Monitoring and warning of acute health events

Abstract

A system comprising: a processing circuit configured to receive a message wirelessly transmitted from a medical device, the message indicating that the medical device has detected an acute health event in a patient, in response to the message, the processing circuit configured to determine a location of the patient, determine an alert region based on the location of the patient, and control transmission of an alert of the patient's acute health event to any one or more computing devices of one or more potential responders within the alert region.

Description

Technical Field

[0001]

[0001] The present disclosure generally relates to systems including medical devices, and more specifically to the monitoring of a patient's health using such systems.

Background Art

[0002]

[0002] Various devices are configured to monitor a patient's physiological signals. Such devices include implantable or wearable medical devices, and various wearable health or fitness tracking devices. Physiological signals sensed by such devices include, by way of example, electrocardiogram (ECG) signals, respiratory signals, perfusion signals, activity and / or posture signals, blood pressure signals, blood oxygen saturation signals, body composition, and blood glucose or other blood component signals. Generally, using these signals, such devices facilitate the monitoring and evaluation of a patient's health outside of a clinical environment over months or years.

[0003]

[0003] In some examples, such devices are configured to detect acute health events based on physiological signals such as episodes of arrhythmia, myocardial infarction, stroke, or seizure. Exemplary types of arrhythmia include cardiac arrest (e.g., asystole), ventricular tachycardia (VT), and ventricular fibrillation (VF). The device may store ECG and other physiological signal data collected during a period including an episode as episode data. Such acute health events are associated with a significant mortality rate, particularly if not treated promptly.

[0004]

[0004] For example, VF and other malignant tachyarrhythmias are the most commonly identified arrhythmias in patients with sudden cardiac arrest (SCA). If this arrhythmia persists for more than a few seconds, it can lead to cardiogenic shock and cessation of effective blood circulation. The survival rate from SCA decreases by 7 - 10 percent every minute the patient waits for defibrillation. As a result, sudden cardiac death (SCD) can occur in just a few minutes. [Overview of the project]

[0005]

[0005] In general, this disclosure describes a technique for providing alerts in response to the detection of an acute health event in a patient by a medical device. In some examples, a patient's computing device, such as a smartphone or smartwatch, receives a radio-transmitted message from a medical device, such as an implantable medical device, indicating the detection of an acute health event. For example, the computing device's processing circuitry may, in response to the message, perform a variety of actions, such as analyzing the patient's physiological data to confirm the acute health event, presenting a local alert via the computing device's user interface, determining whether the alert will be canceled within a time interval, calling emergency medical services (e.g., 911), and sending an alert to the patient's family and / or caregivers. The processing circuitry may also control the transmission of alerts to any one or more computing devices of one or more potential responders present within an alert area determined based on the patient's location. The techniques described herein can reduce the time to treatment for acute health events.

[0006]

[0006] In one example, the system comprises a processing circuit configured to receive a message wirelessly transmitted from a medical device, the message indicating that the medical device has detected an acute health event in a patient. In response to the message, the processing circuit is configured to determine the patient's location, determine an alert area based on the patient's location, and control the transmission of an alert of the patient's acute health event to any one or more computing devices of one or more potential responders within the alert area.

[0007]

[0007] In another example, the method includes a processing circuit receiving a message wirelessly transmitted from a medical device, the message indicating that the medical device has detected an acute health event in a patient; determining the patient's location in response to the message; determining a warning area based on the patient's location; and controlling the transmission of a warning of the patient's acute health event to any one or more computing devices of one or more potential responders within the warning area.

[0008]

[0008] In another example, the system comprises a processing circuit configured to perform one of the methods described herein.

[0009]

[0009] In another example, a non-temporary computer-readable storage medium includes program instructions configured to cause a processing circuit to perform any of the methods described herein.

[0010]

[0010] This summary is intended to provide an overview of the subject matter described herein. It is not intended to provide an exclusive or comprehensive description of the apparatus and methods described in detail in the accompanying drawings and description below. Further details of one or more examples are provided in the accompanying drawings and description below. [Brief explanation of the drawing]

[0011] [Figure 1A]

[0011] Block diagram showing an example of a medical device system configured to detect and respond to an acute health event using one or more of the technologies of the present disclosure. [Figure 1B] A block diagram shows an example of a medical device system configured to detect and respond to an acute health event using one or more of the technologies of this disclosure. [Figure 2]

[0012] Figure 1A is a block diagram showing an example configuration of an IMD. [Figure 3]

[0013] Figures 1A and 2 are conceptual side views showing the configuration of an example of an IMD. [Figure 4]

[0014] Block diagram showing an example configuration of a computing device operating in accordance with one or more of the technologies of this disclosure. [Figure 5]

[0015] Block diagram showing an example configuration of a computing system operating in accordance with one or more of the technologies of this disclosure. [Figure 6]

[0016] This flowchart illustrates an example of a technique that provides warnings in response to the detection of acute health events in patients. [Figure 7]

[0017] This flowchart illustrates an example technique for sending alerts to potential responders within a warning area.

[0012]

[0018] Similar reference characters refer to the same elements throughout the figure and description. [Modes for carrying out the invention]

[0013]

[0019] Various types of implantable and medical devices detect arrhythmia episodes and other acute health events based on sensed ECGs and, in some cases, other physiological signals. External devices that can be used to non-invasively sense and monitor ECGs and other physiological signals include wearable devices with electrodes configured to come into contact with the patient's skin, such as patches, watches, or necklaces. Such external devices can facilitate relatively long-term monitoring of a patient's health during normal daily activities.

[0014]

[0020] Implanted medical devices (IMDs) also sense and monitor ECG and other physiological signals and detect acute health events such as episodes of arrhythmia, cardiac arrest, myocardial infarction, stroke, and seizure. Examples of IMDs include pacemakers and implantable cardioverter defibrillators that can be coupled to intravascular or extravascular leads, and pacemakers with a housing configured to be implanted within the heart, which may be leadless. There are also IMDs that do not provide therapy, such as implantable patient monitors. One example of such an IMD is the Reveal LINQ™ implantable cardiac monitor (ICM) available from Medtronic plc, which can be inserted subcutaneously. Such IMDs facilitate relatively long-term monitoring of patients during normal daily activities and can periodically transmit the collected data, such as episode data of detected arrhythmia episodes, to a remote patient monitoring system such as the Medtronic Carelink™ network.

[0015]

[0021] Figures 1A and 1B are block diagrams showing an example medical device system 2 configured to detect and respond to an acute health event of patient 4 according to the techniques of the present disclosure. The exemplary techniques can be used with an IMD 10 that can wirelessly communicate with one or more external computing devices, such as computing devices 12A and 12B (collectively "computing devices 12"). In some examples, IMD 10 is implanted outside the chest cavity of patient 4 (e.g., subcutaneously at the chest location shown in FIG. 1). IMD 10 can be positioned near or just below the level of the heart of patient 4, e.g., at least partially within the silhouette of the heart, near the sternum. IMD 10 includes a plurality of electrodes (not shown in FIG. 1) and is configured to sense an ECG via the plurality of electrodes. In some examples, IMD 10 takes the form of a LINQ™ ICM. Although mainly described in the context of examples where the IMD takes the form of an ICM, the techniques of the present disclosure can be implemented in a system including any one or more implanted or external medical devices, including monitors, pacemakers, defibrillators, or nerve stimulators.

[0016]

[0022] The computing device 12 is configured to wirelessly communicate with the IMD 10. The computing device 12 retrieves from the IMD 10 the episodes and other physiological data collected and stored by the IMD 10. In some examples, the computing device 12 takes the form of the personal computing device of patient 4. For example, the computing device 12A can take the form of the smart phone of patient 4, and the computing device 12B can take the form of the smart watch or other smart apparel of patient 4. In some examples, the computing device(s) 12 can be any computing device configured to wirelessly communicate with the IMD 10, such as a desktop, laptop, or tablet computer, a smart home controller, an alarm, a thermostat, a speaker, or other smart device, or any Internet of Things (IoT) device. The computing device 12 can communicate with the IMD 10 and with each other, for example, according to the Bluetooth® or Bluetooth® Low Energy (BLE) protocol. In some examples, only one of the computing devices 12, such as the computing device 12A, is configured to communicate with the IMD 10 by executing software that enables communication and interaction with the IMD 10, for example.

[0017]

[0023] In some examples, a computing device (which may be multiple) 12, for example, a wearable computing device 12B in the example shown in Figure 1A, may include electrodes and other sensors for sensing the physiological signals of patient 4, collecting and storing physiological data, and detecting episodes based on such signals. The computing device 12B may be incorporated into the patient's clothing, such as clothing, shoes, glasses, a watch or wristband, a hat, etc. In some examples, the computing device 12B is a smartwatch or other accessory or peripheral for a smartphone computing device 12A.

[0018]

[0024] One or more of the computing devices 12 may be configured to communicate with various other devices or systems, such as the computing system 20, via the network 16. The computing device(s) 12 may transmit data, including data extracted from the IMD 10, to the computing system 20 via the network 16. The data may include values ​​of physiological parameters measured by the IMD 10, and optionally one or more of the computing devices 12, data relating to episodes of arrhythmias or other health events detected by the IMD 10 and the computing device(s) 12, and other physiological signals or data recorded by the IMD 10 and / or the computing device(s) 12.

[0019]

[0025] The computing system 20 may include computing devices configured to enable users, for example, clinicians treating patient 4 and other patients, to interact with data collected from their patients' IMD 10 and computing devices 12. In some examples, the computing system 20 includes one or more handheld computing devices, computer workstations, servers, or other networked computing devices. In some examples, the computing system 20 may include, or be implemented by, the Medtronic Carelink® network.

[0020]

[0026] Network 16 may include one or more computing devices (not shown), such as one or more non-edge switches, routers, hubs, gateways, firewalls, security devices such as intrusion detection and / or intrusion prevention devices, servers, cellular base stations and nodes, wireless access points, bridges, cable modems, application accelerators, or other network devices. Network 16 may also include one or more networks managed by a service provider and thus may form part of a larger public network infrastructure such as the Internet. Network 16 can provide computing devices such as computing device 12, computing devices 14A-14N (collectively, "Computing Device 14"), computing device(s) 18, computing system 20, and emergency medical system (EMS) 22 with access to the Internet and can provide a communication framework that enables computing devices to communicate with each other. In some examples, Network 16 may include a private network that provides a communication framework that enables external devices(s) 12 to communicate with computing system 20 and / or other systems or devices, but for security purposes, one or more of these devices or data flows between these devices are isolated from devices outside the private network. In some examples, communication between external devices (which may be multiple) 12 and other devices such as those in the computing system 20 is encrypted.

[0021]

[0027] One or more processing circuits of System 2, for example, computing device 12A, computing device 12B, and computing system 20, may implement the technology of this disclosure to respond to the detection of an acute health event in patient 4 by IMD 10, either individually or in any combination. The processing circuit may receive a message wirelessly transmitted from IMD 10. The message may indicate that the medical device has detected an acute health event in the patient. The message may indicate the time at which IMD 10 detected the acute health event. The message may include physiological data collected by IMD 10, for example, data leading to the detection of the acute health event, data prior to the detection of the acute health event, and / or real-time or more recent data collected after the detection of the acute health event. The physiological data may include one or more physiological parameters and / or values ​​of digitized physiological signals. Examples of acute health events include cardiac arrest, ventricular fibrillation, ventricular tachycardia, stroke, seizure, or fall.

[0022]

[0028] The processing circuit may provide a warning in response to the detection of an acute health event. For example, the processing circuit may determine the location of patient 4 and determine the warning area 28 based on the patient's location. Computing devices 14A to 14N (collectively, "computing devices 14") are computing devices of one or more potential responders that are located within the warning area 28 and therefore close enough to the location of patient 4 to be capable of providing assistance to the patient having an acute health event. Potential responders are not necessarily known in advance to be potential responders or caregivers for patient 4 or any of the acute health events that patient 4 is experiencing. The processing circuit may send a warning to any computing device 14 located within the warning area 28, and the computing device 14 may present the warning to a user responder.

[0023]

[0029] In some examples, to determine a warning area, the processing circuit is configured to identify at least one of one or more cellular base stations 24 or one or more radio access points (WAPs) 26 that are within a threshold distance of the patient's location (or whose coverage area is within a threshold distance) based on the patient's location. The processing circuit may also be configured to control the transmission of warnings to any one or more computing devices 14 that are communicating with one or more cellular base stations or radio access points.

[0024]

[0030] In some examples, to determine a warning area, the processing circuit is configured to determine a geofence based on the location of patient 4 and a predetermined distance from patient 4. The processing may be configured to control the transmission of warnings to any one or more computing devices 14 within the geofence. This technique for issuing warnings to computing devices 14 within the warning area 28 may be mediated, for example, by a service provided by the processing circuit of the computing system 20. Computing devices 12 and 14 may have software applications for reporting the location of the computing devices to the service, which may determine which computing devices 14 are within the geofence and deliver warnings to those computing devices 14.

[0025]

[0031] The processing circuit may also provide warnings to one or more computing devices 18, which are not necessarily located within the warning area 28. The computing devices 18 may be associated with users predetermined to be responders or caregivers to patient 4 or any acute health event experienced by the patient, such as a treating clinician, family member, first responder, or other caregiver.

[0026]

[0032] The alert may provide various pieces of information to help the responder respond to an acute health event in patient 4. For example, the alert may include at least one of the following: the name or type of the acute health event, the onset time of the acute health event, or the elapsed time of the acute health event, and / or at least some of the physiological data of patient 4 received in the message from IMD10.

[0027]

[0033] The warning may include the location of patient 4. In some examples, the warning may cause or enable the computing device 14 to provide responder instructions to the location of patient 4.

[0028]

[0034] In some cases, the warning includes a treatment command for a health event, such as a cardiopulmonary resuscitation (CPR) command. In some cases, the processing circuit selects the treatment command to include in the warning based on the acute health event and / or physiological data contained in the message from IMD10.

[0029]

[0035] In some examples, the warning includes the location of a portable medical device configured to treat an acute health event, such as an automated external defibrillator (AED). In some examples, the warning may cause or enable the computing device 14 to provide responder instructions to the portable medical device.

[0030]

[0036] In some examples, in addition to the transmitted warning, the processing circuit may cause one or more computing devices 12 of patient 4 to provide warnings through their user interfaces. Such local warnings may be the same as or different from the transmitted warning. The local warnings may be configured, for example, to attract the attention of patient 4 and / or any person in close proximity to patient 4 audibly and / or visually.

[0031]

[0037] In some examples, patient 4 or a nearby caregiver may be able to provide an alert cancellation input via the user interface of one or more computing devices 12. The processing circuit may pause or terminate the local alert in response to the cancellation. The processing circuit may determine whether to send another alert or take other action based on whether it has not received a cancellation within a time interval from the start of the local alert. In some examples, instead of, or in addition to, a sent alert, the processing circuit is configured to control computing device 12 to make a call to an EMS 22, for example, an auto-dial 911. The call may be canceled by patient 4 or a nearby caregiver via the user interface of computing device 12.

[0032]

[0038] In some examples, the processing circuit is configured to perform an analysis to identify an acute health event, and based on the analysis, it may send or withhold warnings and / or calls. The analysis may be an analysis of physiological data received from IMD10 and / or physiological data collected by the patient 4's computing device 12, for example, computing device 12B. In some examples, the processing circuit of, for example, computing device 12 and / or computing system 20 may have higher processing power than IMD10, thereby enabling a more complex analysis of the physiological data. In some examples, the processing circuit may apply the physiological data to a machine learning model or other artificial intelligence to determine, for example, whether the physiological data sufficiently indicates an acute health event.

[0033]

[0039] Although described herein in the context of the exemplary IMD10, the techniques for detecting cardiac arrhythmias disclosed herein may be used in conjunction with other types of devices. For example, the techniques can be implemented using an extracardiac defibrillator coupled to an electrode outside the cardiovascular system, a transcatheter pacemaker configured to be implanted in the heart, such as the Micra® transcatheter pacing system commercially available from Medtronic PLC (Dublin, Ireland), a nerve stimulator, or a drug delivery device.

[0034]

[0040] Figure 2 is a block diagram showing the configuration of an example of the IMD10 shown in Figure 1A. As shown in Figure 2, the IMD10 comprises a processing circuit 50, a sensing circuit 52, a communication circuit 54, a memory 56, a sensor 58, a switching circuit 60, and electrodes 16A, 16B (hereinafter, "electrodes 16"), one or more of which may be located on the housing of the IMD10. In some examples, the memory 56 contains computer-readable instructions that, when executed by the processing circuit 50, cause the IMD10 and the processing circuit 50 to perform various functions attributed to the IMD10 and the processing circuit 50 as herein. The memory 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.

[0035]

[0041] The processing circuit 50 may include fixed-function circuits and / or programmable processing circuits. The processing circuit 50 may include one or more of the following: a microprocessor, a controller, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or equivalent individual or analog logic circuits. In some examples, the processing circuit 50 may include multiple components such as one or more microprocessors, one or more controllers, one or more DSPs, one or more ASICs, or one or more FPGAs, and other individual or integrated logic circuits. The functions attributed to the processing circuit 50 herein may be embodied as software, firmware, hardware, or any combination thereof.

[0036]

[0042] The sensing circuit 52 may be selectively coupled to electrodes 16A and 16B via a switching circuit 60, as controlled by the processing circuit 50. The sensing circuit 52 may monitor the electrical activity of the patient 4's heart in Figure 1A and the signals from electrodes 16A and 16B to generate ECG data for patient 4. In some examples, the processing circuit 50 may identify sensed ECG features such as heart rate, heart rate variability, heart rate interval, and / or ECG morphological features to detect episodes of cardiac arrhythmias in patient 4. The processing circuit 50 may store the digitized ECG and the ECG features used to detect arrhythmia episodes in memory 56 as episode data for the detected arrhythmia episodes.

[0037]

[0043] In some examples, the sensing circuit 52 measures the impedance of tissue adjacent to, for example, IMD 10 via the electrode 16. The measured impedance may vary based on the degree of respiration and perfusion or edema. The processing circuit 50 may determine physiological data regarding respiration, perfusion, and / or edema based on the measured impedance.

[0038]

[0044] In some examples, the IMD 10 includes one or more sensors 58, such as one or more accelerometers, microphones, optical sensors, temperature sensors, and / or pressure sensors. In some examples, the sensing circuit 52 may include one or more filters and amplifiers for filtering and amplifying signals received from one or more of the electrodes 16A, 16B, and / or other sensors 58. In some examples, the sensing circuit 52 and / or the processing circuit 50 may include a rectifier, a filter and / or an amplifier, a sensing amplifier, a comparator, and / or an analog-to-digital converter. The processing circuit 50 can determine physiological data, such as values ​​of physiological parameters of patient 4, based on signals from the sensors 58 which can be stored in memory 56.

[0039]

[0045] The processing circuit 50 may detect acute health events in patient 4 based on one or more combinations of the types of physiological data described herein. For example, the processing circuit 50 may detect cardiac arrest, ventricular fibrillation, ventricular tachycardia, or myocardial infarction based on an ECG and / or other physiological data indicating the electrical or mechanical activity of the heart 6 of patient 4 (Figure 1A). In some examples, the processing circuit 50 may detect a stroke based on such cardiac activity data. In some examples, the sensing circuit 52 may detect brain activity data, such as electroencephalography (EEG), via the electrodes 16, and the processing circuit 50 may detect a stroke or seizure based solely on brain activity, or in combination with cardiac activity data or other physiological data. In some examples, the processing circuit 50 may detect whether the patient has fallen based solely on data from the accelerometer, or in combination with other physiological data.

[0040]

[0046] In some examples, the processing circuit 50 transmits physiological data of an episode to a computing device 12 (Figure 1) via the communication circuit 54. Such transmissions may be daily or on other criteria. In some examples, if the episode is an acute health event, the processing circuit 50 transmits a message indicating the acute health event to one or more computing devices 12 via the communication circuit 54, as described herein. The transmission of the message may be done as quickly as possible, whenever necessary. The communication circuit 54 may include any suitable hardware, firmware, software, or any combination thereof for communicating with another device, such as the computing device 12, using an internal or external antenna, for example, antenna 30.

[0041]

[0047] Figure 3 is a conceptual side view showing the configuration of an example of the IMD10. In the example shown in Figure 3, the IMD10 may comprise a leadless, subcutaneously implantable monitoring device having a housing 72 and an insulating cover 74. Electrodes 16A and 16B may be formed or arranged on the outer surface of the cover 74. Circuits 50-56 and 60 described above with respect to Figure 2 may be formed or arranged on the inner surface of the cover 74 or within the housing 72. In the illustrated example, the antenna 30 is formed or arranged on the inner surface of the cover 74, but in some examples it may be formed or arranged on the outer surface. The sensor 58 may also be formed or arranged on the inner or outer surface of the cover 74 in some examples. In some examples the insulating cover 74 may be placed on an open housing 18 such that the housing 72 and cover 74 enclose the antenna 30, sensor 58, and circuits 50-56 and 60, protecting the antenna and circuits from fluids such as bodily fluids.

[0042]

[0048] One or more of the antenna 30, sensor 58, or circuits 50-56 may be formed on the insulating cover 74, for example, by using flip-chip technology. The insulating cover 74 can be inverted onto the housing 72. When inverted and placed on the housing 72, the components of the IMD 10 formed on the inside of the insulating cover 74 may be placed within a gap 76 defined by the housing 72. The electrode 16 can be electrically connected to the switching circuit 60 via one or more vias (not shown) formed through the insulating cover 74. The insulating cover 74 can be formed from sapphire (i.e., corundum), glass, parylene, and / or any other suitable insulating material. The housing 72 can be formed from titanium or any other suitable material (e.g., biocompatible material). The electrode 16 can be formed from stainless steel, titanium, platinum, iridium, or an alloy thereof. Furthermore, the electrode 16 can be coated with a material such as titanium nitride or fractal titanium nitride, but other suitable materials and coatings can be used on such electrodes.

[0043]

[0049] Figure 4 is a block diagram showing the configuration of an example of a computing device 12 for patient 4, and the computing device 12 can correspond to either (or both in cooperation with) the computing devices 12A and 12B shown in Figure 1A. In some examples, the external device 12 may take the form of a smartphone, laptop, tablet computer, personal digital assistant (PDA), smartwatch or other wearable computing device, smart home appliance such as a smart speaker, or any IoT device. As shown in the example in Figure 4, the computing device 12 comprises a processing circuit 80, a storage device 82, a communication circuit 84, a user interface 86, and in some examples, one or more sensors 88. Although shown as a standalone device in Figure 4 for illustrative purposes, the computing device 12 may be any component or system including a processing circuit for executing software instructions or other suitable computing environment, and does not necessarily have to include one or more elements shown in Figure 4 (for example, in some examples, components such as the storage device 82 may not be located in the same position as the other components or in the same enclosure).

[0044]

[0050] In one example, the processing circuit 80 is configured to implement functions and / or processing instructions for execution within the computing device 12. For example, the processing circuit 80 may be capable of processing instructions including an application 90 stored in the memory device 82. Examples of the processing circuit 80 may include one or more of the following: a microprocessor, a controller, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or equivalent individual or integrated logic circuits.

[0045]

[0051] The storage device 82 may be configured to store information, including the application 90 and data 100, within the computing device 12. In some examples, the storage device 82 is described as a computer-readable storage medium. In some examples, the storage device 82 includes temporary memory or volatile memory. Examples of volatile memory include random access memory (RAM), dynamic random access memory (DRAM), static random access memory (SRAM), and other forms of volatile memory known in the art. In one example, the storage device 82 is used by the application 90 running on the computing device 12 to temporarily store information during program execution. The storage device 82 also, in some examples, includes one or more memories configured for long-term storage of information, such as non-volatile storage elements. Examples of such non-volatile storage elements include magnetic hard disks, optical disks, floppy disks, flash memory, or electrically programmable memory (EPROM) or electrically erasable programmable memory (EEPROM).

[0046]

[0052] The computing device 12 communicates with other devices such as the IMD 10 in Figure 1B, other computing devices 12, and the computing system 20, using the communication circuit 84. The communication circuit 84 may include a network interface card such as an Ethernet card, an optical transceiver, a radio frequency transceiver, or any other type of device capable of sending and receiving information. Other examples of such network interfaces may include 3G, 4G, 5G, and WiFi radios.

[0047]

[0053] The computing device 12 also includes a user interface 86. The user interface 86 may be configured to provide output to the user using tactile, auditory, or visual stimuli and to receive input from the user through tactile, auditory, or visual feedback. The user interface 86 may include, for example, a presence-aware display, a mouse, a keyboard, a voice response system, a video camera, a microphone, or any other type of device for detecting commands from the user, a sound card, a video graphics adapter card, or any other type of device for converting signals into a suitable format understandable to humans or machines, a speaker, a cathode ray tube (CRT) monitor, a liquid crystal display (LCD), or any other type of device capable of producing user-understandable output. In some examples, the presence-aware display includes a touch-sensitive screen.

[0048]

[0054] Exemplary applications 90 executable by the processing circuit 80 of the computing device 12 include an IMD interface application 92, a monitoring system 94 that can utilize one or more machine learning models 96, and a location service 98. The execution of the IMD interface 92 by the processing circuit 80 configures the computing device 12 to interface with the IMD 10. For example, the IMD interface 92 configures the computing device 12 to communicate with the IMD 10 via a communication circuit 84. The processing circuit 80 can receive physiological data of patient 4 from the IMD 10 and store the physiological data in memory 82 as IMD data 102. In some examples, the processing circuit 80 receives physiological data from the IMD 10 along with a message indicating an acute health event. The IMD interface 92 also configures a user interface 86 for a user to interact with the IMD 10 and / or IMD data 102.

[0049]

[0055] The processing circuit 80 may, for example, run a monitoring system 94 to facilitate monitoring of the patient 4's health based on IMD data 102 10 and / or data collected by the computing device 12. The monitoring system 94 may cause the processing circuit 80 and the computing device 12 to perform any of the techniques described herein in relation to the detection of acute health events by the IMD 10.

[0050]

[0056] The processing circuit 80 may perform a location service 98 to determine the location of the computing device 12, thereby determining the estimated location of patient 4. The processing circuit 80 may use Global Positioning System (GPS) data, multilateration, and / or any other known techniques for locating the computing device. In some examples, the monitoring system 94 may use the location of patient 4 and geofence data to determine a warning area 88 as a geofence. The geofence area 106 may include different patient locations with different geofence distances from the patient for different acute health events or different expected population densities, and the monitoring system 94 may select a geofence distance based on such parameters.

[0051]

[0057] In some examples, as shown in Figure 4, the computing device may include one or more sensors 88 for sensing the physiological parameters or signals of the patient 4. The sensor(s) 88 may include electrodes and other sensors, as well as sensing circuits (e.g., including an ADC), as described above with respect to the IMD 10 and Figure 2. The processing circuit 80 may store the physiological data from the sensors 88 as computing device data 104 in the storage device 82.

[0052]

[0058] For example, computing device data 104 may include one or more of the following: activity level, walking / running distance, resting energy, activity energy, exercise time, orthostatic quantification, body weight, body mass index, heart rate, low, high, and / or irregular heart rate events, heart rate variability, walking heart rate, continuous heart rate, digitized ECG, blood oxygen saturation, blood pressure (systolic and / or diastolic), respiratory rate, maximum oxygen volume, blood glucose level, peripheral perfusion, and sleep pattern.

[0053]

[0059] The processing circuit 80 may also receive user-recorded health data via the user interface 86 and store such data as computing device data 104. User-recorded health data may include one or more of the following: exercise and activity data, sleep data, symptom data, medical history data, quality of life data, nutrition data, medication adherence data, allergy data, demographic data, weight, and height. Medical history data may include a history of cardiac arrest, tachyarrhythmia, myocardial infarction, stroke, seizure, chronic obstructive pulmonary disease (COPD), renal dysfunction, or hypertension, a history of procedures such as ablation or electrical defibrillation, and information related to healthcare use.

[0054]

[0060] In some examples, the processing circuit 80 runs the monitoring system 94 to perform an analysis to confirm the acute health event detected by the IMD 10, and delivers or suspends a warning and / or call based on the analysis. The analysis may be an analysis of the IMD data 102 and / or computing device data 104. In some examples, the monitoring system 94 applies the data to one or more machine learning models 96, other artificial intelligence, or other models or algorithms that do not necessarily require machine learning, such as linear regression, trend analysis, decision trees, or thresholding, to determine whether the data indicates an acute health event sufficiently to confirm the occurrence of an acute health event.

[0055]

[0061] Figure 5 is a block diagram showing the configuration of an example of a computing system 20. The computing system 20 may be any component or system including processing circuits or other suitable computing environments for executing software instructions, and does not necessarily have to include one or more elements shown in Figure 5 (for example, components such as the user interface device 204, communication circuit 206, and, in some examples, storage devices (there may be multiple) 208, do not have to be located in the same place as the other components or in the same enclosure). In some examples, the computing system 20 may be a cloud computing system distributed across multiple devices.

[0056]

[0062] In the example shown in Figure 5, the computing system 24 comprises a processing circuit 202, one or more user interface (UI) devices 204, a communication circuit 206, and one or more storage devices 208. In some examples, the computing system 20 further includes one or more applications 220, such as a monitoring system 222, which can be run by the computing system 20.

[0057]

[0063] In one example, the processing circuit 202 is configured to implement functions and / or processing instructions for execution within the computing system 20. For example, the processing circuit 202 may be capable of processing instructions stored in the memory device 208. Examples of the processing circuit 202 may include one or more of the following: a microprocessor, a controller, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or equivalent individual or integrated logic circuits.

[0058]

[0064] One or more storage devices 208 may be configured to store information within the computing device 20 during operation. In some examples, the storage device 208 is described as a computer-readable storage medium. In some examples, the storage device 208 is temporary memory, meaning that the primary purpose of the storage device 208 is not long-term storage. In some examples, the storage device 408 is described as volatile memory, meaning that when the computer is turned off, the storage device 408 does not retain the contents it has stored. Examples of volatile memory include random access memory (RAM), dynamic random access memory (DRAM), static random access memory (SRAM), and other forms of volatile memory known in the art. In some examples, the storage device 208 is used by software or applications 220 running on the computing system 20 to temporarily store information during program execution.

[0059]

[0065] The storage device 208 may be further configured for long-term storage of information such as the application 220 and data 230. In some examples, the storage device 208 includes non-volatile storage elements. Examples of such non-volatile storage elements include magnetic hard disks, optical disks, floppy disks, flash memory, or electrically programmable memory (EPROM) or electrically erasable programmable memory (EEPROM).

[0060]

[0066] In some examples, the computing system 20 also includes a communication circuit 206 for communicating with other devices and systems, such as the computing device 12 shown in Figures 1A and 1B. The communication circuit 206 may include a network interface card such as an Ethernet card, an optical transceiver, a radio frequency transceiver, or any other type of device capable of sending and receiving information. Other examples of such network interfaces may include 3G, 4G, 5G, and WiFi radio.

[0061]

[0067] In one example, the computing system 20 also includes one or more user interface devices 204. In some examples, the user interface devices 204 may be configured to provide output to the user using tactile, auditory, or visual stimuli and to receive input from the user through tactile, auditory, or visual feedback. The user interface devices 204 may, for example, include a presence-knowing display, a mouse, a keyboard, a voice response system, a video camera, a microphone, or any other type of device for detecting commands from the user, a sound card, a video graphics adapter card, or any other type of device for converting signals into a suitable format understandable to humans or machines, a speaker, a cathode ray tube (CRT) monitor, a liquid crystal display (LCD), or any other type of device capable of producing output understandable to the user.

[0062]

[0068] Application 220 may include program instructions and / or data executable by the processing circuit 202 of the computing system 20 in order to cause the computing system 20 to provide functions attributable to the processing circuit herein. An exemplary application (there may be more than one) 220 may include a monitoring system 222. Other additional applications not shown herein may be included alternatively or additionally to provide other functions described herein, but are not illustrated for the sake of simplification.

[0063]

[0069] According to the technology of this disclosure, the computing system 20 receives IMD data 102 and computing device data 104 from the computing device 12 via a communication circuit 206. The computing system 20 may also receive location data 232 indicating the location of patient 4 from the computing device 12 via the communication circuit 206. The processing circuit 202 stores these and geofence data 106 as data 230 in the storage device 208. The processing circuit 202 may run a monitoring system 222. The monitoring system 222 may be the same as the monitoring system 94 of the computing device 12, for example, the computing device 12 may primarily relay messages and data to the computing system 20 for the execution of the technology described herein, or it may operate in conjunction with the monitoring system 94 to facilitate any of the functions described herein.

[0064]

[0070] Figure 6 is a flowchart illustrating an example of a technique that provides a warning in response to the detection of an acute health event in a patient. The exemplary technique in Figure 6 is described as implementing, for example, a monitoring system 94, which is implemented by the processing circuit 80 of the computing device 12. In some examples, the processing circuit 202 of the computing system 20 may implement a monitoring system 222 to perform some or all of the functions of the exemplary technique.

[0065]

[0071] In the example shown in Figure 6, processing circuit 80 receives a wireless transmission message from IMD 10 indicating that patient 4 has experienced an acute health event (300). Processing circuit 80 analyzes physiological data in response to the message (302). The physiological data may include, for example, IMD data 102 received from IMD 10 as part of the message, and / or computing device data 104. If the computing device is configured to perform the exemplary technique, the computing device may sense the computing device data 104, or another computing device 12. For example, computing device 12A in Figure 1A, e.g., a smartphone, implements the exemplary technique of Figure 6 and can receive computing device data 104 from computing device 12B, e.g., a smartwatch or other wearable sensing and computing device. The analysis may include applying the physiological data to machine learning models, other artificial intelligence, or other models or algorithms that do not necessarily require machine learning, such as linear regression, trend analysis, decision trees, or thresholding.

[0066]

[0072] If the processing circuit 80 determines that no acute health event is detected by analysis (no in 304), the exemplary technique may terminate. If the processing circuit 80 determines that an acute health event is detected by analysis (yes in 304), the processing circuit 80 may present a local warning via the user interface 86 of the computing device 12 (306). The processing circuit 80 may start a timer. The processing circuit 80 may determine whether a user input to cancel the warning is received via the user interface within a predetermined time interval from the start of the warning (308). If the processing circuit 80 determines that a warning cancellation input has been received within a predetermined time interval (yes in 308), the local warning may be stopped and the exemplary technique may terminate. If the processing circuit 80 determines that no warning cancellation input has been received within a predetermined time interval (no in 308), the processing circuit 80 may transmit a warning, call the EMS, and / or take any other action described herein. For example, the processing circuit 80 may send a warning to one or more computing devices 14 of one or more potential responders in the warning area 88, and to one or more computing devices 18 of the patient's family or caregiver.

[0067]

[0073] Figure 7 is a flowchart illustrating an example technique for sending an alert to one or more computing devices 14 of potential responders within an alert area 88. According to the example shown in Figure 7, the processing circuit 80 of computing device 12 receives a radio transmission message from IMD 10 indicating that patient 4 has experienced an acute health event (300). In response to the message, the processing circuit 80 determines the location of patient 4, for example, by performing a location service 98 (402).

[0068]

[0074] The processing circuit 80 of the computing device 12 and / or the processing circuit 202 of the computing system 20 determine the warning area 28 based on the location of patient 4 (404). The processing circuit 80 and / or the processing circuit 202 transmit a warning to one or more computing devices 14 of any one or more potential responders within the warning area 28 (406).

[0069]

[0075] In some examples, to determine a warning area, the processing circuit is configured to identify at least one of one or more cellular base stations 24 or one or more radio access points (WAPs) 26 that are within a threshold distance of the patient's location (or whose coverage area is within a threshold distance) based on the patient's location. The processing circuit may also be configured to control the transmission of warnings to any one or more computing devices 14 that are communicating with one or more cellular base stations or radio access points.

[0070]

[0076] In some examples, to determine a warning area, the processing circuit is configured to determine a geofence based on the location of patient 4 and geofence data 106. The processing circuit may be configured to control the transmission of warnings to any one or more computing devices 14 within the geofence. This technique for issuing warnings to computing devices 14 within a warning area 28 can be facilitated by a monitoring system 222 performed by a processing circuit 202 of a computing system 20. Computing devices 12 and 14 may have software applications for reporting the location of the computing devices to the monitoring system 222, which may determine which computing devices 14 are within the geofence and deliver warnings to those computing devices 14.

[0071]

[0077] Example 1. A system comprising a processing circuit configured to receive a message wirelessly transmitted from a medical device, the message indicating that the medical device has detected an acute health event in a patient, and in response to the message, to determine the patient's location, determine a warning area based on the patient's location, and control the transmission of a warning of the patient's acute health event to any one or more computing devices of one or more potential responders within the warning area.

[0072]

[0078] Example 2. The system according to Example 1, wherein the medical device includes an implantable medical device.

[0073]

[0079] Example 3. The system according to Example 1 or 2, wherein the processing circuit includes a processing circuit for the patient's computing device.

[0074]

[0080] Example 4. The system according to Example 3, wherein the patient's computing device includes at least one of a smartphone, smartwatch, smart device, or Internet of Things device.

[0075]

[0081] Example 5. The system according to any one of Examples 1 to 4, wherein the acute health event includes at least one of cardiac arrest, ventricular fibrillation, ventricular tachycardia, myocardial infarction, stroke, seizure, or fall.

[0076]

[0082] Example 6. The system according to any one of Examples 1 to 5, wherein the warning includes at least one of the onset time of the acute health event or the elapsed time of the acute health event.

[0077]

[0083] Example 7. The system according to any one of Examples 1 to 6, wherein the message includes physiological data of a patient collected by a medical device, and the warning includes at least a portion of the physiological data.

[0078]

[0084] Example 8. The system described in any one of Examples 1-7, wherein the warning includes the patient's position.

[0079]

[0085] Example 9. The system according to any one of Examples 1 to 8, wherein the processing circuit is configured to select a treatment order based on an acute health event, and the warning includes a treatment order.

[0080]

[0086] Example 10. The system according to any one of Examples 1 to 9, wherein a warning includes the location of a portable medical device configured to treat an acute health event.

[0081]

[0087] Example 11. The system according to Example 10, wherein the portable treatment device includes an automated external defibrillator (AED).

[0082]

[0088] Example 12. The system according to any one of Examples 1 to 11, wherein, in order to determine a warning area, the processing circuit is configured to identify at least one of one or more cellular base stations or one or more radio access points based on the patient's location, and in order to control the transmission of a warning to any one or more computing devices communicating with one or more cellular base stations or radio access points, the processing circuit is configured to control the transmission of a warning to any one or more computing devices communicating with one or more cellular base stations or radio access points.

[0083]

[0089] Example 13. The system according to any one of Examples 1 to 12, wherein the processing circuit is configured to determine a geofence based on the patient's location in order to determine a warning area, and the processing circuit is configured to control the transmission of warnings to any one or more computing devices within the geofence in order to control the transmission of warnings to any one or more computing devices of one or more potential responders within the warning area.

[0084]

[0090] Example 14. The system according to any one of Examples 1 to 13, wherein the process is further configured to control the transmission of alerts of acute health events of the patient to any one or more computing devices of one or more caregivers or family members of the patient.

[0085]

[0091] Example 15. The system according to Example 3, combined with any of Examples 4 to 13, wherein the warning includes a first warning, and the processing circuit is configured to control the user interface of the patient's computing device to present a second warning.

[0086]

[0092] Example 16. The system according to Example 15, wherein the processing circuit is configured to determine whether a warning cancellation is received via the user interface within a time interval from the presentation of the second warning, and to control the transmission of the first warning based on the determination that a warning cancellation is not received within the time interval.

[0087]

[0093] Example 17. The system according to Example 3, combined with any of Examples 4-16, wherein the processing circuit is configured to control the patient's computing device to make a phone call to emergency medical services.

[0088]

[0094] Example 18. The system according to Examples 16 and 17, wherein the processing circuit is configured to control the computing device to make a call to emergency medical services based on the determination that a warning cancellation has not been received within a time interval.

[0089]

[0095] Example 19. The system according to Example 3, combined with any of Examples 4 to 18, wherein the message includes patient physiological data collected by a medical device, and the processing circuit is configured to analyze the physiological data and determine whether to control the transmission of a warning based on the analysis.

[0090]

[0096] Example 20. The system according to Example 19, wherein the patient's physiological data collected by a medical device includes the patient's first physiological data, the patient's computing device is configured to collect the patient's second physiological data, and a processing circuit is configured to analyze the patient's first and second physiological data in order to analyze the physiological data.

[0091]

[0097] Example 21. A method comprising: receiving a message wirelessly transmitted from a medical device, the message indicating that the medical device has detected an acute health event in a patient; determining the patient's location in response to the message; determining a warning area based on the patient's location; and controlling the transmission of a warning of the patient's acute health event to any one or more computing devices of one or more potential responders located within the warning area.

[0092]

[0098] Example 22. The method according to Example 21, wherein the medical device includes an implantable medical device.

[0093]

[0099] Example 23. The method according to Example 21 or 22, wherein the processing circuit includes a processing circuit for a patient's computing device.

[0094]

[0100] Example 24. The method according to Example 23, wherein the patient's computing device includes at least one of a smartphone, smartwatch, smart device, or Internet of Things device.

[0095]

[0101] Example 25. The method according to any one of Examples 21 to 24, wherein the acute health event includes at least one of cardiac arrest, ventricular fibrillation, ventricular tachycardia, myocardial infarction, stroke, seizure, or fall.

[0096]

[0102] Example 26. The method according to any one of Examples 21 to 25, wherein the warning includes at least one of the onset time of the acute health event or the elapsed time of the acute health event.

[0097]

[0103] Example 27. The method according to any one of Examples 21 to 26, wherein the message is physiological data of a patient collected by a medical device, and the warning includes at least a portion of the physiological data.

[0098]

[0104] Example 28. The method according to any one of Examples 21-27, wherein a warning is given regarding the patient's position.

[0099]

[0105] Example 29. The method according to any one of Examples 21 to 28, further comprising selecting a treatment order based on an acute health event, wherein the warning includes a treatment order.

[0100]

[0106] Example 30. The method according to any one of Examples 21-29, wherein a warning indicates the location of a portable medical device configured to treat an acute health event.

[0101]

[0107] Example 31. The method according to Example 30, wherein the portable treatment device includes an automated external defibrillator (AED).

[0102]

[0108] Example 32. The method according to any one of Examples 21 to 31, wherein determining a warning area includes identifying at least one of one or more cellular base stations or one or more radio access points based on the location of a patient, and controlling the transmission of a warning to any one or more computing devices of one or more potential responders in the warning area includes controlling the transmission of a warning to any one or more computing devices communicating with one or more cellular base stations or radio access points.

[0103]

[0109] Example 33. The method according to any one of Examples 21 to 32, wherein determining a warning area includes determining a geofence based on the patient's location, and controlling the transmission of warnings to any one or more computing devices of one or more potential responders within the warning area includes controlling the transmission of warnings to any one or more computing devices within the geofence.

[0104]

[0110] Example 34. The method according to any one of Examples 21 to 33, further comprising controlling the transmission of alerts of acute health events of the patient to any one or more computing devices of one or more caregivers or family members of the patient.

[0105]

[0111] Example 35. The method of Example 23 in combination with any of Examples 24-33, wherein the warning includes a first warning, and the method further includes controlling the user interface of the patient's computing device to present a second warning.

[0106]

[0112] Example 36. The method of Example 35, further comprising determining whether a warning cancellation is received via the user interface within a time interval from the presentation of a second warning, and controlling the transmission of a first warning based on the determination that a warning cancellation is not received within the time interval.

[0107]

[0113] Example 37. The method of Example 23, combined with any of Examples 24-36, further comprising controlling the patient's computing device to make a call to emergency medical services.

[0108]

[0114] Example 38. The method according to Examples 36 and 37, wherein the patient's computing device is controlled to call emergency medical services based on the determination that an alert cancellation is not received within a time interval.

[0109]

[0115] Example 39. The method of Example 23, combined with any of Examples 24-38, wherein the message includes physiological data of a patient collected by a medical device, and the method further includes analyzing the physiological data and determining whether to control the transmission of a warning based on the analysis.

[0110]

[0116] Example 40. The method according to Example 39, wherein the patient's physiological data collected by a medical device includes first physiological data of the patient, the patient's computing device is configured to collect second physiological data of the patient, and the analysis of the physiological data includes analyzing the patient's first and second physiological data.

[0111]

[0117] Example 41. A method comprising any combination of the methods of the examples described herein.

[0112]

[0118] Example 42. A system comprising a processing circuit configured to perform one or more of the methods described in Examples 21 to 41.

[0113]

[0119] Example 43. A non-temporary computer-readable storage medium comprising program instructions configured to cause a processing circuit to execute the method described in any one or more of Examples 21 to 41.

[0114]

[0120] It should be understood that the various embodiments disclosed herein may be combined in combinations different from those specifically presented in the description and accompanying drawings. It should also be understood that, depending on the embodiment, certain actions or events of any process or method described herein may be performed in a different order, added, combined, or omitted entirely (for example, not all described actions or events may be necessary to perform the technology). Furthermore, while certain embodiments of this disclosure are described for clarity as being performed by a single module, unit, or circuit, it should be understood that the technology of this disclosure may be performed, for example, by a combination of units, modules, or circuits related to a medical device.

[0115]

[0121] In one or more embodiments, the described techniques may be implemented in hardware, software, firmware, or any combination thereof. When implemented in software, the functions may be stored as one or more instructions or codes on a computer-readable medium and executed by a hardware-based processing unit. The computer-readable medium may include non-temporary computer-readable media corresponding to tangible media such as data storage media (e.g., RAM, ROM, EEPROM, flash memory, or any other medium that can be used to store desired program code in the form of instructions or data structures and that can be accessed by a computer).

[0116]

[0122] Instructions may be executed by one or more processors, such as digital signal processors (DSPs), general-purpose microprocessors, application-specific integrated circuits (ASICs), field-programmable logic arrays (FPGAs), or other equivalent integrated circuits or separate logic circuits. Therefore, the terms “processor” or “processing circuit” as used herein may refer to any of the aforementioned structures or any other physical structure suitable for implementing the described technology. Furthermore, the technology may be fully implemented by one or more circuits or logic elements.

[0117]

[0123] Various embodiments are described. These and other examples are within the scope of the claims below.

Claims

1. A system equipped with a processing circuit, A message transmitted wirelessly from a medical device, wherein the message indicates that the medical device has detected an acute health event in a patient, In response to the aforementioned message, Determine the position of the aforementioned patient, Based on the aforementioned position of the patient, the warning area is determined, Controlling the transmission of the patient's acute health event alert to any one or more computing devices of one or more potential responders within the warning area, To determine the aforementioned warning area, Based on the location of the patient, at least one of one or more cellular base stations or one or more wireless access points is identified. To control the transmission of the warning to any one or more computing devices of one or more potential responders within the warning area, control the transmission of the warning to any one or more computing devices communicating with the one or more cellular base stations or wireless access points, To determine the aforementioned warning area, Based on the aforementioned location of the patient, a geofence is determined, A system comprising a processing circuit configured to control the transmission of the warning to any one or more computing devices within the geofence in order to control the transmission of the warning to any one or more computing devices of any one or more potential responders within the warning area.

2. The system according to claim 1, wherein the medical device includes an implantable medical device.

3. The system according to claim 1, wherein the processing circuit includes a processing circuit for the patient's computing device.

4. The system according to claim 3, wherein the patient's computing device includes at least one of a smartphone, a smartwatch, a smart device, or an Internet of Things device.

5. The system according to claim 1, wherein the acute health event includes at least one of cardiac arrest, ventricular fibrillation, ventricular tachycardia, myocardial infarction, stroke, seizure, or fall.

6. The system according to claim 1, wherein the warning includes at least one of the onset time of the acute health event or the elapsed time of the acute health event.

7. The system according to claim 1, wherein the message includes physiological data of the patient collected by the medical device, and the warning includes at least a portion of the physiological data.

8. The system according to claim 1, wherein the warning includes the location of the patient.

9. The system according to claim 1, wherein the processing circuit is configured to select a treatment order based on the acute health event, wherein the warning includes a treatment order.

10. The system according to claim 1, wherein the warning includes the location of a portable medical device configured to treat the acute health event.

11. The system according to claim 10, wherein the portable treatment device includes an automated external defibrillator (AED).

12. The system according to claim 1, wherein the processing circuit is further configured to control the transmission of the warning of the acute health event of the patient to any one or more computing devices of one or more caregivers or family members of the patient.

13. The processing circuit, Receiving a message wirelessly transmitted from a medical device, the message indicating that the medical device has detected an acute health event in a patient, In response to the aforementioned message, Determining the position of the aforementioned patient, Determining the warning area based on the aforementioned position of the patient, Controlling the transmission of the patient's acute health event warning to any one or more computing devices of one or more potential responders within the warning area, To determine the aforementioned warning area, Based on the location of the patient, at least one of one or more cellular base stations or one or more wireless access points is identified. To control the transmission of the warning to any one or more computing devices of one or more potential responders within the warning area, this includes controlling the transmission of the warning to any one or more computing devices communicating with the one or more cellular base stations or wireless access points, To determine the aforementioned warning area, Based on the aforementioned position of the patient, a geofence is determined, To control the transmission of the warning to any one or more computing devices of one or more potential responders within the warning area, control the transmission of the warning to any one or more computing devices within the geofence. A method that includes this.

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