in the multiple identified cardiac depolarizations; determining the variability of the amplitude; and determining that the variability satisfies a variability threshold.

[0162] Item 8. A method according to Item 8, wherein the variability of the amplitude includes: determining a maximum amplitude of the multiple amplitudes; determining a representative amplitude of the multiple amplitudes; and determining a comparison measure of the maximum amplitude and the representative amplitude.

[0163] Item 9. The method of item 1, 2, 3, or 4, wherein the plurality of false asystole detection criteria further include a third false asystole detection criterion, and determining that the third false asystole detection criterion is satisfied includes:

[0164] Identify multiple cardiac depolarizations occurring in the cardiac electrogram before the time interval; determine one or more intervals between adjacent cardiac depolarizations of the multiple cardiac depolarizations; based on the determined intervals, identify one or more expected cardiac depolarization windows and one or more expected inter-depolarization windows within the time interval; determine a first energy of the one or more cardiac depolarization windows and a second energy of the one or more inter-depolarization windows; determine a comparison measure of the first energy and the second energy; and determine that the comparison measure satisfies a threshold.

[0165] Item 10. The method according to Item 1, 2, 3 or 4 further includes the processing circuit system: determining a count of instances that satisfy the cardiac arrest detection criteria within a certain time period; and determining whether the count satisfies at least one cardiac arrest counting criteria, wherein determining whether the multiple false cardiac arrest detection criteria are satisfied includes determining whether the multiple false cardiac arrest detection criteria are satisfied based on determining that the count satisfies at least one cardiac arrest counting criteria.

[0166] Item 11. A method according to Item 1, 2, 3 or 4, wherein the plurality of electrodes are implanted subcutaneously, and sensing the cardiac electrogram includes sensing the cardiac electrogram through the plurality of subcutaneously implanted electrodes.

[0167] Item 12. A method according to Item 1, 2, 3 or 4, wherein the plurality of electrodes are implanted extravascularly, and sensing the cardiac electrogram includes sensing the cardiac electrogram through the plurality of extravascularly implanted electrodes.

[0168] Item 13. A non-temporary computer-readable storage medium comprising program instructions which, when executed by a processing circuit system of a medical system, cause the processing circuit system to: determine that a cardiac arrest detection criterion is satisfied based on a cardiac electrogram sensed by a plurality of electrodes of the medical system; determine whether a plurality of false cardiac arrest detection criteria are satisfied based on the cardiac electrogram signal based on the determination that the cardiac arrest detection is satisfied; and deny an indication of a cardiac arrest episode to the patient based on a determination that at least one of the plurality of false cardiac arrest detection criteria is satisfied, wherein the plurality of false cardiac arrest detection criteria comprise: a first false cardiac arrest detection criterion comprising a reduced amplitude threshold for detecting cardiac depolarization in the cardiac electrogram; and a second false cardiac arrest detection criterion for detecting attenuated noise in the cardiac electrogram.

[0169] In addition, in some aspects, the functions described herein can be provided in dedicated hardware and / or software modules. Depicting different features as modules or units is intended to highlight different functional aspects, and does not necessarily imply that such modules or units must be implemented by separate hardware or software components. On the contrary, the functions associated with one or more modules or units can be performed by separate hardware or software components, or integrated in shared or separate hardware or software components. Moreover, the technology can be implemented completely in one or more circuits or logic elements. The technology disclosed herein can be implemented in various devices or equipment (comprising an IMD, an external programmer, a combination of an IMD and an external programmer, a collection of integrated circuits (ICs) or ICs and / or a discrete circuit system residing in an IMD and / or an external programmer).

Claims

1. A medical system, comprising: a plurality of electrodes configured to sense a cardiac electrogram of a patient; as well as processing circuitry configured to: determining based on the cardiac electrogram that asystole detection criteria are met; based on the determining that the asystole detection is satisfied, determining based on the cardiac electrogram whether a plurality of false asystole detection criteria are satisfied; and withholding an indication of an asystole episode from the patient based on a determination that at least one of the plurality of false asystole detection criteria is satisfied, The plurality of false asystole detection criteria include: a first false asystole detection criterion comprising a reduced amplitude threshold for detecting cardiac depolarization in the cardiac electrogram; as well as A second false asystole detection criterion is provided, wherein the second false asystole detection criterion is used to detect attenuated noise in the cardiac electrogram.

2. The medical system of claim 1, wherein the processing circuitry is configured to determine that the asystole detection criteria are met based on an absence of identification of cardiac depolarization in the cardiac electrogram during a time interval.

3. The medical system of claim 2, wherein to determine that the first pseudo asystole detection criterion is satisfied, the processing circuitry is configured to: comparing the reduced amplitude threshold to the electrocardiogram during the time interval; and A threshold number of cardiac depolarizations is identified in the cardiac electrogram during the time interval based on the comparing.

4. The medical system of claim 2 or 3, wherein the processing circuit system is configured to: identifying one or more cardiac depolarizations occurring in the cardiac electrogram prior to the time interval; determining an amplitude of each of the one or more identified cardiac depolarizations; and The lowered amplitude threshold is determined based on the determined amplitude of the one or more identified cardiac depolarizations.

5. The medical system of claim 4, wherein the one or more identified cardiac depolarizations comprises a plurality of identified cardiac depolarizations, and the processing circuitry is configured to: determining a representative amplitude based on the amplitude of each identified cardiac depolarization of the plurality of identified cardiac depolarizations; and The reduced amplitude threshold is determined as a predetermined fraction of the representative amplitude.

6. The medical system of claim 2 or 3, wherein to determine that the second pseudo asystole detection criterion is satisfied, the processing circuit system is configured to: calculating an area under a curve value of the electrocardiogram during at least a portion of the time interval; and It is determined that the area under the curve value satisfies an area under the curve threshold.

7. The medical system of claim 2 or 3, wherein to determine that the second pseudo asystole detection criterion is satisfied, the processing circuit system is configured to: determining a differential signal of the cardiac electrogram during at least a portion of the time interval; for each sample of the plurality of samples of the differential signal, determining whether the sign of the sample is positive or negative; and It is determined that the amount of samples having one of the symbols satisfies a common symbol threshold.

8. The medical system of claim 2 or 3, wherein the plurality of false asystole detection criteria further include a third false asystole detection criterion, wherein to determine that the third false asystole detection criterion is satisfied, the processing circuit system is configured to: identifying a plurality of cardiac depolarizations occurring in the cardiac electrogram prior to the time interval; determining an amplitude of each identified cardiac depolarization of the plurality of identified cardiac depolarizations; determining a variability of the amplitude; and It is determined that the variability satisfies a variability threshold.

9. The medical system of claim 8, wherein to determine the variability of the amplitude, the processing circuitry is configured to: determining a maximum amplitude of the plurality of amplitudes; determining a representative amplitude of the plurality of amplitudes; and A comparison metric of the maximum amplitude to the representative amplitude is determined.

10. The medical system of claim 2 or 3, wherein the plurality of false asystole detection criteria further include a third false asystole detection criterion, wherein to determine that the third false asystole detection criterion is satisfied, the processing circuit system is configured to: identifying a plurality of cardiac depolarizations occurring in the cardiac electrogram prior to the time interval; determining one or more intervals between adjacent cardiac depolarizations of the plurality of cardiac depolarizations; identifying one or more expected cardiac depolarization windows and one or more expected inter-depolarization windows within the time interval based on the determined interval; determining a first energy of the one or more cardiac depolarization windows and a second energy of the one or more inter-depolarization windows; determining a comparison metric of the first energy and the second energy; and It is determined that the comparison metric satisfies a threshold.

11. The medical system of claim 1 , wherein the processing circuitry is configured to: determining a count of instances in which the asystole detection criteria are met within a period of time; and determining whether the count satisfies at least one asystole count criterion, Wherein the processing circuit system is configured to determine whether the plurality of false asystole detection criteria are satisfied based on determining that the count satisfies at least one asystole count criterion.

12. The medical system of any of the preceding claims, wherein the plurality of electrodes are configured for subcutaneous implantation and the electrocardiogram comprises a subcutaneous electrocardiogram.

13. The medical system of any of the preceding claims, wherein the plurality of electrodes are configured for extravascular implantation and the electrocardiogram comprises an extravascular electrocardiogram.

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