Identifying false asystole detection

Abstract

The present disclosure is directed to techniques for identifying false detection of asystole in an electrocardiogram, including determining whether at least one of a plurality of false asystole detection criteria is met. In some examples, the plurality of false asystole detection criteria includes a first false asystole detection criterion including a reduced amplitude threshold for detecting cardiac depolarization in the electrocardiogram and a second false asystole detection criterion for detecting decaying noise in the electrocardiogram.

Description

[Technical field]

[0001] The present disclosure relates generally to medical systems, and more particularly to medical systems configured to detect asystole based on cardiac electrograms. [Background technology]

[0002] Some types of medical devices may monitor a patient's electrocardiogram (EGM) to monitor the electrical activity of the patient's heart. Cardiac EGMs are electrical signals sensed via electrodes. In some examples, the medical device monitors cardiac EGMs to detect one or more types of arrhythmias, such as bradycardia, tachycardia, fibrillation, or asystole (e.g., caused by sinus arrest or atrioventricular block). Summary of the Invention

[0003] Cardiac EGMs may contain noise in addition to signals representative of the electrical activity of the heart. Furthermore, the amplitude of the signals representative of the electrical activity of the heart in the cardiac EGMs may vary over time, for example, due to movement of the electrodes relative to the cardiac tissue. Noise and signal amplitude variations may confound the detection of arrhythmias, such as asystole, using cardiac EGMs.

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

[0005] In one example, the medical system includes a plurality of electrodes configured to sense a patient's electrocardiogram and a processing circuit. The processing circuit is configured to determine that an asystole detection criterion is met based on the electrocardiogram, and determine whether a plurality of false asystole detection criteria are met based on the electrocardiogram signal based on a determination that asystole detection is met. The processing circuit is further configured to withhold an indication of an asystole episode of the patient based on a determination that at least one of the plurality of false asystole detection criteria is met. 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 electrocardiogram and a second false asystole detection criterion for detecting decaying noise in the electrocardiogram.

[0006] In another example, a method includes sensing a patient's electrogram via a plurality of electrodes of a medical system and determining, by a processing circuit of the medical system, that asystole detection criteria are met based on the electrogram. The method further includes determining, by the processing circuit, that at least one of a plurality of false asystole detection criteria are met based on the electrogram signal based on the determination that asystole detection is met, and withholding an indication of an asystole episode in the patient based on the determination, by the processing circuit, that at least one of the plurality of false asystole detection criteria is met. 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 electrogram and a second false asystole detection criterion for detecting decaying noise in the electrogram.

[0007] In another example, a non-transitory computer-readable storage medium comprises program instructions that, when executed by a processing circuit of a medical system, cause the processing circuit to determine that asystole detection criteria are met based on electrograms sensed via a plurality of electrodes of the medical system. Based on a determination that asystole detection is met, the program instructions cause the processing circuit to determine whether a plurality of false asystole detection criteria are met based on the electrogram signals and to withhold an indication of an asystole episode in the patient based on a determination that at least one of the plurality of false asystole detection criteria is met. 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 electrogram and a second false asystole detection criterion for detecting decaying noise in the electrogram.

[0008] This summary is intended to provide an overview of the subject matter described in the present disclosure. It is not intended to provide an exclusive or comprehensive description of the systems, devices, and methods described in detail in the accompanying drawings and the following description. Further details of one or more examples of the present disclosure are set forth in the accompanying drawings and the following description. Other features, objects, and advantages will be apparent from the description and drawings, and from the claims. [Brief description of the drawings]

[0009] [Figure 1] 1 illustrates an exemplary healthcare system environment in collaboration with a patient. [Diagram 2] 2 is a functional block diagram illustrating an exemplary configuration of an implantable medical device (IMD) of the medical system of FIG. 1. [Diagram 3] FIG. 3 is a conceptual side view illustrating an example configuration of the IMD of FIGS. 1 and 2. [Figure 4] 2 is a functional block diagram illustrating an example configuration of the external device of FIG. 1. [Diagram 5]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 may be coupled to the IMD and external devices of Figures 1-4. [Figure 6] 1 is a flow diagram illustrating example operations for determining whether an identification of an asystole episode is false based on whether a number of false asystole detection criteria are met. [Figure 7] 11 is a graph illustrating cardiac EGMs associated with an identified asystole episode and an exemplary technique for determining whether exemplary false asystole detection criteria are met based on the cardiac EGMs. [Figure 8] 1 is a flow diagram illustrating example operations for determining whether example false asystole criteria including a reduced amplitude threshold for depolarization detection are met. [Figure 9] Graph showing cardiac EGM with decaying noise. [Figure 10] 1 is a graph illustrating a cardiac EGM including decaying noise and an exemplary technique for determining whether exemplary false asystole detection criteria are met based on the cardiac EGM. [Figure 11] 11 is a flow diagram illustrating example operations for determining whether example false asystole criteria for detecting decaying noise are met. [Figure 12] 1 is a graph illustrating a differential signal of a cardiac EGM including attenuating noise and an exemplary technique for determining whether exemplary false asystole detection criteria are met based on the cardiac EGM. [Figure 13] 11 is a flow diagram illustrating another exemplary operation for determining whether exemplary false asystole criteria for detecting decaying noise are met. [Figure 14] 11 is a graph illustrating cardiac EGMs associated with an identified asystole episode and an exemplary technique for determining whether another exemplary false asystole detection criterion is met based on the cardiac EGMs. [Figure 15]11 is a flow diagram illustrating another exemplary operation for determining whether exemplary false asystole criteria are met. [Figure 16] 11 is a graph illustrating cardiac EGMs associated with an identified asystole episode and an exemplary technique for determining whether another exemplary false asystole detection criterion is met based on the cardiac EGMs. [Figure 17] 11 is a flow diagram illustrating another exemplary operation for determining whether exemplary false asystole criteria are met. [Figure 18A] FIG. 1 is a conceptual diagram illustrating a front view of a patient using another exemplary medical system. [Figure 18B] FIG. 18B is a conceptual diagram illustrating a side view of a patient using the exemplary medical system of FIG. 18A. [Figure 18C] FIG. 18B is a schematic diagram illustrating a cross-sectional view of a patient using the exemplary medical system of FIG. 18A. Like reference characters refer to like elements throughout the description and figures. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Various types of medical devices sense cardiac EGMs. Some medical devices that sense cardiac EGMs are non-invasive, using multiple electrodes placed in contact with an external portion of the patient, such as at various locations on the patient's skin. The electrodes used to monitor cardiac EGMs in these non-invasive processes may be attached to the patient, for example, using adhesives, straps, belts, or vests, and electrically coupled to a monitoring device, such as an electrocardiograph, 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 the electronic device for further processing and / or display of the electrical signals. Non-invasive devices and methods may be utilized to monitor a patient temporarily, for example, during a clinical visit, such as during a doctor's appointment, or for a predetermined period of time, such as for a day (24 hours) or for several days.

[0011] External devices that can be used to non-invasively sense and monitor cardiac EGMs include wearable devices with electrodes configured to contact the patient's skin, such as patches, watches, necklaces, etc. One example of a wearable physiological monitor configured to sense cardiac EGMs is the SEEQ™ Mobile Cardiac Telemetry System available from Medtronic plc, Dublin, Ireland. Such external devices may facilitate relatively long-term monitoring of a patient during normal daily activities and may periodically transmit collected data to a network service, such as the Medtronic Carelink™ network.

[0012] Implantable medical devices (IMDs) also sense and monitor cardiac EGMs. Electrodes used by the 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. Examples of IMDs that monitor cardiac EGMs include pacemakers and implantable cardiac defibrillators, which may be coupled to intravascular or extravascular leads, as well as pacemakers with housings configured for implantation within the heart, which may be leadless. An example of a pacemaker configured for intracardiac implantation is the Micra™ transcatheter pacing system available from Medtronic plc. Some IMDs that do not provide therapy, such as implantable patient monitors, sense cardiac EGMs. One example of such an IMD is the Reveal LINQ™ insertable cardiac monitor, available from Medtronic plc, which can be inserted subcutaneously. Such IMDs may facilitate relatively long-term monitoring of a patient during normal daily activities and may periodically transmit collected data to a network service, such as the Medtronic Carelink™ network.

[0013] Regardless of which type or types of devices are used, noise signals, sometimes referred to as artifacts, may appear in the cardiac EGM. The duration of the noise signal may span a portion of the normal time frame of a cardiac cycle of the heart, or may span a time span in which multiple cardiac cycles may be expected to have occurred. Such noise signals may be more prevalent when sensing cardiac EGMs using cutaneous, subcutaneous, or extravascular electrodes, for example, because contact between at least one of the electrodes and the tissue in which the electrode is located temporarily changes due to relative motion between the electrode and the tissue. In some instances, the noise signal may appear as a baseline drift in the cardiac EGM, including a portion that decays toward a steady-state baseline.

[0014] The presence of a noise signal in a sensed cardiac EGM may cause a circuit for detecting a depolarization, e.g., an R-wave, to erroneously detect the noise signal as a depolarization. The noise signal may then cause the circuit to fail to sense some subsequent depolarizations because the noise signal may be much larger in amplitude than subsequent depolarizations, and in some cases, high amplitude noise may cause an adjustable sensing threshold used by the circuit to be adjusted to a level larger than the amplitude of the true depolarization. Furthermore, the amplitude of the cardiac signal, e.g., a depolarization, in the sensed cardiac EGM may vary over time, e.g., due to respiration. Such cardiac signal amplitude variations may also be more common in cardiac EGMs sensed using cutaneous, subcutaneous, or extravascular electrodes. Variations in cardiac signal amplitude may also cause a depolarization to temporarily fall below the sensing threshold, resulting in the depolarization not being detected.

[0015] Inappropriate sensing of these types of depolarizations can lead to inappropriate analysis of actual cardiac activity occurring with respect to the patient being monitored. For example, inappropriate sensing of these types of depolarizations can potentially cause false positive indications of cardiac events that did not actually occur with the patient, such as asystole. Such false positive indications can lead to erroneous assessments of the patient's condition, including delivery of therapy and / or transmission of erroneous alerts to medical personnel responsible for the care of the monitored patient. Low-pass filtering of cardiac EGMs generally does not help to solve these problems, as these types of noise signals and amplitude fluctuations can occur at frequencies close to or even lower than the frequency of the cardiac signal.

[0016] A medical system according to the present disclosure implements techniques for identifying false detection of asystole in a cardiac EGM, for example, by detecting the presence of noise signals and amplitude variations in the cardiac signal. In some examples, the processing circuitry of the system 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 may be configured to detect one or more indicators of noise and / or amplitude variations in the cardiac EGM.

[0017] In some examples, the processing circuitry of the medical system may perform this analysis in response to the asystole detection criteria being met and, based on the analysis, determine whether to provide or withhold an indication that the patient has experienced asystole (e.g., to a clinician or other user). The processing circuitry may perform the techniques of the present disclosure substantially in real time in response to the detection of asystole or during a subsequent review of the cardiac EGM data for an episode identified as asystole. In either case, the processing circuitry may include the processing circuitry of the medical device that detected the asystole episode and / or the processing circuitry of another device, such as a local or remote computing device, that retrieved the episode data from the medical device. In this manner, the techniques of the present disclosure may improve accuracy in identifying true asystole, thereby advantageously enabling a better assessment of the patient's condition.

[0018] Figure 1 shows an environment of an exemplary medical system 2 in cooperation with a patient 4 according to one or more techniques of the present disclosure. The exemplary techniques can be used with an IMD 10 that can wirelessly communicate with at least one of an external device 12 and other devices not shown in Figure 1. In some examples, the IMD 10 is implanted outside the patient's chest (e.g., subcutaneously at the chest location shown in Figure 1). The IMD 10 can be positioned near or just below the level of the patient's heart, near the sternum, for example, at least partially within the silhouette of the heart. The IMD 10 includes a plurality of electrodes (not shown in Figure 1) and is configured to sense cardiac EGM via the plurality of electrodes. In some examples, the IMD 10 takes the form of a LINQ (trademark) ICM.

[0019] The external device 12 can be a computing device having a display viewable by a user and an interface (i.e., a user input mechanism) for providing input to the external device 12. In some examples, the external device 12 can be a notebook computer, a tablet computer, a workstation, one or more servers, a mobile phone, a personal digital assistant, or another computing device capable of running an application that enables the computing device to interact with the IMD 10.

[0020] The external device 12 is configured to communicate via wireless communication with the IMD 10 and optionally with another computing device (not shown in Figure 1). The external device 12 can communicate, for example, via short-range communication techniques (e.g., inductive coupling, NFC, or other communication techniques operable in a range less than 10 - 20 cm) and long-range communication techniques (e.g., wireless frequency (RF) telemetry using 802.11 or Bluetooth (registered trademark) specifications, or other communication techniques operable over a wider range than short-range communication techniques).

[0021] The external device 12 may be used to configure the operating parameters of the IMD 10. The external device 12 may be used to retrieve data from the IMD 10. The retrieved data may include values ​​of physiological parameters measured by the IMD 10, indications of arrhythmias or other disease episodes detected by the IMD 10, and physiological signals recorded by the IMD 10. For example, the external device 12 may retrieve cardiac EGM segments recorded by the IMD 10 for the IMD 10 to determine that asystole or another disease episode occurred during the segment. As discussed in more detail below with respect to FIG. 5, one or more remote computing devices may interact with the IMD 10 in a manner similar to the external device 12, e.g., over a network, to program the IMD 10 and / or retrieve data from the IMD 10.

[0022] Processing circuitry of the medical system 2, e.g., the IMD 10, the external device 12, and / or one or more other computing devices, may be configured to execute the exemplary techniques for identifying false detection of asystole of the present disclosure. In some examples, the processing circuitry of the medical system 2 analyzes the cardiac EGMs sensed by the IMD 10 and associated with the 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 variation in the cardiac EGMs. Although described in the context of an example in which the IMD 10 sensing the cardiac EGMs comprises an insertable cardiac monitor, an exemplary system including any type of one or more implantable or external devices configured to sense the cardiac EGMs may be configured to implement the techniques of the present disclosure.

[0023] Figure 2 is a functional block diagram illustrating an example configuration of the IMD 10 of Figure 1 in accordance with one or more of the techniques described herein. In the illustrated example, the IMD 10 includes electrodes 16A and 16B (collectively "electrodes 16"), an antenna 26, a processing circuit 50, a sensing circuit 52, a communication circuit 54, a storage device 56, a switching circuit 58, and a sensor 62. Although the illustrated example includes two electrodes 16, in some examples, an IMD that includes or is coupled to three or more electrodes 16 can implement the techniques of this disclosure.

[0024] The processing circuitry 50 may include fixed function circuits and / or programmable processing circuits. The processing circuitry 50 may include any one or more of a microprocessor, a controller, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or equivalent discrete or analog logic circuitry. In some examples, the processing circuitry 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 circuits. The functionality attributed to the processing circuitry 50 herein may be embodied as software, firmware, hardware, or any combination thereof.

[0025] Sensing circuit 52 may be selectively coupled to electrodes 16 via switching circuit 58 to select the electrodes 16 and polarity, referred to as a sensing vector, used to sense cardiac EGMs, as controlled by processing circuit 50, for example. Sensing circuit 52 may sense signals from electrodes 16 to generate, for example, cardiac EGMs, to facilitate monitoring of cardiac electrical activity. Sensing circuit 52 may also monitor signals from sensors 62, which may include, by way of example, one or more accelerometers, pressure sensors, and / or optical sensors. In some examples, sensing circuit 52 may include one or more filters and amplifiers for filtering and amplifying signals received from electrodes 16 and / or sensors 62.

[0026] The sensing circuit 52 and / or the processing circuit 50 may be configured to detect a cardiac depolarization (e.g., a P-wave or an R-wave) when the cardiac EGM amplitude exceeds a sensing threshold. In some examples, the sensing threshold is automatically adjustable over time using any of a variety of automatic sensing threshold adjustment techniques known in the art. For example, in response to detecting a cardiac depolarization, the sensing threshold for detecting a subsequent cardiac depolarization may decay from an initial value over a period of time. The sensing circuit 52 and / or the processing circuit 50 may determine the initial value based on the amplitude of the detected cardiac depolarization. The initial value and decay of the adjustable sensing threshold may be configured such that the sensing threshold is relatively higher immediately after a detected cardiac depolarization when no subsequent depolarization is expected, and decays to a relatively lower value over time as the occurrence of a cardiac depolarization becomes more likely. For cardiac depolarization detection, the sensing circuit 52 may include a rectifier, a filter, an amplifier, a comparator, and / or an analog-to-digital converter in some examples.

[0027] In some examples, sensing circuitry 52 may output an indication to processing circuitry 50 in response to sensing a cardiac depolarization. In this manner, processing circuitry 50 may receive detected cardiac depolarization indicators corresponding to the occurrence of detected R-waves and P-waves in the respective heart chambers. Processing circuitry 50 may use the indications of detected R-waves and P-waves to determine heart rate and detect arrhythmias, such as tachyarrhythmia and asystole.

[0028] Processing circuitry 50 may detect an asystole episode based on determining that the cardiac electrogram meets an asystole detection criterion. The asystole detection criterion may be the absence of a cardiac depolarization for a threshold period of time. In such an example, processing circuitry 50 may determine that the cardiac EGM meets the asystole detection criterion based on reaching a predetermined time interval from the detection of a cardiac depolarization without receiving another cardiac depolarization indication from sensing circuitry 52.

[0029] The sensing circuit 52 may also provide one or more digitized cardiac EGM signals to the processing circuit 50 for analysis, e.g., for use in cardiac rhythm discrimination and / or for analysis to determine whether one or more false asystole detection criteria have been met in accordance with the techniques of the present disclosure. In some examples, based on the satisfaction of the asystole detection criteria, the processing circuit 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 over a period during which the sensing circuit 52 did not indicate a detection of a depolarization, as well as a period before and / or after this period during which a depolarization was detected. The processing circuit 50 of the IMD 10, and / or a processing circuit of another device that retrieves the episode data from the IMD 10, may analyze the cardiac EGM segment to determine whether one or more false asystole detection criteria have been met in accordance with the techniques of the present disclosure.

[0030] The communication circuitry 54 may include any suitable hardware, firmware, software, or any combination thereof for communicating with the external device 12, another networked computing device, or another device, such as another IMD or sensor. Under the control of the processing circuitry 50, the communication circuitry 54 may receive downlink telemetry from, and transmit uplink telemetry to, the external device 12 or another device with the aid of an internal or external antenna, e.g., the antenna 26. Additionally, the processing circuitry 50 may communicate with an external device (e.g., the external device 12) and a networked computing device via a computer network, such as the Medtronic CareLink® network. The antenna 26 and the communication circuitry 54 may 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 methods.

[0031] In some examples, the storage device 56 includes computer-readable instructions that, when executed by the processing circuitry 50, cause the IMD 10 and the processing circuitry 50 to perform various functions attributed to the IMD 10 and the processing circuitry 50 herein. The storage device 56 may include any volatile, non-volatile, magnetic, optical, or electrical medium, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), electrically erasable programmable ROM (EEPROM), flash memory, or any other digital medium. The storage device 56 may store, by way of example, programmed values ​​of one or more operating parameters of the IMD 10 and / or data collected by the IMD 10 for transmission to another device using the communication circuitry 54. The data stored by the storage device 56 and transmitted by the communication circuitry 54 to one or more other devices may include suspected asystole episode data and / or an indication that the suspected asystole met one or more false asystole detection criteria.

[0032] FIG. 3 is a conceptual side view illustrating an example configuration of the IMD 10 of FIGS. 1 and 2. In the example shown in FIG. 3, the IMD 10 may include a leadless subcutaneously implantable monitoring device having a housing 15 and an insulating cover 76. The electrodes 16A and 16B may be formed or disposed on an exterior surface of the cover 76. The circuitry 50-62 described above with respect to FIG. 2 may be formed or disposed on an interior surface of the cover 76 or within the housing 15. In the illustrated example, the antenna 26 is formed or disposed on an interior surface of the cover 76, but in some examples, it may be formed or disposed on an exterior surface. In some examples, the insulating cover 76 may be positioned over the open housing 15 such that the housing 15 and cover 76 enclose the antenna 26 and the circuitry 50-62 and protect the antenna and the circuitry from fluids, such as bodily fluids.

[0033] The antenna 26 or one or more of the circuits 50-62 may be formed on the inside of the insulating cover 76, such as by using flip chip technology. The insulating cover 76 may be flipped over the housing 15. Once flipped over and placed on the housing 15, the components of the IMD 10 formed on the inside of the insulating cover 76 may be positioned within the gap 78 defined by the housing 15. The electrodes 16 may be electrically connected to the switching circuitry 58 through one or more vias (not shown) formed through the insulating cover 76. The insulating cover 76 may be formed of sapphire (i.e., corundum), glass, parylene, and / or any other suitable insulating material. The housing 15 may be formed of titanium or any other suitable material (e.g., a biocompatible material). The electrodes 16 may be formed of any of stainless steel, titanium, platinum, iridium, or alloys thereof. Additionally, the electrodes 16 may be coated with a material such as titanium nitride or fractal titanium nitride, although other suitable materials and coatings may be used for such electrodes.

[0034] 4 is a block diagram illustrating an exemplary configuration of components of external device 12. In the example of FIG. 4, external device 12 includes processing circuitry 80, communication circuitry 82, a storage device 84, and a user interface 86.

[0035] Processing circuitry 80 may include one or more processors configured to implement functions and / or process instructions for execution within external device 12. For example, processing circuitry 80 may be capable of processing instructions stored in storage device 84. Processing circuitry 80 may include, for example, a microprocessor, a DSP, an ASIC, an FPGA, or equivalent discrete or integrated logic circuitry, or a combination of any of the foregoing devices or circuits. Thus, processing circuitry 80 may include any suitable structure for performing the functions attributed to processing circuitry 80 herein, whether hardware, software, firmware, or any combination thereof.

[0036] The communications circuitry 82 may include any suitable hardware, firmware, software, or any combination thereof for communicating with another device, such as the IMD 10. Under the control of the processing circuitry 80, the communications circuitry 82 may receive downlink telemetry from, as well as transmit uplink telemetry to, the IMD 10 or another device. The communications circuitry 82 may be configured to transmit or receive signals via inductive coupling, electromagnetic coupling, NFC, RF communications, Bluetooth, WiFi, or other proprietary or non-proprietary wireless communications methods. The communications circuitry 82 may also be configured to communicate with devices other than the IMD 10 via any of a variety of forms of wired and / or wireless communications and / or network protocols.

[0037] 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 examples, the storage device 84 includes one or more of short-term memory or long-term memory. The storage device 84 may include, for example, a form of RAM, DRAM, SRAM, magnetic disk, optical disk, flash memory, or EPROM or EEPROM. In some examples, the storage device 84 is used to store data indicative of instructions for execution by the processing circuitry 80. The storage device 84 may be used by software or applications executing on the external device 12 to temporarily store information during program execution.

[0038] 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 modify one or more operating parameters and / or export collected data. For example, the processing circuitry 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. The external device 12 may then receive the collected data from the IMD 10 and store the collected data in the storage device 84. The processing circuitry 80 may implement any of the techniques described herein to analyze the cardiac EGMs received from the IMD 10, for example, to determine whether asystole and false asystole criteria are met.

[0039] 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 light emitting diode (LED) display or other type of screen, with which the processing circuitry 80 can present information related to the IMD 10, such as cardiac EGMs, an indication of detection of an arrhythmia episode, and an indication of a determination that one or more false asystole detection criteria have been met. Additionally, the user interface 86 can include an input mechanism configured to receive input from a user. The input mechanism can include, for example, any one or more of a button, a keypad (e.g., an alphanumeric keypad), a peripheral pointing device, a touch screen, or another input mechanism that allows a user to navigate a user interface presented by the processing circuitry 80 of the external device 12 and provide input. In other examples, the user interface 86 also includes audio circuitry for providing audible notifications, instructions, or other sounds to the user, receiving voice commands from the user, or both.

[0040] 5 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 device 100") that may be coupled to an IMD 10 and an external device 12 via a network 92 in accordance with one or more techniques described herein. In this example, the IMD 10 may use communications circuitry 54 to communicate with the external device 12 via a first wireless connection and with the access point 90 via a second wireless connection. In the example of FIG. 5, the access point 90, the external device 12, the server 94, and the computing device 100 are interconnected and may communicate with each other via the network 92.

[0041] The access point 90 may include a device that connects to the network 92 via any of a variety of connections, such as a telephone dial-up, digital subscriber line (DSL), or cable modem connection. In other examples, the access point 90 may be coupled to the network 92 via a different form of connection, including a wired or wireless connection. In some examples, the access point 90 may be a user device, such as a tablet or smartphone, that may be co-located with the patient. The IMD 10 may be configured to transmit data to the access point 90, such as asystole episode data and an indication that one or more false asystole detection criteria have been met. The access point 90 may then communicate the retrieved data over the network 92 to a server 94.

[0042] In some cases, server 94 may be configured to provide a secure storage site for data collected from IMD 10 and / or external device 12. In some cases, server 94 may assemble the data in a web page or other document for viewing by a trained professional, such as a clinician, via computing device 100. One or more aspects of the illustrated system of FIG. 5 may be implemented using common network technologies and capabilities that may be similar to those provided by the Medtronic CareLink® network.

[0043] In some examples, one or more of the computing devices 100 may be a tablet or other smart device located with a clinician, allowing the clinician to program, receive alerts from, and / or interrogate the IMD 10. For example, the clinician may access data collected by the IMD 10 via the computing device 100 to check the status of a medical condition, such as when the patient 4 is between clinical visits. In some examples, the clinician may enter instructions for a medical intervention for the patient 4 into an application executed by the computing device 100, such as based on the patient's health status determined by the IMD 10, the external device 12, the server 94, or any combination thereof, or based on other patient data known to the clinician. The device 100 may then transmit the instructions for the medical intervention to another computing device 100 located with the patient 4 or a caregiver of the patient 4. For example, such instructions for medical intervention may include instructions to change the dosage, timing, or selection of a medication, instructions to schedule a consultation with a clinician, or instructions to seek medical treatment. In a further example, 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 a prescription for medical intervention. In this manner, patient 4 is empowered to take action to address their medical condition, if necessary, which may help improve clinical outcomes for patient 4.

[0044] In the example shown in FIG. 5, server 94 includes, for example, a storage device 96 for storing data retrieved from IMD 10, and a processing circuit 98. Although not shown in FIG. 5, computing device 100 may similarly include a storage device and a processing circuit. Processing circuit 98 may include one or more processors configured to implement functions and / or process instructions for execution within server 94. For example, processing circuit 98 may be capable of processing instructions stored in storage device 96. Processing circuit 98 may include, for example, a microprocessor, a DSP, an ASIC, an FPGA, or equivalent discrete or integrated logic circuitry, or any combination of the foregoing devices or circuits. Thus, processing circuit 98 may include any suitable structure for performing the functions attributed to processing circuit 98 herein, whether hardware, software, firmware, or any combination thereof. The processing circuit 98 of server 94, and / or the processing circuit of computing device 100, can implement any of the techniques described herein to analyze the cardiac EGM received from IMD 10, for example, to determine whether cardiac arrest and false cardiac arrest criteria are met.

[0045] 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 the form of EPROM or EEPROM. In some examples, storage device 96 is used to store data indicative of instructions for execution by processing circuit 98.

[0046] 6 is a flow diagram illustrating example operations for determining whether an identification of an asystole episode is false based on whether a number of false asystole detection criteria are met. According to the illustrated example of FIG. 6, processing circuitry 50 of IMD 10 determines (120) that at least one asystole detection criterion is met based on cardiac EGMs sensed by sensing circuitry 52 of IMD 10. For example, as discussed in more detail with respect to FIG. 2, processing circuitry 50 may determine that a threshold time interval, e.g., 2-3 seconds, has elapsed since sensing circuitry 52 identified a cardiac depolarization, e.g., an R-wave, in the cardiac EGM.

[0047] Based on determining that the asystole detection criteria are met, the processing circuit 50 determines whether one or more of a plurality of false asystole detection criteria are met. In the illustrated example, the processing circuit 50 determines whether the false asystole detection criteria are met (122), including an asystole detection count criterion. For example, the processing circuit 50 may determine whether the asystole detection criteria have been met at least a threshold number of times within a predetermined time period dating back to the most recent fulfillment of the asystole detection criteria, e.g., at least twice within the past 30 days. As another example, the processing circuit may determine whether the asystole detection criteria have been met at a threshold rate over a period of time, e.g., at a rate of one asystole per 30 days. The period of time may be the total time the IMD 10 has been active from implantation or from a period of time other than implantation, e.g., a certain number of days, weeks, or months after implantation, or from a period of time beginning upon a power-on or other reset of the IMD 10.

[0048] Based on determining that the asystole detection count criterion is not met (NO at 122), the example operation of FIG. 6 ends (124). Based on determining that the asystole detection count criterion is met (YES at 122), the processing circuit 50 proceeds to determine whether one or more of the other false asystole detection criteria are met. The implementation of such an asystole detection count criterion is based on the observation that false asystole detection is more likely to occur in devices that detect asystole frequently and less likely to occur in devices that detect asystole infrequently. By requiring the asystole detection count criterion to be met before applying other false asystole detection criteria, as in the example operation of FIG. 6, false asystole detection criteria may avoid erroneously classifying a suspected asystole as false.

[0049] Noise signals may occur in the cardiac EGMs intermittently or with varying frequency, for example, based on changes in the IMD 10 or the condition of the patient 4. As a result, during periods when asystole detection is more frequent (indicating that there may be noise in the EGM) than during periods when asystole detection is less frequent, it may be more likely that a given asystole detection is false (e.g., caused by noise). By implementing asystole detection count criteria to selectively activate and deactivate evaluation of the cardiac EGMs for suspected asystole episodes using the false asystole detection criteria described herein, one can achieve different emphasis on the sensitivity versus specificity of asystole detection depending on the recent frequency of asystole and, therefore, the likelihood that the most recent asystole episode is false.

[0050] During periods when the frequency of asystole is below the threshold and thus the asystole count criterion is not met, the processing circuit 50 may use the false asystole detection criterion to not activate the evaluation of the cardiac EGMs for suspected asystole episodes, thereby maintaining the sensitivity of asystole detection. During periods when the frequency of asystole is above the threshold and thus the asystole count criterion is not met, the processing circuit 50 may use the false asystole detection criterion to activate the evaluation of the cardiac EGMs for suspected asystole episodes, thereby improving the specificity of asystole detection. Thus, by selectively (e.g., intermittently) activating and deactivating the evaluation of the cardiac EGMs for suspected asystole episodes using the false asystole detection criterion, a desired balance between sensitivity and specificity may be provided for the current state of the cardiac EGMs, e.g., the degree of noise in the cardiac EGMs.

[0051] In the illustrated example, based on a determination that the asystole detection count criterion is met (YES at 122), processing circuitry 50 proceeds to determine whether a threshold number of depolarizations are detected using a reduced amplitude threshold within a time interval of the cardiac EGM in which no depolarizations were detected using the asystole detection criterion amplitude threshold (126). Based on the depolarizations at the reduced amplitude threshold criterion being met (YES at 126), processing circuitry 50 may determine that the suspected asystole episode is false asystole (128). Based on the depolarizations at the reduced amplitude threshold criterion not being met (NO at 126), processing circuitry 50 may proceed to consider another false asystole detection criterion.

[0052] In the illustrated example, based on a determination that the depolarization at reduced amplitude threshold criterion is not met (NO at 126), processing circuitry 50 proceeds to determine whether the cardiac EGM associated with the met asystole detection criterion also meets the decaying noise criterion (130). Based on the decaying noise criterion being met (YES at 130), processing circuitry 50 may determine that the suspected asystole episode is false asystole (128). Based on the decaying noise criterion not being met (NO at 130), processing circuitry 50 may proceed to consider another false asystole detection criterion.

[0053] In the illustrated example, based on a determination that the decaying noise criterion is not met (NO at 130), processing circuitry 50 proceeds to determine whether the cardiac EGM associated with the suspected asystole episode meets the preceding depolarization variability criterion (132). Based on the preceding depolarization variability criterion being met (YES at 132), processing circuitry 50 may determine that the suspected asystole episode is false asystole (128). Based on the preceding depolarization variability criterion not being met (NO at 132), processing circuitry 50 may proceed to consider another false asystole detection criterion.

[0054] In the illustrated example, based on a determination that the preceding depolarization variability criteria have not been met (NO at 132), processing circuitry 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 at 134), processing circuitry 50 may determine that the suspected asystole episode is a false asystole (128). Based on the energy criteria not being met (NO at 134), the example operation of FIG. 6 ends (124).

[0055] 6 due to, for example, none of the false asystole detection criteria being met or an insufficient number or combination of false asystole detection criteria being met (124), processing circuitry 50 may classify the suspected asystole episode as a true asystole episode. Based on the asystole episode being classified as true, processing circuitry 50 may use the asystole episode in further operations, such as computing statistics, determining a patient's status, or transmitting true episode data to other devices. Based on determining that the suspected asystole episode is false asystole (128), processing circuitry 50 may use the false asystole episode in further operations, such as computing false episode statistics and transmitting false episode data to other devices, for example, for a user to consider changing the operation of IMD 10 to avoid further false asystole detections.

[0056] The order and flow of operations shown in FIG. 6 is an example. In other examples according to the present disclosure, more or fewer false asystole detection criteria may be considered, the false asystole detection criteria may be considered in a different order, or a different number or combination of false asystole detection criteria may be required for a determination that a suspected asystole episode was false. Furthermore, in some examples, the processing circuitry may or may not perform the method of FIG. 6 or any of the techniques described herein, as instructed by a user, e.g., via the external device 12 or the computing device 100. For example, a patient, clinician, or other user may 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 mobile phone or using a medical device programmer).

[0057] Additionally, although described in the context of an example in which the IMD 10 and the processing circuitry 50 of the IMD 10 perform each of the exemplary portions of the operations, the exemplary operations of FIG. 6, as well as the exemplary operations described herein with respect to FIGS. 7-17, may be performed by any combination of one or more of the processing circuitry of any one or more devices of the medical system, e.g., the processing circuitry 50 of the IMD 10, the processing circuitry 80 of the external device 12, the processing circuitry 98 of the server 94, or the processing circuitry of the computing device 100. In some examples, the processing circuitry 50 of the IMD 10 may determine whether asystole detection criteria are met and provide episode data of the suspected asystole episode to another device. In such examples, the processing circuitry of the other device, e.g., the external device 12, the server 94, or the processing circuitry of the computing device 100, may apply one or more false asystole detection criteria to the episode data.

[0058] 7 is a graph illustrating a cardiac EGM 148 associated with an identified episode suspected to be asystole, and an example technique for determining whether example false asystole detection criteria are met based on the cardiac EGM 148. In some examples, the cardiac EGM 148 is a digitized segment of a cardiac EGM sensed by sensing circuitry 52 of the IMD 10 via electrodes 16, and corresponds to a suspected asystole episode identified by processing circuitry 50 which applies one or more asystole detection criteria to the cardiac EGM.

[0059] FIG. 7 illustrates cardiac depolarizations 150A-150H (R-waves in this example) identified by IMD 10, for example, by comparing cardiac EGM 148 to an amplitude threshold that may be automatically adjustable as described herein. FIG. 7 also illustrates asystole interval 152. Asystole interval 152 represents the time interval between adjacent depolarizations 150F and 150G identified by IMD 10. As described herein, processing circuit 50 may have determined that asystole detection criteria are met when asystole interval 152 reaches a predetermined threshold amount of time. Based on the satisfaction of asystole detection criteria, processing circuit 50 may store cardiac EGM 148, including the period before and after asystole interval 152, and an indication of the detection (e.g., timing) of depolarizations 150A-150H in storage device 52.

[0060] As discussed with reference to item 126 of FIGURE 6, one false asystole detection criterion may include determining whether a threshold number of depolarizations are detected in cardiac EGM 148 during asystole interval 152 using a reduced amplitude threshold 154. In the example shown in FIGURE 7, processing circuit 50 detects depolarizations 150I-150K during interval 152 by comparing cardiac EGM 148 to reduced amplitude threshold 154. The threshold number of depolarizations detected during interval 152 using threshold 154 required to meet the reduced amplitude threshold criterion may be any integer number equal to or greater than one, including two or three detected depolarizations.

[0061] In some examples, processing circuitry 50 determines reduced amplitude threshold 154 based on the amplitude of a predetermined number of depolarizations 150A-150F preceding asystole interval 152. In some examples, processing circuitry 50 determines the amplitude of depolarizations 150A-150F by determining the amplitude of cardiac EGM 148 at samples corresponding to zero crossings of the differential signal of cardiac EGM 148. In some examples, processing circuitry 50 determines a representative value of the amplitude of depolarizations 150A-150F, e.g., a median or average amplitude, and determines reduced amplitude threshold 154 to be a predetermined portion, e.g., a fraction or percentage, of the representative amplitude. By way of example, the predetermined portion may be 1 / 10, 1 / 8, 1 / 5, 1 / 3, or 1 / 2. In some examples, any number of preceding depolarizations may be used to determine threshold 154, such as two to eight preceding depolarizations, including six preceding depolarizations.

[0062] In one example, if the median amplitude of the six preceding R-waves is 80 microvolts (μV), then the reduced amplitude threshold 154 of 1 / 8 the median amplitude would be 10 μV. In such an example, the processing circuit 50 would determine that the false asystole detection criterion has been met if a 15 μV signal is present in the cardiac EGM 148 during the interval 152. Applying the reduced amplitude threshold 154 during the asystole interval 152 may also obscure an atrioventricular block having a 15 μV P-wave. However, applying this false asystole detection criterion based on the satisfaction of the asystole detection count criterion (122 in FIG. 6 ) and the low probability that this false asystole detection criterion will be met by a cardiac EGM having a relatively high R-wave amplitude reduces the likelihood of misclassification of an episode.

[0063] Figure 8 is a flow diagram illustrating example operations for determining whether example false asystole criteria are met including a reduced amplitude threshold for depolarization detection, e.g., corresponding to item 126 of Figure 6. The example operations of Figure 8 will be described with reference to the cardiac EGM 148 and other data shown in Figure 7.

[0064] 8, processing circuitry 50 of IMD 10 identifies (160) a predetermined number "N" of depolarizations 150 that precede an asystole interval 152, e.g., the most recent N depolarizations prior to the asystole interval. Processing circuitry 50 determines (162) the amplitudes of the N preceding depolarizations 150. Processing circuitry 50 determines (164) a reduced amplitude threshold 154 based on the amplitudes of the N preceding depolarizations 150, e.g., based on a predetermined fraction or other portion of a median or other representative value of the determined amplitudes of the N preceding depolarizations 150.

[0065] The processing circuit 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 50 determines whether a threshold number of depolarizations 150 are identified within the asystole interval 152 based on the comparison, e.g., based on the cardiac EGM 148 being equal to or greater than the reduced amplitude threshold 154 within the asystole interval (168). By way of example, the threshold number of depolarizations may be one, two, or three depolarizations. Based on detecting the threshold number of depolarizations (yes at 168), the processing circuit 50 may determine that the suspected asystole episode is false asystole (128). Based on not detecting the threshold number of depolarizations (no at 168), the processing circuit 50 may proceed to apply another false asystole detection criterion, such as the decaying noise criterion described with reference to block 130 of FIG. 6 (170).

[0066] 9 is a graph showing a cardiac EGM 181 with attenuating noise, which may be a digitized cardiac EGM segment included as episode data for a suspected asystole episode.

[0067] Over the time span generally indicated by bracket 182, cardiac EGM 181 includes a somewhat consistent pattern of peaks and variations in amplitude that repeat at relatively consistent time intervals. During the time span generally indicated by bracket 183, 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 a much larger amplitude and duration than any of the peaks provided in cardiac EGM 181 during the time span indicated by bracket 182.

[0068] Following amplitude spike 184 and during the time span generally indicated by bracket 185, cardiac EGM 181 may include greater variation in the amplitude of the signal and may include more negative peaks and / or lower overall mean or median amplitude values ​​compared to these same parameters when measured over the time span indicated by bracket 182. In some examples of false asystole detection criteria, processing circuit 50 may analyze the variation indicated during amplitude spike 184 and / or the time span indicated by bracket 185 following amplitude spike 184 to determine whether these portions of cardiac EGM 181 represent a noise signal, e.g., decaying noise.

[0069] 10 is a graph illustrating a cardiac EGM 191 including attenuating noise and an exemplary technique for determining whether exemplary false asystole detection criteria are met based on the cardiac EGM. The cardiac EGM 191 may be, for example, a digitized cardiac EGM segment that is included by the IMD 10 as episode data for a suspected asystole episode based on the processing circuitry 50 of the IMD 10 determining that the asystole detection criteria are met.

[0070] 10, cardiac EGM 191 includes an amplitude spike 202 in a portion of cardiac EGM 191 following the time shown as "0" (zero) seconds. For example, using a set of detection windows, such as illustratively represented by detection windows 194 and 196 in the example of FIG. 10, processing circuit 50 can analyze one or more portions of cardiac EGM 191 to determine whether cardiac EGM 191 includes a noise signal, such as amplitude spike 202 or other decaying noise.

[0071] In various examples, analyzing the cardiac EGM 191 to determine if a noise signal is present includes determining a sample time 192 as a basis for setting detection windows 194 and 196. In some examples, determining the sample time 192 includes setting the sample time equal to the time at which a depolarization 203, e.g., an R-wave, is detected in the cardiac EGM 191. The depolarization 203, in some examples, may be the most recent depolarization preceding the asystole interval 152 ( FIG. 7 ).

[0072] Once processing circuitry 50 selects sample time 192, processing circuitry 50 may set a baseline window 194 such that the baseline window includes a time span 195 that extends from sample time 192 to an amount of time prior to sample time 192. The width of time span 195 is not limited to a particular time span, and in some examples may be a time span in the range of 0.5 to 5 seconds. In the example of FIG. 10, baseline window 194 extends from sample time 192 and includes an exemplary time span 195 of approximately 1 second, extending to include a portion of cardiac EGM 191 spanning a time from sample time 192 to up to 1 second prior to sample time 192.

[0073] In various examples, processing circuitry 50 determines a baseline amplitude value 199 based on sample 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 EGMs 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 the average or median of the amplitude values ​​of cardiac EGMs 191 during baseline window 194.

[0074] Processing circuitry 50 also sets measurement window 196 to include time span 197 extending from sample time 192 for an amount of time following sample time 192. Time span 197 is not limited to a particular duration and, in some examples, may be in the range of 0.5 to 5 seconds. In the example of FIG. 10, the time span is approximately 1 second in duration, including the portion of cardiac EGM 191 spanning from sample time 192 to a time up to 1 second after sample time 192. In various examples, the width of time span 197 of measurement window 196 is equal to or different from the width of time span 195 set for baseline window 194. In examples where depolarization 203 is the immediate depolarization preceding asystole interval 152, measurement window 196 includes at least a portion of the asystole interval.

[0075] Processing circuitry 50 can determine amplitude values ​​of samples of the cardiac EGM 191 within the measurement window 196. Processing circuitry 50 can determine an area under the curve value of the portion of the cardiac EGM 191 based on these sampled amplitude values ​​within the measurement window 196 and a baseline amplitude value 199 determined based on the baseline window 194.

[0076] For example, processing circuitry 50 may determine a set of difference values ​​between amplitude values ​​of the cardiac EGMs 191 that are within the measurement window 196 and the baseline amplitude value 199. In some examples, processing circuitry 50 determines an area under the curve value by calculating an area 198 contained under the portion of the cardiac EGMs 191 that is within the measurement window 196 and that exceeds the baseline amplitude value 199. The calculation of the area under the curve value is not limited to a particular technique for calculating this area and may include any technique for calculating the area under the curve, as would be understood by one of ordinary skill in the art. Once the area under the curve value is calculated for the area 198, processing circuitry 50 may compare the area under the curve value to a noise signal threshold. In some examples, if the area under the curve value exceeds or is equal to the noise signal threshold, processing circuitry 50 determines that a noise signal has been detected in the cardiac EGMs 191 and the false asystole detection criteria have been met.

[0077] Although in the example of FIG. 10, baseline window 194 extends back in time and measurement window 196 extends forward in time from the immediately preceding depolarization 203, processing circuitry 50 may set baseline window 194 and measurement window 196 with other time relationships to depolarization 203. For example, processing circuitry 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 of time after detection of depolarization 203, referred to as a blanking period, during which IMD 10 is prevented from detecting subsequent depolarizations. In such examples, measurement window 196 may have a longer duration than baseline window 194, for example, to capture the expected duration of amplitude spike 202. In some examples, baseline window 194 and measurement window 196 need not be contiguous or adjacent.

[0078] Generally, P-waves are relatively more narrowly and / or more uniformly distributed above and below the baseline amplitude, resulting in a smaller area under the curve measurement, after which the noise signal decays, e.g., decays exponentially. As a result, the area under the curve measurement can effectively distinguish between P-waves occurring during true asystole and decaying noise that resulted in the detection of false asystole.

[0079] Figure 11 is a flow diagram illustrating example operations for determining whether example false asystole criteria for detecting decaying noise are met, e.g., corresponding to item 130 of Figure 6. The example operations of Figure 11 will be described with reference to the cardiac EGM 148 and other data shown in Figure 7, and the cardiac EGM 191 and other data shown in Figure 10.

[0080] 11 , processing circuitry 50 identifies (220) the last depolarization 203 preceding asystole interval 152. Processing circuitry 50 further sets (222) a baseline window 194 and a measurement window 196 based on the time of the last depolarization 203. Processing circuitry 50 determines (224) a baseline amplitude 199 based on the amplitude of the cardiac EGM 191 within baseline window 194, e.g., as the mean or median of the amplitude within baseline window 194.

[0081] Processing circuitry 50 further determines (226) a measure of the area under the curve of the portion of the cardiac EGM 191 within the measurement window 196 relative to the baseline amplitude 199. For example, processing circuitry 50 may determine the measure of the area under the curve 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 measuring the area under the curve may be employed.

[0082] Processing circuitry 50 determines whether the area under the curve measurement meets a threshold, e.g., is greater than or equal to a threshold (228). Based on the area under the curve measurement meeting the threshold (yes at 228), processing circuitry 50 may determine that the suspected asystole episode is false asystole (128). Based on the area under the curve measurement not meeting the threshold (no at 228), processing circuitry 50 may proceed to apply another false asystole detection criterion (170), such as a leading depolarization variability criterion as described with reference to block 132 of FIG.

[0083] 12 is a graph illustrating a differential signal 241 of a cardiac EGM including attenuated noise, and an exemplary technique for determining whether exemplary false asystole detection criteria are met based on the cardiac EGM. The processing circuitry 50 of the IMD 10 may determine the differential signal 241 based on digitized cardiac EGM segments included by the IMD 10 as episode data for a suspected asystole episode, for example, based on the processing circuitry 50 determining that the asystole detection criteria are met. In some examples, the processing circuitry 50 determines a value for each sample "y" of the differential signal 241 by taking the amplitude value of the corresponding sample "y" of the cardiac EGM and subtracting from the amplitude value the amplitude value of the cardiac EGM at sample "yn", where n is a predetermined number of samples.

[0084] 12, some of the values ​​of differential signal 241 fall below the "zero" value line 237 and some of the signal values ​​in differential signal 241 fall below the "zero" value line 237. A noise signal in the cardiac EGM, such as amplitude spike 202 as shown in FIG. 10, may result in the differential signal having one or more spikes, such as spike 242 in differential signal 241, followed by a gradual return of differential signal 241 to the zero value line 237.

[0085] Processing circuitry 50 can set measurement window 246 based on detection of an event, such as an R-wave of another depolarization 243 in the cardiac EGM. In the illustrated example, time span 245 begins upon detection of depolarization 243. In the example of FIG. 12, time span 245 extends over a period of 0.5 seconds. The period included in time span 245 is not limited to a particular time span and, in some examples, may range from 0.2 to 1 second. In some examples, time span 245 may correspond to a period after detection of depolarization 243, referred to as a blanking period, during which IMD 10 is prevented from detecting subsequent depolarizations.

[0086] Measurement window 246 begins at the expiration of time span 245, extends across time span 248, and ends at the expiration of time span 248, indicated by vertical dashed line 247. In the example of Figure 12, time span 248 extends over a period of 1.5 seconds. The period included in time span 248 is not limited to a particular time span, and in some examples may range from 1 to 5 seconds.

[0087] The processing circuitry 50 determines the sign, i.e., positive above the zero line 237, negative below the zero line 237, or on the zero line, for the samples of the differential signal 241 within the measurement window 246. The processing circuitry 50 determines a count of one or more of the signs and determines whether the count meets a threshold, e.g., equal to, exceeds, or is below the threshold. The count can take the form of a percentage or fraction of the total number of samples considered. Generally, when decaying noise is present in the cardiac EGM, the signs of the differential signal 241 within the measurement window 246 will be unbalanced, e.g., more signs are negative in the example of FIG. 12. In some examples, the negative signs may be counted or quantified, while other examples may include counting or quantifying the number of positive sample values, the number of non-negative sample values ​​(e.g., a count of zero sample values ​​+ positive sample values), or the number of non-positive sample values ​​(e.g., a count of zero sample values ​​+ negative sample values).

[0088] Using the imbalance in the sign of the differential signal within the measurement window following the last depolarization to detect the presence of decay noise may involve simpler calculations for the IMD 10 processing circuitry 50 than calculating the area under the curve to detect decay noise. Furthermore, P-waves or thermal noise occurring during the asystole interval during true asystole will have a substantially equal distribution of the sign of the differential signal within the measurement window (occurring during the asystole interval), whereas exponential or other decay noise may have a comment, e.g., more than 70% of the samples with a negative sign.

[0089] 13 is a flow diagram illustrating another exemplary operation for determining whether exemplary false asystole criteria for detecting decaying noise are met. The exemplary operation of FIG. 13 will be described with reference to the cardiac differential signal 241 and other data shown in FIG.

[0090] According to the example of Figure 13, processing circuitry 50 identifies (260) the last depolarization 243 preceding an asystole interval, e.g., asystole interval 152 of Figure 7. Processing circuitry further sets (262) a measurement window 246 that begins a period 245 after the last depolarization and determines (264) a differential signal 241 within measurement window 246. Processing circuitry 50 further determines the signs of samples of differential signal 241 within measurement window 246 and, for at least one of the signs, counts or otherwise quantifies (266) the number of samples having that sign.

[0091] The processing circuit 50 determines whether the count of one of the symbols meets a common symbol threshold, e.g., is greater than or equal to the threshold (268). Based on the common symbol threshold being met (yes at 268), the processing circuit 50 may determine that the suspected asystole episode is a false asystole (128). Based on the common symbol threshold not being met (no at 268), the processing circuit 50 may proceed to apply another false asystole detection criterion, such as a leading depolarization variability criterion as described with reference to block 132 of FIG. 6 (270).

[0092] 14 is a graph illustrating a cardiac EGM 290 associated with an identified asystole episode, as well as an exemplary technique for determining whether another exemplary false asystole detection criterion is met based on the cardiac EGM. The cardiac EGM 290 may be, for example, a digitized cardiac EGM segment included by the IMD 10 as episode data for a suspected asystole episode based on the processing circuitry 50 of the IMD 10 determining that the asystole detection criterion is met.

[0093] FIG. 14 illustrates cardiac depolarizations 292A-292G (in this example, R-waves) identified by the IMD 10, for example, by comparing the cardiac EGM 290 to an amplitude threshold, which may be automatically adjustable as described herein. FIG. 14 also illustrates an asystole interval 294. The asystole interval 294 represents the time interval between adjacent (in time) depolarizations 292F and 292G identified by the IMD 10. As described herein, the processing circuit 50 may have determined that an asystole detection criterion is met when the asystole interval 294 reaches a predetermined threshold amount of time. Based on the satisfaction of the asystole detection criterion, the processing circuit may store the cardiac EGM 290, including the period before and after the asystole interval 294, and an indication of the detection (e.g., timing) of the depolarizations 292A-292G (collectively, “depolarizations 292”) in the storage device 52.

[0094] As discussed with reference to item 132 of FIG. 6, one false asystole detection criterion may include determining whether the variability of N depolarizations 292 preceding asystole interval 294 meets a variability threshold. The number "N" of depolarizations preceding asystole interval 294 may be any integer greater than 1, such as 4, 6, or 8. The N depolarizations 292 may, but need not, include the last depolarization 292F preceding asystole interval 294. For example, processing circuit 50 may determine the variability of six depolarizations 292A-292F preceding asystole interval 292.

[0095] The variability may be the variability of the amplitude or other characteristic of the depolarization 292. Processing circuitry 50 may use any known technique for measuring or otherwise characterizing the variability of multiple values ​​to determine the variability of the preceding depolarization 292. In some examples, processing circuitry 50 may compare, e.g., determine, the difference between, for example, the maximum and median amplitudes of the preceding depolarizations. In such examples, processing circuitry 50 may determine whether this difference or other comparison meets, e.g., exceeds, a predetermined threshold.

[0096] Electrical noise can cause false asystole detection. In some instances, cardiac EGMs of asystole episodes falsely detected due to electrical noise appear as flat lines with added random peaks ranging from 40 µV to 2000 µV. True cardiac EGMs likely do not contain such a wide range of R-wave amplitudes within a few seconds. The variability of the preceding depolarizations, e.g., the difference between the maximum and median, can be highly sensitive and specific to false asystole detection caused by electrical noise. Although such criteria may falsely reject true asystole detection if electrical noise happens to occur immediately before the true asystole detection, this confluence is unlikely to occur, especially in IMDs where the asystole detection frequency is below the asystole count detection threshold (122 in Figure 6).

[0097] 15 is a flow diagram illustrating another exemplary operation for determining whether exemplary false asystole criteria are met. The exemplary operation of FIG. 15 will be described with reference to the cardiac EGM 290 and other data shown in FIG.

[0098] 15, processing circuitry 50 identifies (300) N depolarizations 292 that precede an asystole interval 294. Processing circuitry 50 determines the variability of the N leading depolarizations 292. For example, processing circuitry 50 may determine (302) the amplitudes of the N leading depolarizations 292, determine a maximum amplitude of the N leading depolarizations 292, and determine a representative value of the amplitudes of the N leading depolarizations 292, e.g., a median or mean amplitude. Processing circuitry 50 further determines (304) a comparison metric between the maximum amplitude and the representative amplitude, such as a difference or ratio.

[0099] Processing circuitry 50 determines whether the comparison metric meets a threshold, e.g., is greater than or equal to a threshold (306). Based on the comparison metric meeting the threshold (yes at 306), processing circuitry 50 may determine that the suspected asystole episode is false asystole (128). Based on the comparison metric not meeting the threshold (no at 306), processing circuitry 50 may proceed to apply another false asystole detection criterion, such as an energy pattern criterion as described with reference to block 134 of FIG. 6 (308).

[0100] 16 is a graph illustrating a cardiac EGM 320 associated with an identified asystole episode and an exemplary technique for determining whether another exemplary false asystole detection criterion is met based on the cardiac EGM. The cardiac EGM 320 may be, for example, a digitized cardiac EGM segment included by the IMD 10 as episode data for a suspected asystole episode based on the processing circuitry 50 of the IMD 10 determining that the asystole detection criterion is met.

[0101] FIG. 16 illustrates cardiac depolarizations 322A-322E (R-waves in this example) identified by IMD 10, for example, by comparing cardiac EGM 320 to an amplitude threshold that may be automatically adjustable as described herein. FIG. 16 also illustrates asystole interval 323. Asystole interval 323 represents the time interval between adjacent depolarizations 322D and 322E identified by IMD 10. As described herein, processing circuit 50 may have determined that asystole detection criteria are met when asystole interval 323 reaches a predetermined threshold amount of time. Based on the satisfaction of asystole detection criteria, processing circuit 50 may store cardiac EGM 320, including the period before and after asystole interval 323, and an indication of the detection (e.g., timing) of depolarizations 322A-322E (collectively, “depolarizations 322”) in storage device 52.

[0102] As described with reference to item 134 of FIG. 6, one false asystole detection criterion may include evaluating the energy pattern of the cardiac EGM 320 during the asystole interval 323. When a physician reviews a graphical representation of a cardiac EGM, such as the cardiac EGM 320, to determine whether a suspected asystole is true or false, the physician may measure or evaluate the R-R interval preceding the asystole interval 323 to determine whether there is a visible small peak within the asystole interval 323 that is at the same pace or in phase with the preceding R-R interval, e.g., has an R-R interval similar to the preceding R-R interval. Such a pattern may indicate to the physician that the detection of asystole is false, e.g., caused by a drop in R-wave amplitude. In contrast, a small peak within the asystole interval 323 that is out of phase with the preceding R-R interval may be a P-wave during true asystole caused by atrioventricular block.

[0103] In some examples, processing circuitry 50 identifies N depolarizations 322 preceding asystole interval 323, e.g., N consecutive depolarizations 322 including last depolarization 322D preceding asystole interval 323. Based on the N preceding depolarizations 322, processing circuitry 50 can determine N-1 intervals between preceding depolarizations 322, including intervals 324A and 324B (collectively, “inter-depolarization intervals 324”). N can be any integer, such as 7 or 13. Within asystole interval 323, processing circuitry 50 sets expected depolarization windows 326A-326C (collectively, “expected depolarization windows 326”) and expected inter-depolarization windows 328A-328C (collectively, “expected inter-depolarization windows 328”) based on inter-depolarization intervals 324. Although the example of FIG. 16 shows three of each type of window, other examples may employ more or fewer windows of each type and / or different numbers of windows for the two types of windows.

[0104] In some examples, processing circuitry 50 determines a median or other representative value of inter-depolarization interval 324. Processing circuitry 50 can set windows 326 and 328 within asystole interval 323 based on the representative value of inter-depolarization interval 324. For example, processing circuitry 50 can set each of expected depolarization windows 326 to occur, e.g., be centered, at a time that is a different integer multiple of a representative interval after the last preceding depolarization 322D. In one such example, processing circuitry 50 can set expected depolarization window 326A to be a representative interval after depolarization 322D, expected depolarization window 326B to be twice the representative interval after depolarization 322D, and expected depolarization window 326C to be three times the representative interval after depolarization 322D. Processing circuitry 50 can set each of expected inter-depolarization windows 328 to occur, e.g., centered, at a time that is a different non-integer multiple, e.g., fractional multiple, of a representative interval after the last preceding depolarization 322D. In one such example, processing circuitry 50 can set expected inter-depolarization window 328A to be 1 / 2 the representative interval after depolarization 322D, set expected inter-depolarization window 328B to be 1 1 / 2 times the representative interval after depolarization 322D, and set expected inter-depolarization window 328C to be 2 1 / 2 times the representative interval after depolarization 322D. The widths of windows 326 and 328 can be set as a predetermined portion, e.g., a fraction or percentage, or a representative interval, where the predetermined portion can be the same or different between window 326 and window 328.

[0105] Processing circuitry 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 circuitry 50 determines an energy value for each of window 326 and window 328, and then determines a first average, median, or other representative energy value of the energy values ​​of window 326 and a second representative energy value of the energy values ​​of window 328. Processing circuitry 50 may employ any known technique for determining the energy of a signal within a window. In some examples, as the energy value for each of windows 326 and 328, processing circuitry 50 determines a difference, ratio, or other comparison metric between the maximum amplitude of cardiac EGM 320 and the minimum amplitude of cardiac EGM 320 within the window.

[0106] Processing circuitry 50 further determines a difference, ratio, or other comparison metric between a first representative energy value of expected depolarization window 326 and a second representative energy value of expected inter-depolarization window 328. Processing circuitry 50 determines whether the comparison metric meets a threshold, e.g., is equal to or greater than 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 was a false asystole detection.

[0107] 17 is a flow diagram illustrating another exemplary operation for determining whether exemplary false asystole criteria are met. The exemplary operation of FIG. 17 will be described with reference to the cardiac EGM 320 and other data shown in FIG.

[0108] 17 , processing circuitry 50 identifies (340) N depolarizations 322 that precede an asystole interval 323. Processing circuitry 50 determines (342) an interval 324 between the N preceding depolarizations 322. Processing circuitry 50 further sets (344) an expected depolarization window 326 and an expected inter-depolarization window 328 within asystole interval 323 based on interval 324, e.g., based on integer and non-integer multiples, respectively, of the mean or median of interval 124.

[0109] Processing circuitry 50 determines (346) the difference between the energy values ​​of each of expected depolarization window 326 and expected inter-depolarization window 328, e.g., the maximum and minimum amplitudes of cardiac EGM 320 within each window. Processing circuitry 50 further determines (348) a comparison metric between the energy of window 326 and the energy of window 328. For example, processing circuitry 50 may determine the difference between the average of the energy of window 326 and the average of the energy of window 328.

[0110] Processing circuitry 50 determines whether the comparison metric meets a threshold, e.g., is greater than or equal to a threshold (350). Based on the comparison metric meeting the threshold (yes at 350), processing circuitry 50 may determine that the suspected asystole episode is false asystole (128). Based on the comparison metric not meeting the threshold (no at 350), processing circuitry 50 may proceed to apply another false asystole detection criterion, or if there are no other false asystole detection criterion to apply, the operations of Figures 17 and 6 may end (124).

[0111] 18A-18C are conceptual diagrams of another exemplary medical system 410 implanted within a patient 408. FIG 1A is a front view of the medical system 410 implanted within a patient 408. FIG IB is a side view of the medical system 410 implanted within a patient 408. FIG 1C is a cross-sectional view of the medical device system 410 implanted within a patient 408.

[0112] In some examples, the medical system 410 is an extravascularly implantable cardioverter defibrillator (EV-ICD) system implanted within a patient 408. The medical system 410 includes an IMD 412, which in the illustrated example is implanted subcutaneously or submuscularly in the left mid-axilla of the patient 408 such that the IMD 412 may be positioned on the left side of the patient 408 above the rib cage. In some other examples, the IMD 412 may be implanted in other subcutaneous locations on the patient 408, such as in a thoracic location or an abdominal location. The IMD 412 includes a housing 420 that may form an airtight seal to protect the components of the IMD 412. In some examples, the housing 420 of the IMD 412 may be formed from a conductive material, such as titanium, or from a combination of conductive and non-conductive materials that may function as the housing electrodes. The IMD 412 may also include a connector assembly (also referred to as a connector block or header) that includes electrical feedthroughs that make electrical connections between the leads 422 and electronic components contained within the housing.

[0113] The IMD 412 may provide cardiac EGM sensing, asystole detection, and other functions described herein with respect to the IMD 10, and the housing 420 may house the circuitry 50-62 that provides such functions and the antenna 26 (FIGS. 2 and 3). The 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 the patient 408. The system 410 may include an external device 12 that may function with the IMD 412 as described herein with respect to the IMD 10 and system 2.

[0114] 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 including a connector (not shown) configured to connect to the IMD 412 and a distal portion including electrodes 432A, 432B, 434A, and 434B. The lead 422 extends subcutaneously above the rib cage toward the center of the patient's 408 torso from the IMD 412. At a location near the center of the torso, the lead 422 bends or curves and extends superiorly within the thoracic cavity below / below the sternum 424. Thus, the lead 422 may be at least partially implanted within the substernal space, such as a target site between the rib cage or sternum 424 and the heart 418. In one such configuration, a proximal portion of the lead 422 may be configured to extend subcutaneously from the IMD 12 toward the sternum 24, and a distal portion of the lead 22 may be configured to extend superiorly below or inferior to the sternum 424 in the anterior mediastinum 426 (FIG. 1C).

[0115] For example, the lead 422 can extend superiorly within the thoracic cavity below / inferior to the sternum 424 in the anterior mediastinum 426. The anterior mediastinum 426 can be considered to be bounded posteriorly by the pericardium 416, laterally by the pleura 428, and anteriorly by the sternum 424. In some examples, the anterior wall of the anterior mediastinum 426 can also be formed by the transverse thoracic muscle and one or more costal cartilages. The anterior mediastinum 426 includes a quantity of loose connective tissue (such as loose tissue), some lymphatic vessels, lymph glands, substernal musculature (e.g., transverse pectoralis muscle), and small blood vessels or vascular branches. In one example, a distal portion of the lead 422 can be substantially implanted within the loose connective tissue and / or substernal musculature of the anterior mediastinum 426. In such examples, the distal portion of the lead 422 can be physically isolated from the pericardium 416 of the heart 418. A lead implanted substantially within the anterior mediastinum 426 is an example of a substernal lead, or, more generally, an extravascular lead.

[0116] The distal portion of the lead 422 is described herein as being substantially implanted within the anterior mediastinum 426. Thus, a portion of the distal portion of the lead 422 can extend from the anterior mediastinum 426 (e.g., a proximal end of the distal portion), but much of the distal portion can be located within the anterior mediastinum 426. In other embodiments, the distal portion of the lead 422 can be implanted within the thoracic cavity in other non-vascular extrapericardial locations, including gaps, tissues, or other anatomical features that are around and adjacent to, but not attached to, the pericardium 416 or other portions of the heart 418 and that are not above the sternum 424 or rib cage. The lead 422 can be implanted anywhere within the "substernal space," defined by the inferior surface between the sternum and / or rib cage 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," as known to those skilled in the art, and includes the anterior mediastinum 426. The substernal space may also include the anatomical region described as Larrey's space 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 within the region about the exterior surface of the heart 418, but is not attached to the heart 418. For example, the distal portion of the lead 422 may be physically isolated from the pericardium 416.

[0117] The lead 422 may include an insulative lead body having a proximal end including a connector 430 configured to connect to the IMD 412 and a distal portion including one or more electrodes. As shown in FIG. 18A, the one or more electrodes of the lead 422 may include electrodes 432A, 432B, 434A, and 434B, although in other examples, the lead 422 may include more or fewer electrodes. The lead 422 also includes one or more conductors that form a conductive pathway within the lead body and interconnect each one of the electrodes with the electrical connector.

[0118] Electrodes 432A, 432B may be defibrillation electrodes (individually or collectively, "defibrillation electrodes 432"). Electrodes 432 may be referred to herein as "defibrillation electrodes 432," although electrodes 432 may be configured to deliver other types of anti-tachyarrhythmia shocks, such as cardioversion shocks. Defibrillation electrodes 432 are depicted as coil electrodes for clarity in FIGS. 18A-18C, but it should be understood that defibrillation electrodes 432 may be of other configurations in other examples. Defibrillation electrodes 432 may be located at a distal portion of lead 422, which is the portion of lead 422 configured to be implanted extravascularly beneath sternum 424.

[0119] The lead 422 may be implanted at a target site below or along the sternum 424 such that a therapy vector substantially traverses the ventricles of the heart 418. In some examples, the therapy vector (e.g., a shock vector for delivering an anti-tachyarrhythmia shock) may be between the defibrillation electrode 432 and a housing electrode formed by or on the IMD 412. The therapy vector, in one example, may be considered as a line extending from a point on the defibrillation electrode 432 (e.g., the center of one of the defibrillation electrodes 432) to a point on the housing electrode of the IMD 412. Thus, it may be advantageous to increase the amount of area over which the defibrillation electrode 432 (and the distal portion of the lead 422 therein) extends across the heart 418. Thus, the lead 422 may be configured to define a curved distal portion, as shown in FIG. 18A. In some examples, the curved distal portion of the lead 22 may help improve the effectiveness and / or efficiency of pacing, sensing, and / or defibrillation of the heart 418 by the IMD 412.

[0120] Electrodes 434A, 434B may be pace / sense electrodes (individually or collectively "pace / sense electrodes 434") located at a distal portion of lead 422. Electrodes 434 are referred to herein as pace / sense electrodes because they are generally configured for use in delivering pacing pulses and / or sensing cardiac electrical signals. In some cases, electrodes 434 may provide only pacing functions, only sensing functions, or both pacing and sensing functions. In the example shown in FIGS. 18A and 18B, pace / sense electrodes 434 are separated from one another by defibrillation electrode 432B. However, in other examples, pace / sense electrodes 434 may both be distal to defibrillation electrode 432B or both be proximal to defibrillation electrode 432B. In examples where lead 422 includes more or fewer electrodes 432, 434, such electrodes may be positioned elsewhere on lead 422.

[0121] In the example of FIG. 18A , the distal portion of the lead 422 is serpentine-shaped, including two “C”-shaped curves, which together may resemble the Greek letter epsilon “ε”. The defibrillation electrodes 432 are each carried by one of the two respective C-shaped portions of the lead body distal portion. 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 pace / sense electrode 434 may be approximately aligned with the central axis of the straight proximal portion of the lead 422. In such examples, the midpoint of the defibrillation electrode 432 is offset laterally from the pace / sense electrode 434. Other examples of extracardiac leads including one or more defibrillation electrodes and one or more pace / sense electrodes 434 carried by a curved, serpentine, undulating, or zigzag distal portion of the lead 422 may also be implemented using the techniques described herein. In some examples, the distal portion of the lead 422 can be straight (eg, straight or nearly straight).

[0122] Deploying the lead 422 so that the electrodes 432, 434 lie at the delineated peaks and valleys of the serpentine shape can provide access to a preferred sensing or therapy vector. Orienting a serpentine-shaped lead so that the pace / sense electrodes 434 are closer to the heart 418 can provide better electrical sensing of cardiac signals and / or a lower pacing capture threshold than if the pace / sense electrodes 434 were oriented further away from the heart 418. The serpentine or other shape of the distal portion of the lead 422 can improve fixation to the patient 408 as a result of the shape providing resistance against adjacent tissue when axial forces are applied. Another advantage of a shaped distal portion is that the electrodes 432, 434 can access a larger surface area over a shorter length of the heart 418 versus a lead having a straighter distal portion.

[0123] In some examples, the elongated lead body of the lead 422 may include one or more elongated conductors (not shown) that extend within the lead body from a connector at the proximal lead end to the electrodes 432, 434 located along a distal portion of the lead 422. The one or more elongated conductors included within the lead body of the lead 422 may engage with each of the electrodes 432, 434. The conductors may be electrically coupled to circuits, such as the therapy delivery circuitry and sensing circuitry 52 of the IMD 412, via connections in the connector assembly. The conductors deliver therapy from the therapy delivery circuitry to one or more of the electrodes 432, 434 and transmit sensed cardiac EGMs from one or more of the electrodes 432, 434 to the sensing circuitry 52 in the IMD 412.

[0124] Generally, the IMD 412 can sense cardiac EGMs, such as via one or more sensing vectors including a combination of the pace / sense electrodes 434 and / or housing electrodes of the IMD 412. In some examples, the IMD 412 can sense cardiac EGMs using one or both of the defibrillation electrodes 432 and / or a sensing vector including one of the defibrillation electrodes 432 and one of the pace / sense electrodes 434 or a housing electrode of the IMD 412. The medical system 410, including the IMD 412 and / or the processing circuitry of the external device 12, can perform any of the techniques described herein for determining whether asystole detection and false asystole detection criteria are met based on the cardiac EGMs sensed via the extravascular electrodes 432, 434, for example. Cardiac EGMs sensed via the extravascular electrodes may include noise due to contact with tissue and / or changes in orientation relative to the heart, for example, in a manner similar to that described herein for subcutaneous electrodes. In general, if the electrodes are not fixed directly to the myocardium, motion, e.g., respiratory motion, can cause variability in depolarization amplitude and other noise, which can lead to false asystole detection. The techniques described herein can be implemented with cardiac EGMs sensed via subcutaneous, cutaneous, substernal, extravascular, intramuscular, or any electrodes positioned on (or in contact with) any tissue of the patient.

[0125] The techniques described in this disclosure may be implemented, at least in part, in hardware, software, firmware, or any combination thereof. For example, various aspects of the techniques may be implemented in one or more microprocessors, DSPs, ASICs, FPGAs, or any other equivalent integrated or discrete logic QRS circuits, as well as any combination of such components, embodied in an external device, such as a physician or patient programmer, stimulator, or other device. The term "processor" or "processing circuitry" may generally refer to any of the aforementioned logic circuits, alone or in combination with other logic circuits, or any other equivalent circuitry, alone or in combination with other digital or analog circuits.

[0126] For software-implemented aspects, at least a portion of the functionality attributable to the systems and devices described in this disclosure may be embodied as instructions on a computer-readable storage medium, such as in the form of RAM, DRAM, SRAM, magnetic disk, optical disk, flash memory, or EPROM or EEPROM, which may be executed to support one or more aspects of the functionality described in this disclosure.

[0127] Further items are described as follows:

[0128] Item 1. A method comprising: sensing an electrocardiogram of the patient via a plurality of electrodes of the medical system; determining, by a processing circuit of the medical system, that asystole detection criteria are met based on the electrocardiogram; and based on the determination that asystole detection has been met, determining, by the processing circuit, that at least one of a plurality of false asystole detection criteria is met based on the electrocardiogram signal; and withholding an indication of an asystole episode from the patient based on a determination, by the processing circuitry, that at least one of a plurality of false asystole detection criteria is met, the plurality of false asystole detection criteria including: A first false cardiac arrest detection criterion including a reduced amplitude threshold for detecting cardiac depolarization in an electrocardiogram, and a second false cardiac arrest detection criterion for detecting attenuation noise in an electrocardiogram, the method comprising.

[0129] Item 2. Determining that the cardiac arrest detection criterion is satisfied includes determining that the cardiac arrest detection criterion is satisfied based on not identifying cardiac depolarization in the electrocardiogram during a certain time interval. The method of item 1.

[0130] Item 3. Determining that the first false cardiac arrest detection criterion is satisfied includes comparing a reduced amplitude threshold with the electrocardiogram during a time interval, and based on the comparison, determining that the number of cardiac depolarization thresholds is identified in the electrocardiogram during the time interval. The method of item 1 or 2.

[0131] Item 4. Further includes identifying one or more cardiac depolarizations occurring in the electrocardiogram preceding the time interval by a processing circuit, determining the amplitude of each of the one or more identified cardiac depolarizations, and determining a reduced amplitude threshold based on the determined amplitudes of the one or more identified cardiac depolarizations. The method of any one of the above items.

[0132] Item 5. One or more identified cardiac depolarizations include a plurality of identified cardiac depolarizations, and determining a reduced amplitude threshold includes determining a representative amplitude based on the amplitude of each of the plurality of identified cardiac depolarizations, and determining a reduced amplitude threshold as a predetermined portion of the representative amplitude. The method of item 4.

[0133] Item 6. Determining that the second false cardiac arrest detection criterion is satisfied includes calculating the value of the area under the curve of the electrocardiogram during at least a portion of the time interval, and determining that the value of the area under the curve satisfies a threshold of the area under the curve. The method of item 1, 2, 3, or 4.

[0134] Item 7. Determining that a second false asystole detection criterion is met 5. The method of item 1, 2, 3, or 4, comprising: determining a differential signal of a cardiac electrogram during at least a portion of a time interval; determining for each of a plurality of samples of the differential signal whether the sign of the sample is positive or negative; and determining that an amount of samples having one of the signs satisfies a common sign threshold.

[0135] Item 8. The method of items 1, 2, 3, or 4, wherein the plurality of false asystole detection criteria further includes a third false asystole detection criterion, and determining that the third false asystole detection criterion is met includes identifying a plurality of cardiac depolarizations occurring in a cardiac electrogram preceding the time interval, determining an amplitude of each of the plurality of identified cardiac depolarizations, determining a variability of the amplitudes, and determining that the variability meets a variability threshold.

[0136] Item 8. The method of item 8, wherein determining the variability of the amplitude includes determining a maximum amplitude of the plurality of amplitudes, determining a representative amplitude of the plurality of amplitudes, and determining a comparison metric of the maximum amplitude to the representative amplitude.

[0137] Item 9. The plurality of false asystole detection criteria further includes a third false asystole detection criterion, and determining that the third false asystole detection criterion is satisfied includes: 5. The method of items 1, 2, 3, or 4, comprising: identifying a plurality of cardiac depolarizations occurring in a cardiac electrogram preceding the time interval; determining one or more intervals between adjacent ones 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 intervals; 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 to the second energy; and determining that the comparison metric meets a threshold.

[0138] Item 10. The method of items 1, 2, 3, or 4, further including determining, by the processing circuitry, a count of instances of satisfaction of asystole detection criteria within a period of time and determining whether the count meets at least one asystole count criterion, wherein determining whether the multiple false asystole detection criteria are met includes determining whether the multiple false asystole detection criteria are met based on determining that the count meets the at least one asystole count criterion.

[0139] Item 11. The method of claim 14, wherein a plurality of electrodes are implanted subcutaneously, and sensing the cardiac electrogram comprises sensing the cardiac electrogram via the plurality of subcutaneously implanted electrodes.

[0140] Item 12. The method of items 1, 2, 3, or 4, wherein a plurality of electrodes are extravascularly implanted, and sensing the cardiac electrogram comprises sensing the cardiac electrogram via the plurality of extravascularly implanted electrodes.

[0141] Item 13. A non-transitory computer-readable storage medium comprising program instructions that, when executed by a processing circuit of a medical system, cause the processing circuit to: determine that an asystole detection criterion is met based on an electrocardiogram sensed via a plurality of electrodes of the medical system; determine whether a plurality of false asystole detection criteria are met based on the electrocardiogram signal based on a determination that asystole detection is met; and withhold indication of an asystole episode in the patient based on a determination that at least one of the plurality of false asystole detection criteria is met, wherein 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 electrocardiogram and a second false asystole detection criterion for detecting decaying noise in the electrocardiogram.

[0142] Furthermore, in some aspects, the functionality described herein may be provided within dedicated hardware and / or software modules. The depiction of different features as modules or units is intended to emphasize different functional aspects and does not necessarily imply that such modules or units must be realized by separate hardware or software components. Rather, functionality associated with one or more modules or units may be performed by separate hardware or software components or may be integrated within a common or separate hardware or software component. The technology may also be fully implemented in one or more circuits or logic elements. The technology of the present disclosure may be implemented in a wide variety of devices or apparatuses, including an IMD, an external programmer, a combination of an IMD and an external programmer, an integrated circuit (IC) or set of ICs present within the IMD and / or external programmer, and / or discrete electrical circuits.

Claims

1. 1. A health care system comprising: a plurality of electrodes configured to sense a cardiac electrogram of the patient; and a processing circuit, the processing circuit comprising: determining that an asystole detection criterion is met based on the electrocardiogram; and determining whether a plurality of false asystole detection criteria are met based on the electrocardiogram signal based on the determination that the asystole detection criteria are met; and withholding an indication of an asystole episode for the patient based on a determination that at least one of the plurality of false asystole detection criteria is met; 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 electrocardiogram; and a second false asystole detection criterion for detecting decaying noise in the electrocardiogram, The processing circuitry comprises: determining that the asystole detection criterion is met based on not identifying a cardiac depolarization in the electrogram during a time interval; identifying one or more cardiac depolarizations occurring in the electrogram preceding the time interval; determining an amplitude of each of the one or more identified cardiac depolarizations; determining the amplitude threshold based on the determined amplitudes of the one or more identified cardiac depolarizations. It is configured as follows: the one or more identified cardiac depolarizations include a plurality of identified cardiac depolarizations; The processing circuitry further comprises: determining a representative amplitude based on the amplitude of each of the plurality of identified cardiac depolarizations; determining the amplitude threshold as a predetermined portion of the representative amplitude; A healthcare system structured in such a way.

2. To determine that the second false asystole detection criterion is met, the processing circuitry further comprises: determining a differential signal of the electrocardiogram during at least a portion of the time interval; determining, for each of a plurality of samples of the differential signal, whether the sign of the sample is positive or negative; and determining whether an amount of samples having one of the signs meets a common sign threshold.

3. A medical system comprising: a plurality of electrodes configured to sense a cardiac electrogram of the patient; and a processing circuit, the processing circuit comprising: determining that an asystole detection criterion is met based on the electrocardiogram; and determining whether a plurality of false asystole detection criteria are met based on the electrocardiogram signal based on the determination that the asystole detection criteria are met; and withholding an indication of an asystole episode for the patient based on a determination that at least one of the plurality of false asystole detection criteria is met; 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 electrocardiogram; and a second false asystole detection criterion for detecting decaying noise in the electrocardiogram, the processing circuitry is configured to determine that the asystole detection criterion is met based on not identifying a cardiac depolarization in the electrogram during a time interval; To determine that the second false asystole detection criterion is met, the processing circuitry further comprises: calculating a value of the area under the curve of said electrocardiogram during at least a portion of said time interval; determining whether the area under the curve value satisfies an area under the curve threshold. A healthcare system structured in this way.

4. the plurality of false asystole detection criteria further includes a third false asystole detection criterion, and to determine that the third false asystole detection criterion is satisfied, the processing circuitry: identifying a number of cardiac depolarizations occurring in the electrogram preceding the time interval; determining an amplitude of each of the plurality of identified cardiac depolarizations; determining a variability of the amplitude; The medical system of claim 1 , further comprising: a step of: determining whether the variability satisfies a variability threshold.

5. To determine the variability of the amplitude, the processing circuitry determining a maximum amplitude of the plurality of amplitudes; determining a representative amplitude of the plurality of amplitudes; and determining a metric of a comparison of the maximum amplitude to the representative amplitude.

6. the plurality of false asystole detection criteria further includes a third false asystole detection criterion, and to determine that the third false asystole detection criterion is satisfied, the processing circuitry: identifying a number of cardiac depolarizations occurring in the electrogram preceding the time interval; determining one or more intervals between adjacent ones 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 metric of a comparison of the first energy to the second energy; and determining whether the comparison metric meets a threshold.

7. The processing circuitry comprises: determining a count of instances of satisfaction of the asystole detection criteria within a period of time; determining whether the count meets at least one asystole count criterion; 7. The medical system of claim 1, wherein the processing circuitry is configured to determine whether the plurality of false asystole detection criteria are met based on determining that the count meets at least one asystole count criterion.

8. The medical system of any one of claims 1 to 7, wherein the plurality of electrodes is configured for subcutaneous implantation and the cardiac electrogram comprises a subcutaneous cardiac electrogram.

9. The medical system of any one of claims 1 to 8, wherein the plurality of electrodes is configured for extravascular implantation and the cardiac electrogram comprises an extravascular cardiac electrogram.

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