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WO2025008691A1 - Système de détection d'impact externe sur un patient - Google Patents

Système de détection d'impact externe sur un patient Download PDF

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Publication number
WO2025008691A1
WO2025008691A1 PCT/IB2024/055651 IB2024055651W WO2025008691A1 WO 2025008691 A1 WO2025008691 A1 WO 2025008691A1 IB 2024055651 W IB2024055651 W IB 2024055651W WO 2025008691 A1 WO2025008691 A1 WO 2025008691A1
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WIPO (PCT)
Prior art keywords
patient
change
threshold
posture
imd
Prior art date
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Pending
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PCT/IB2024/055651
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English (en)
Inventor
Hyun J. Yoon
Ryan D. WYSZYNSKI
Jerry D. REILAND
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Medtronic Inc
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Medtronic Inc
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Filing date
Publication date
Application filed by Medtronic Inc filed Critical Medtronic Inc
Publication of WO2025008691A1 publication Critical patent/WO2025008691A1/fr
Pending legal-status Critical Current
Anticipated expiration legal-status Critical

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Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Measuring devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb
    • A61B5/1116—Determining posture transitions

Definitions

  • the disclosure relates generally to medical systems and, more particularly, medical systems configured to monitor patient activity for changes in patient health.
  • Some types of medical systems may monitor various patient data, e.g., cardiac electrogram (EGM) data, of a patient to detect changes in health.
  • the medical system may monitor the cardiac EGM data to detect one or more types of arrhythmia, such as bradycardia, tachycardia (e.g., atrial tachycardia), fibrillation (e.g., atrial fibrillation), or asystole (e.g., caused by sinus pause or AV block).
  • the medical system may include one or more of an implantable medical device or a wearable device to collect the data.
  • a medical system may monitor physiological parameters of a patient.
  • Medical systems may include implantable or wearable medical devices and/or sensors configured to sense physiological parameters from the patient.
  • a patient may experience an external impact (e.g., as a result of a traffic collision, a collision with a person and/or an object, an impact with a projectile, effects of a nearby explosion, or the like).
  • the external force may cause the patient to experience medical conditions (e.g., contusions, concussions, fractures to bones, cardiac conditions, cranial conditions) which may require medical aid rendered by a medical care provider (e.g., a clinician, an emergency medical services (EMS) provider).
  • EMS emergency medical services
  • the medical care provider may be delayed in receiving a notification indicating that the patient requires medical aid.
  • the medical system may determine that the patient experiences an external force based on changes to the physiological parameters and transmit a notification in response to the determination.
  • the medical system may detect a change in one or more physiological parameters and compare the change in the physiological parameters against a threshold condition (e.g., a threshold amount of change) to determine whether the patient experienced an external force.
  • the medical system may determine that the patient experienced an external force by detecting a threshold amount of change in the acceleration experienced by the patient (e.g., in terms of g-forces on the patient), a threshold change in posture of the patient, and/or other metrics indicative of the application of an external force on the body of the patient.
  • the threshold conditions may correspond to a magnitude of the external force and may be used by the medical system to only detect external forces of sufficient magnitude.
  • the medical system may detect occurrences of external force on the patient without requiring signals and/or data from computing devices or computing systems external to the medical system.
  • the medical system may include an implantable medical device (IMD) such as an implantable cardiac monitor (ICM).
  • IMD implantable medical device
  • ICM implantable cardiac monitor
  • the medical system described herein may provide several advantages over other medical systems.
  • the medical system described herein may include sensors positioned on or within the patient at locations that may increase the detection accuracy of sensors (e.g., accelerometers) relative to other medical systems, e.g., may allowing the sensors to sense multi-directional sensing vectors corresponding to movement of the patient.
  • the medical system may allow for the accurate impact detection without requiring additional implantable, wearable, or external sensors outside of the medical system.
  • the medical system may distinguish between different types of external force and provide the information to medical care providers to facilitate the delivery of medical aid to the patient.
  • the medical system may automatically adjust threshold conditions for the impact detection process, thereby maintaining and/or increasing the accuracy of the detections made by the medical system.
  • external impacts may lead to downstream effects on the health of the patient after a period of time (e.g., days, weeks, months, years) following the external impact, such as additional health issues.
  • information regarding the external impact may be used to inform a clinician of the cause, severity, or treatment of the additional health issues.
  • an external impact near a heart of a patient may negatively affect the heart of the patient and potentially contribute to cardiac-related health issues experienced by the patient in the future.
  • the medical system described herein may store information corresponding to a detected and/or confirmed external impact and may output the stored information (e.g., in response to a request from a clinician) at a later time (e.g., days, weeks, months, years after the external impact).
  • the medical system may provide information corresponding to a prior external impact which contributed to a health issue in response to detection of the health issue, thereby improving the accuracy of diagnosis and/or the efficacy of treatment or of prophylactic measures against the health issue.
  • the disclosure describes an implantable medical device (IMD) configured to be implanted within a patient, the IMD comprising: a plurality of sensors comprising an accelerometer; communications circuitry; and processing circuitry coupled to the plurality of sensors and to the communications circuitry, the processing circuitry being configured to: determine, based on sensed data from the accelerometer, a change in acceleration experienced by the patient and a change in posture of the patient; determine that the change in acceleration satisfies a first threshold condition; and that the change in posture satisfies a second threshold condition; and based on a determination that the change in acceleration satisfies the first threshold condition and that the change in posture satisfies the second threshold condition, cause the communications circuitry to transmit a notification indicating the occurrence of an external impact.
  • IMD implantable medical device
  • the disclosure describes a system comprising: an implantable medical device (IMD) configured to be implanted within a patient, the IMD comprising: a plurality of sensors comprising an accelerometer; an external computing device comprising a user interface; and processing circuitry configured to: receive, from the IMD, sensed data corresponding to values for a plurality of physiological parameters of the patient, the plurality of physiological parameters comprising an acceleration detected by the accelerometer of the IMD; determine, based on the received sensed data, changes to one or more physiological parameters of the plurality of physiological parameters, wherein the changes to the one or more physiological parameters comprises one or more of a change in acceleration experienced by the patient or a change in posture of the patient; compare the changes to each of the one or more physiological parameters to a correspond threshold condition of one or more threshold conditions; and based on a determination that the changes to the one or more physiological parameters satisfy at least one threshold condition of the one or more threshold conditions, cause the external computing device to display a notification to the patient via the user interface.
  • IMD implantable medical device
  • a method for operating a medical system comprising an implantable medical device (IMD), the method comprising: sensing, via a plurality of sensors of the IMD configured to be implanted within a patient, information corresponding to a plurality of physiological parameters of the patient, wherein the plurality of sensors comprises an accelerometer; determining, by processing circuitry of the medical system and based on sensed information, changes to one or more physiological parameters of the plurality of physiological parameters, wherein the changes to the one or more physiological parameters comprise one or more of a change in acceleration experienced by the patient or a change in a posture of the patient; comparing, by the processing circuitry, the changes to each of the one or more physiological parameters to a corresponding threshold condition of one or more threshold conditions; and based on a determination that the changes to the one or more physiological parameters satisfy at least one threshold condition of the one or more threshold conditions, transmitting, by the processing circuitry and via communications circuitry of the IMD, a notification to a computing device.
  • IMD implantable medical device
  • a computer-readable medium comprising instructions that, when executed, causes processing circuitry to: sense, via a plurality of sensors of the IMD configured to be implanted within a patient, information corresponding to a plurality of physiological parameters of the patient, wherein the plurality of sensors comprises an accelerometer; determine, based on sensed information, changes to one or more physiological parameters of the plurality of physiological parameters, wherein the changes to the one or more physiological parameters comprise one or more of a change in acceleration experienced by the patient or a change in a posture of the patient; compare the changes to each of the one or more physiological parameters to a corresponding threshold condition of one or more threshold conditions; and based on a determination that the changes to the one or more physiological parameters satisfy at least one threshold condition of the one or more threshold conditions, transmit, via communications circuitry of the IMD, a notification to a computing device.
  • FIG. 1 illustrates an example medical system including an IMD in conjunction with a patient, in accordance with one or more examples of the present disclosure.
  • FIG. 2A is a perspective drawing illustrating an example IMD.
  • FIG. 2B is a perspective drawing illustrating another example IMD.
  • FIG. 3 is a block diagram illustrating an example configuration of an IMD.
  • FIG. 4 is a block diagram illustrating an example configuration of a computing device that operates in accordance with one or more techniques of the present disclosure.
  • FIG. 5 is a block diagram illustrating an example configuration of a health monitoring system that operates in accordance with one or more techniques of the present disclosure.
  • FIG. 6 is a flowchart illustrating an example process of determining that a patient has experienced an external impact.
  • FIG. 7 is a flowchart illustrating another example process of determining that a patient has experienced an external impact.
  • Patients may experience collisions that may cause injuries to the patient.
  • collisions include, but are not limited to, motor vehicle collisions, collisions between the patient and a person or object, or activities that may subject the patient to relatively high changes in acceleration (e.g., causing the patient to experience at least a threshold g-force) or relatively sudden changes in the acceleration and with or without postural changes.
  • the collision may apply an external force or an external impact to the patient that may cause injuries.
  • the injuries may include, but are not limited to, lacerations, contusions, bone fractures, concussions, cardiac conditions, cranial conditions, neurological conditions, or the like. The effects of the injuries may be readily apparent or may not be observable by the patient and/or other persons.
  • patient may require prompt medical aid rendered by a medical care provider (e.g., an emergency medical services (EMS) provider).
  • EMS emergency medical services
  • the patient may be unable to contact a medical care provider and request medical aid.
  • the patient may suffer injuries that may not be observable but which may worsen over time or increase the risk of additional injuries.
  • the patient may not visit a clinician due to the lack of overt injuries or symptoms of injuries, which may allow the injuries to worsen or lead to more severe injuries or delayed critical symptoms.
  • This disclosure describes example medical devices, medical systems, and techniques for detecting external forces or impacts on the patient based on changes to physiological parameters detected by an example medical device or medical system
  • the medical system may output a notification indicating that the patient has experienced an external impact to a computing device of the patient and/or to one or more third parties (e.g., caretaker(s), clinician(s), medical care provider(s)).
  • third parties e.g., caretaker(s), clinician(s), medical care provider(s)
  • the medical system described in this disclosure may provide several benefits over other medical systems.
  • the medical system may include sensors and/or IMDs positioned on or within the patient at locations that may increase the detection accuracy of the medical system.
  • the medical system may allow for the accurate impact detection without requiring additional implantable, wearable, or external sensors outside of the medical system.
  • the medical system may distinguish between different types of external force and provide the type of the external force to the third parties to facilitate the delivery of appropriate medical aid to the patient.
  • the medical system may automatically adjust threshold conditions for the impact detection process, thereby maintaining and/or increasing the accuracy of the detections made by the medical system as the physiology of the patient changes over time.
  • IMD 104 is configured for continuous, long-term monitoring of patient 102.
  • IMD 104 is configured to sense cardiac signals form the heart of patient 102.
  • Continuous monitoring and/or sensing by IMD 104 may include monitoring and/or sensing on a triggered or periodic basis, without requiring user or clinician intervention.
  • IMD 104 may include an implantable cardiac monitor (ICM), implantable pacemaker, or implantable cardioverter, which may be coupled to intravascular or extravascular leads, or to a pacemaker with a housing configured for implantation within the heart, which may be leadless.
  • ICM implantable cardiac monitor
  • implantable pacemaker or implantable cardioverter
  • IMD 104 may be a Reveal LINQTM or LINQ IITM ICM, available from Medtronic, Inc., of Minneapolis, Minnesota, which may be inserted subcutaneously. Such IMDs may facilitate relatively longer-term and continuous monitoring of patients during normal daily activities, and may periodically transmit collected data to a remote patient monitoring system , such as the Medtronic CarelinkTM Network.
  • a remote patient monitoring system such as the Medtronic CarelinkTM Network.
  • IMD 104 may determine values of physiological parameters of patient 102 based on physiological signals sensed by sensors on, within, or coupled to IMD 104.
  • Physiological parameters may include, but are not limited to, a posture of patient 102, acceleration of the body (e.g., of the torso) of patient 102, a g-force on patient 102, a heart rate of patient 102, a respiration rate of patient 102, a stress hormone level of patient 102, a body temperature of patient 102, glucose level of patient 102, blood pressure of patient 102, electroencephalogram (EEG) signals of patient 102, change in electrocardiogram (ECG) morphology of patient 102, change in electrogram (EGM) morphology of patient 102, impedance between two or more locations on patient 102, a blood oxygen saturation of patient 102, or a rate of change of a physiological parameter (e.g., a rate of change in heart rate, body temperature, respiration rate, and/or blood oxygen saturation).
  • IMD 104 may determine a posture of patient 102 (e.g., whether patient 102 is sitting, standing, lying down, prone, crouching) based on sensed physiological signals from sensors (e.g., accelerometers, gyroscopes, inertial measurement units (IMU)) within or connected to IMD 104.
  • sensors e.g., accelerometers, gyroscopes, inertial measurement units (IMU)
  • IMU inertial measurement units
  • IMD 104 may compare changes in physiological parameters against a threshold condition stored in IMD 104.
  • IMD 104 may determine a change in the values of a physiological parameter by comparing a determined physiological parameter value against an average (and dynamic or accumulative or fixed duration average) physiological parameter value or against a previous determined physiological parameter value.
  • IMD 104 may determine that patient 102 has experienced an external impact or external force based on the determination based on a determination that changes in the values of one or more physiological parameters satisfy corresponding threshold conditions (e.g., a minimum threshold amount of change).
  • a threshold amount of change may include, but are not limited to, a threshold change in acceleration, a threshold change in g-force, a change in posture of patient 102 from a first posture to a second posture in a threshold amount of time, a threshold change in heart rate, a threshold change in respiration rate, a morphology change in EGM, a threshold change in blood oxygen saturation, or the like.
  • system 100 includes one or more patient computing devices 106A, 106B (collectively referred to herein as “patient computing devices 106”).
  • Patient computing devices 106 are configured for wireless communication with IMD 104.
  • Patient computing devices 106 may retrieve physiological parameter data (e.g., physiological signals, physiological parameter values) from IMD 104.
  • Patient computing devices 106 e.g., patient computing device 106A
  • patient computing device 106B may be worn by patient 102.
  • Patient computing devices 106 may be any computing device configured for wireless communication with IMD 104, such as a desktop computer, a laptop computer, a tablet, a smartwatch, or a smartphone. Patient computing devices 106 may communicate with IMD 104 and with another patient computing device 106 according to a wireless communication protocol (e.g., according to Bluetooth® or Bluetooth® Low Energy (BLE) protocols). Wearable patient computing device 106B may include sensors (e.g., electrodes, oximeters, accelerometers) configured to sense physiological signals of patient 102 and may collect and store physiological parameter values based on the sensed physiological signals.
  • sensors e.g., electrodes, oximeters, accelerometers
  • One or more of patient computing devices 106 may be configured to communicate with a variety of other devices or systems via a network 108.
  • one or more of patient computing devices 106 may be configured to communicate with one or more computing systems (e.g., computing system 110) via network 108.
  • Computing system 110 may provide cloud storage and analysis of physiological signals and/or physiological parameter values, maintenance, software services, or other networked functionality for patient computing devices 106 and/or IMD 104.
  • computing system 110 may include or maybe implemented by the Medtronic CarelinkTM Network.
  • IMD 104 may transmit a notification to patient computing devices 106 or computing system 100 via network 108 and patient computing devices 106.
  • IMD 104 may transmit the notification in response to determining that patient 102 has experienced an external impact.
  • the notification may indicate that patient 102 has experienced an external impact, physiological parameter values, and/or changes in physiological parameter values.
  • patient computing devices 106 may receive physiological parameter values and/or physiological signals from IMD 104.
  • Patient computing devices 106 may determine, based on the receive values and/or signals, that patient 102 experienced an external impact (e.g., by comparing changes in the physiological parameter values against a threshold condition).
  • Patient computing devices 106 may then transmit the notification indicating that patient 102 has experienced an external impact to computing system 110 via network 108.
  • Patient computing devices 106 may transmit data including data retrieved from IMD 104, to computing system 110 via network 108.
  • the data may include sensed data, e.g., values of physiological parameters measured by IMD 104 and/or patient computing devices 106.
  • Computing system 110 may include processing circuitry 112 and memory 114.
  • Processing circuitry 112 may include fixed function circuitry and/or programmable processing circuitry.
  • Processing circuitry 112 may include any one or more of a microprocessor, a controller, a digital signal processor (DSP), graphics processing unit (GPU), tensor processing unit (TPU), an application specific integrated circuitry (ASIC), a field-programmable gate array (FPGA), or equivalent discrete or analog logic circuitry.
  • DSP digital signal processor
  • GPU graphics processing unit
  • TPU tensor processing unit
  • ASIC application specific integrated circuitry
  • FPGA field-programmable gate array
  • processing circuitry 112 may include multiple components, such as any combination of one or more microprocessors, one or more controllers, one or more DSPs, GPUs, TPUs, one or more ASICs, or one or more FPGAs, as well as other discrete or integrated logic circuitry, which may be physically located in one or more devices in one or more physical locations.
  • Computing system 110 may be configured as a cloud computing system.
  • Processing circuitry 112 may be capable of processing instructions stored in memory 114.
  • memory 114 includes a computer-readable medium that includes instructions that, when executed by processing circuitry 112, cause computing system 110 and processing circuitry 112 to perform various functions attributed to them herein. In the example illustrated in FIG.
  • computing system 110 implements a health monitoring system (HMS) 116.
  • HMS 116 may determine whether patient 102 has experienced an external impact based on sensed physiological signals or physiological parameter values from IMD 104.
  • Memory 114 may include any volatile, non-volatile, magnetic, optical, or electrical media, such as a randomaccess memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), electrically-erasable programmable ROM (EEPROM), ferroelectric RAM (FRAM), dynamic random-access memory (DRAM), flash memory, or any other digital media.
  • RAM randomaccess memory
  • ROM read-only memory
  • NVRAM non-volatile RAM
  • EEPROM electrically-erasable programmable ROM
  • FRAM ferroelectric RAM
  • DRAM dynamic random-access memory
  • flash memory or any other digital media.
  • Network 108 may include one or more computing devices, such as one or more non-edge switches, routers, hubs, gateways, security devices such as firewalls, intrusion detection, and/or intrusion prevention devices, servers, cellular bast stations and nodes, wireless access points, bridges, cable modems, application accelerators, or other network devices.
  • Network 108 may include one or more networks administered by service providers, and may thus form part of a large-scale public network infrastructure, e.g., the Internet.
  • Network 108 may provide computing devices and systems, such as those illustrated in FIG. 1, access to the Internet, and may provide a communication framework that allows the computing devices and systems illustrated in FIG. 1 to communicate with each other, but isolates some of the data flows from devices external to the private network for security purposes. In some examples, the communications between the computing devices and systems illustrated in FIG. 1 are encrypted.
  • IMD 104 may be configured to transmit physiological parameters values and/or determinations of whether patient 102 has experienced an external impact to wireless access point 124 and/or patient computing devices 106. Wireless access point 124 and/or patient computing devices 106 may then communicate the retrieved data to computing system 110 via network 108.
  • computing system 110 may be configured to provide a secure storage site for data that has been collected from IMD 104 and/or patient computing devices 106.
  • Computing system 110 may include a database that stores medical-related and health-related data.
  • computing system 110 includes a cloud server or other remote serve that stores data collected from IMD 104 and/or patient computing devices 106.
  • Computing system 110 may assemble data in webpages or other documents for viewing by trained clinicians, such as clinicians 130, via clinician computing devices 128.
  • Clinicians 130 may include, but are not limited to, medical care providers and emergency medical services (EMS) providers.
  • One or more aspects of the system 100 illustrated in FIG. 1 may be implemented with general network technology and functionality, which may be similar to that provided by the Medtronic CareLink® Network.
  • clinician computing devices 128 may be a tablet, smartphone, laptop computer, desktop computer, or other computing device associated with one or more of clinicians 130, by which one or more clinicians 130 may program, receive notifications from, and/or interrogate IMD 104.
  • one or more of clinicians 130 may access data collected by IMD 104 and/or patient computing devices 106 through a clinician computing device 128, such as when clinician computing device 128 receives a notification from IMD 104, patient computing devices 106, and/or computing systems 110 indicating that patient 102 has experienced an external impact.
  • Clinician 130 may determine, based on the data accessed through clinician computing device 128, whether patient 102 may require medical aid.
  • the data and notification transmitted to clinician computing device 128 may facilitate the provision of medical aid by one or more clinicians 130 to patient 102.
  • Focal network 122 may facilitate communication between patient computing devices 106 and other computing devices and systems (e.g., computing system 110, HMS 116) connected to network 108.
  • Local network 112 may be configured with wireless technology, such as IEEE 802.11 wireless networks, IEEE 802,15 ZigBee networks, an ultra-wideband protocol, near-field communications, or the like.
  • Local network 122 may include one or more wireless access points 124 configured to provide support for wireless communications throughout an environment encompassing local network 122.
  • patient computing devices 106 may communicate with network 108 (e.g., with HMS 116), via a cellular base station and/or cellular network.
  • System 100 may determine whether patient 102 has experienced an external impact.
  • System 100 may determine changes in one or more physiological parameters (e.g., changes in acceleration experienced by patient 102, changes in g-force on patient 102, changes in posture of patient 102, changes in heart rate of patient 102, changes in respiration rate of patient 102, changes in blood oxygen saturation of patient 102).
  • System 100 may determine a presence of and a magnitude of a change in one or more physiological parameters by comparing a currently determined physiological parameter value against an average physiological parameter value or a previously determined physiological parameter value.
  • System 100 may adjust average physiological parameters values over time based on changes in sensed physiological parameters or based on instructions to adjust the average values, e.g., in response to changes in physiology of patient 102.
  • System 100 may compare change(s) in physiological parameters against threshold conditions and determine that patient 102 has experienced an external impact based on a determination that the change(s) in physiological parameters satisfy at least one threshold condition. In some examples, system 100 may determine that a change in acceleration experienced by patient 102 satisfies a threshold change in acceleration by determining that the change in acceleration is greater than or equal to the threshold change in acceleration. In some examples, system 100 may determine that a change in posture of patient 102 satisfies a threshold condition by determining that patient 102 transitions from a first posture to a second posture over a time period less than or equal to a threshold amount of time.
  • Threshold conditions may be stored in system 100 and may be used by system 100 to filter out false-positive occurrences of external forces and/or external forces or relatively low magnitude.
  • system 100 is configured to monitor for external forces or impacts such as vehicle collisions and may store threshold conditions selected to cause system 100 to avoid detecting lower-magnitude external forces or impacts (e.g., a fall or the like).
  • System 100 may determine a severity of the external impact based on a magnitude of the change of one or more physiological parameters and/or a number of changes in physiological parameters that satisfy threshold conditions.
  • system 100 determines that a first external force corresponding to a first change in acceleration experienced by patient 102 is more severe that a second external force corresponding to a smaller change in acceleration experienced by patient 102. In some examples, system 100 determines that first external force corresponding to at least a threshold change in acceleration experienced by patient 102 and a threshold change in posture of patient 102 is more severe than a second external force corresponding only to a threshold change in acceleration experienced by patient 102.
  • System 100 may, in response to determining that patient 102 has experienced an external impact, transmit a notification to one or more of patient computing devices 106, computing system 110, and/or clinician computing devices 128.
  • the notification may include, but are not limited to, an indication that patient 102 has experienced an external impact, a severity of the detected external impact (e.g., in terms of a relative severity such as a relative score, in terms of an absolute severity such as a magnitude of the force or impact, e.g., in joules (J)), physiological parameter values preceding, during, and/or following the external impact, and/or determined changes in the physiological parameter values corresponding to the external impact.
  • a severity of the detected external impact e.g., in terms of a relative severity such as a relative score, in terms of an absolute severity such as a magnitude of the force or impact, e.g., in joules (J)
  • physiological parameter values preceding, during, and/or following the external impact e.g., in joules (J
  • the notification may include medical information of patient 102 and/or location data of patient 102, e.g., to facilitate delivery of medical aid to patient 102 in response to the external impact.
  • an external impact may have long-term effects on the user and may at least contribute to medical events experienced by the user in the future.
  • System 100 may store information corresponding to the external impact and may output the information at a later time to facilitate determination of the type, cause, severity, and/or treatment of one or more medical events experienced by the user in the future.
  • system 100 may transmit a notification after a threshold period of time has passed and/or when one or more of certain medical events occur within a threshold period of time of an external impact.
  • the threshold period of time may be a threshold number of days, weeks, months, or years after detection of an external impact.
  • System 100 may transmit the notification after system 100 determines or receives an indication that the user is experiencing a medical event.
  • the notification may include information corresponding to the prior external impact, a likelihood of the prior external impact contributing or causing the current medical event, and/or recommended courses of action to alleviate or treat the medical event.
  • the notification of the impact may supplement a notification regarding the medical event in some examples.
  • IMD 104A is a perspective drawing illustrating an IMD 104A, which may be an example configuration of IMD 104 of FIG. 1 as an ICM.
  • IMD 104A may be embodied as a monitoring device having housing 202, proximal electrode 206A and distal electrode 206B.
  • Housing 202 may further comprise first major surface 204, second major surface 208, proximal end 210, and distal end 212.
  • Housing 202 encloses electronic circuitry located inside the IMD 104A and protects the circuitry contained therein from body fluids.
  • Housing 202 may be hermetically sealed and configured for subcutaneous implantation. Electrical feedthroughs provide electrical connection of electrodes 206A and 206B .
  • IMD 104A is defined by a length L, a width W and thickness or depth D and is in the form of an elongated rectangular prism wherein the length L is much larger than the width W, which in turn is larger than the depth D.
  • the geometry of the IMD 104 A - in particular a width W greater than the depth D - is selected to allow IMD 104A to be inserted under the skin of the patient using a minimally invasive procedure and to remain in the desired orientation during insertion.
  • the device shown in FIG. 2A includes radial asymmetries (notably, the rectangular shape) along the longitudinal axis that maintains the device in the proper orientation following insertion.
  • the spacing between proximal electrode 206A and distal electrode 206B may range from 5 millimeters (mm) to 55 mm, 30 mm to 55 mm, 35 mm to 55 mm, and from 40 mm to 55 mm and may be any range or individual spacing from 5 mm to 60 mm.
  • IMD 104 A may have a length L that ranges from 30 mm to about 70 mm. In other examples, the length L may range from 5 mm to 60 mm, 40 mm to 60 mm, 45 mm to 60 mm and may be any length or range of lengths between about 30 mm and about 70 mm.
  • the width W of major surface 204 may range from 3 mm to 15, mm, from 3 mm to 10 mm, or from 5 mm to 15 mm, and may be any single or range of widths between 3 mm and 15 mm.
  • the thickness of depth D of IMD 104 A may range from 2 mm to 15 mm, from 2 mm to 9 mm, from 2 mm to 5 mm, from 5 mm to 15 mm, and may be any single or range of depths between 2 mm and 15 mm.
  • IMD 104A according to an example of the present disclosure is has a geometry and size designed for ease of implant and patient comfort.
  • Examples of IMD 104A described in this disclosure may have a volume of three cubic centimeters (cm) or less, 1.5 cubic cm or less or any volume between three and 1.5 cubic centimeters.
  • the first major surface 204 faces outward, toward the skin of the patient while the second major surface 208 is located opposite the first major surface 204.
  • proximal end 210 and distal end 212 are rounded to reduce discomfort and irritation to surrounding tissue once inserted under the skin of the patient.
  • IMD 104 A including instrument and method for inserting IMD 104 A is described, for example, in U.S. Patent No. 11311312, entitled filed on March 11, 2014, issued on April 26, 2022, and entitled “Subcutaneously Delivery Tool”, the entirety of which is herein incorporated by reference in its entirety.
  • Proximal electrode 206 A is at or proximate to proximal end 210, and distal electrode 206B is at or proximate to distal end 212.
  • Proximal electrode 206 A and distal electrode 206B are used to sense cardiac signals, e.g., ECG signals, and measure interstitial impedance thoracically outside the ribcage, which may be sub-muscularly or subcutaneously.
  • ECG signals and impedance measurements may be stored in a memory of IMD 104 A, and data may be transmitted via integrated antenna 216A to another device, which may be another implantable device or an external device, such as one or more of patient computing devices 106.
  • electrodes 206A and 206B may additionally or alternatively be used for sensing any bio-potential signal of interest, which may be, for example, an electrogram (EGM), EEG, electromyogram (EMG), or a nerve signal, from any implanted location.
  • Housing 202 may house the circuitry of IMD 104 as illustrated in FIG. 3.
  • proximal electrode 206A is at or in close proximity to the proximal end 210 and distal electrode 206B is at or in close proximity to distal end 212.
  • distal electrode 206B is not limited to a flattened, outward facing surface, but may extend from first major surface 204 around rounded edges 222 and/or end surface 214 and onto the second major surface 208 so that the electrode 206B has a three-dimensional curved configuration.
  • electrode 206B is an uninsulated portion of a metallic, e.g., titanium, part of housing 202.
  • proximal electrode 206A is located on first major surface 204 and is substantially flat, and outward facing.
  • proximal electrode 206A may utilize the three dimensional curved configuration of distal electrode 206B, providing a three dimensional proximal electrode (not shown in this example).
  • distal electrode 206B may utilize a substantially flat, outward facing electrode located on first major surface 204 similar to that shown with respect to proximal electrode 206A.
  • proximal electrode 206A and distal electrode 206B are located on both first major surface 204 and second major surface 208.
  • proximal electrode 206A and distal electrode 206B are located on both major surfaces 204 and 208.
  • both proximal electrode 206A and distal electrode 206B are located on one of the first major surface 204 or the second major surface 208 (e.g., proximal electrode 206A located on first major surface 204 while distal electrode 206B is located on second major surface 208).
  • IMD 104A may include electrodes on both major surface 204 and 208 at or near the proximal and distal ends of the device, such that a total of four electrodes are included on IMD 104A.
  • Electrodes 206A and 206B may be formed of a plurality of different types of biocompatible conductive material, e.g. stainless steel, titanium, platinum, iridium, or alloys thereof, and may utilize one or more coatings such as titanium nitride or fractal titanium nitride.
  • proximal end 210 includes a header assembly 218 that includes one or more of proximal electrode 206A, integrated antenna 216A, anti-migration projections 221, and/or suture hole 220.
  • Integrated antenna 216A is located on the same major surface (i.e., first major surface 114) as proximal electrode 206A and is also included as part of header assembly 218.
  • Integrated antenna 216A allows IMD 104A to transmit and/or receive data.
  • integrated antenna 216A may be formed on the opposite major surface as proximal electrode 206A, or may be incorporated within the housing 202 of IMD 104A. In the example shown in FIG.
  • anti-migration projections 221 are located adjacent to integrated antenna 216A and protrude away from first major surface 204 to prevent longitudinal movement of the device.
  • anti-migration projections 221 include a plurality (e.g., nine) small bumps or protrusions extending away from first major surface 204.
  • anti-migration projections 221 may be located on the opposite major surface as proximal electrode 206A and/or integrated antenna 216A.
  • header assembly 218 includes suture hole 220, which provides another means of securing IMD 104 A to the patient to prevent movement following insertion.
  • header assembly 218 is a molded header assembly made from a polymeric or plastic material, which may be integrated or separable from the main portion of IMD 104A.
  • FIG. 2B is a perspective drawing illustrating another IMD 104B, which may be another example configuration of IMD 104 from FIG. 1 as an ICM.
  • IMD 104B of FIG. 2B may be configured substantially similarly to IMD 104A of FIG. 2A, with differences between them discussed herein.
  • IMD 104B may include a leadless, subcutaneously -implantable monitoring device, e.g. an ICM.
  • IMD 104B includes housing having a base 223 and an insulative cover 222.
  • Proximal electrode 206C and distal electrode 206D may be formed or placed on an outer surface of cover 222.
  • Various circuitries and components of IMD 104B e.g., described with respect to FIG. 3, may be formed or placed on an inner surface of cover 222, or within base 223.
  • a battery or other power source of IMD 104B may be included within base 223.
  • antenna 214B is formed or placed on the outer surface of cover 222, but may be formed or placed on the inner surface in some examples.
  • insulative cover 222 may be positioned over an open base 223 such that base 223 and cover 222 enclose the circuitries and other components and protect them from fluids such as body fluids.
  • the housing including base 223 and insulative cover 222 may be hermetically sealed and configured for subcutaneous implantation.
  • Circuitries and components may be formed on the inner side of insulative cover
  • Insulative cover 222 may be flipped onto a base 223.
  • the components of IMD 104B formed on the inner side of insulative cover 222 may be positioned in a gap 224 defined by base
  • Electrodes 206C and 206D and antenna 216B may be electrically connected to circuitry formed on the inner side of insulative cover 222 through one or more vias (not shown) formed through insulative cover 222.
  • Insulative cover 222 may be formed of sapphire (i.e., corundum), glass, parylene, and/or any other suitable insulating material.
  • Base 223 may be formed from titanium or any other suitable material (e.g., a biocompatible material).
  • Electrodes 206C and 206D may be formed from any of stainless steel, titanium, platinum, iridium, or alloys thereof.
  • electrodes 206C and 206D may be coated with a material such as titanium nitride or fractal titanium nitride, although other suitable materials and coatings for such electrodes may be used.
  • the housing of IMD 104B defines a length L, a width W and thickness or depth D and is in the form of an elongated rectangular prism wherein the length L is much larger than the width W, which in turn is larger than the depth D, similar to IMD 104A of FIG. 2A.
  • the spacing between proximal electrode 206C and distal electrode 206D may range from 5 mm to 50 mm, from 30 mm to 50 mm, from 35 mm to 45 mm, and may be any single spacing or range of spacings from 5 mm to 50 mm, such as approximately 40 mm.
  • IMD 104B may have a length L that ranges from 5 mm to about 70 mm.
  • the length L may range from 30 mm to 70 mm, 40 mm to 60 mm, 45 mm to 55 mm, and may be any single length or range of lengths from 5 mm to 50 mm, such as approximately 45 mm.
  • the width W may range from 3 mm to 15 mm, 5 mm to 15 mm, 5 mm to 10 mm, and may be any single width or range of widths from 3 mm to 15 mm, such as approximately 8 mm.
  • the thickness or depth D of IMD 104B may range from 2 mm to 15 mm, from 5 mm to 15 mm, or from 3 mm to 5 mm, and may be any single depth or range of depths between 2 mm and 15 mm, such as approximately 4 mm.
  • IMD 104B may have a volume of three cubic centimeters (cm) or less, or 1.5 cubic cm or less, such as approximately 1.4 cubic cm.
  • outer surface of cover 222 faces outward, toward the skin of the patient.
  • proximal end 226 and distal end 228 are rounded to reduce discomfort and irritation to surrounding tissue once inserted under the skin of the patient.
  • edges of IMD 104B may be rounded.
  • FIG. 3 is a block diagram illustrating an example configuration of IMD 104 of FIG. 1.
  • IMD 104 includes processing circuitry 302, memory 304, sensing circuitry 306 coupled to electrodes 206A and 206B (hereinafter, “electrodes 206”) and one or more sensor(s) 308, and communication circuitry 310.
  • Processing circuitry 302 may include fixed function circuitry and/or programmable processing circuitry. Processing circuitry 302 may include any one or more of a microprocessor, a controller, a GPU, a TPU, a DSP, an ASIC, a FPGA, or equivalent discrete or analog logic circuitry. The functions attributed to processing circuitry 302 herein may be embodied as software, firmware, hardware, or any combination thereof.
  • memory 304 includes computer-readable instructions that, when executed by processing circuitry 302, cause IMD 104 and processing circuitry 302 to perform various functions attributed herein to IMD 104 and processing circuitry 302.
  • Memory 304 may include any volatile, non-volatile, magnetic, optical, or electrical media, such as RAM, ROM, NVRAM, EEPROM, flash memory, or any other digital media.
  • Sensing circuitry 306 may sense an electrocardiogram (ECG) signal and measure impedance, e.g., of tissue proximate to IMD 104, via electrodes 206.
  • ECG electrocardiogram
  • the measured impedance may vary based on respiration, cardiac pulse, or flow, and a degree of perfusion or edema.
  • Processing circuitry 302 may determine physiological parameter values relating to respiration, fluid retention, cardiac pulse or flow, perfusion, and/or edema based on the measured impedance.
  • processing circuitry 302 may identify features of the sensed ECG, such as heart rate, heart rate variability, T-waveretemans, intra-beat intervals (e.g., QT intervals), and/or ECG morphologic features.
  • Processing circuitry 302 may determine that patient 102 has experienced an external impact based on changes in identified features of the sensed ECG (e.g., changes in the heart rate) in addition to changes in other physiological parameters (e.g., changes in acceleration experienced by patient 102, changes in posture of patient 102, changes in g- force on patient 102).
  • changes in identified features of the sensed ECG e.g., changes in the heart rate
  • other physiological parameters e.g., changes in acceleration experienced by patient 102, changes in posture of patient 102, changes in g- force on patient 102
  • IMD 104 may include one or more sensors 308, such as one or more accelerometers, gyroscopes inertial measurement units (IMUs), microphones, oximeters, optical sensors, temperature sensors, pressure sensors, and/or chemical sensors.
  • Sensing circuitry 306 may include one or more filters and amplifiers for filtering and amplifying signals from one or more of electrodes 206 and/or sensor(s) 308.
  • Sensing circuitry 306 and/or processing circuitry 302 may include a rectifier, filter and/or amplifier, a sense amplifier, comparator, and/or analog-to-digital converter.
  • Processing circuitry 302 may determine physiological parameter data 320, e.g., values of physiological parameters of patient 102, based on signals from sensor(s) 308, which may be stored as data 316 in memory 304.
  • Physiological parameter may include a posture of patient 102, acceleration of the body (e.g., of the torso) of patient 102, a g-force on patient 102, a heart rate of patient 102, a respiration rate of patient 102, a stress hormone level of patient 102, a body temperature of patient 102, glucose level of patient 102, blood pressure of patient 102, EEG signals of patient 102, change in electrocardiogram (ECG) morphology of patient 102, change in EGM morphology of patient 102, impedance between two or more locations on patient 102, a blood oxygen saturation of patient 102 or a rate of change of a physiological parameter (e.g., a rate of change in heart rate, body temperature, respiration rate, and/or blood oxygen saturation).
  • Sensing circuitry 306 may continuously or periodically sensed physiological signals via electrodes 206 and/or sensor(s) 308. Processing circuitry 302 may receive an instruction to sense physiological signals (e.g., from computing system 110, patient computing devices 106) and cause sensing circuitry 306 to sense physiological signals from patient 102 in response to the instruction.
  • computing system 110 and/or patient computing devices 106 transmit the instruction to IMD 104 based on location data (e.g., global positioning system (GPS)) of one or more patient computing devices 106.
  • the location data may correspond to activity by patient 102 that may increase a likelihood that patient 102 experiences an external impact.
  • computing system 110 and/or patient computing devices 106 may determine, based on the location data, that patient 102 is in or operating a vehicle and may transmit the instructions to IMD 104 in response.
  • memory 304 may store application(s) 312 executable by processing circuitry 302.
  • Application(s) 312 may include impact detection application 314 executable by processing circuitry 302 to detect occurrences of external impact on patient 102 based on changes in physiological parameters sensed by sensing circuitry 306 and processing circuitry 302 via electrodes 206 and/or sensor(s) 308.
  • Processing circuitry 302 may determine changes in physiological parameter data 320 by comparing a currently sensed physiological parameter value against an average physiological parameter value stored as data 316 in memory 304. In some examples, processing circuitry 302 determines changes in physiological parameter data 320 by comparing a currently sensed physiological parameter value against a previously sensed physiological parameter value. In some examples, processing circuitry 302 determines a change in acceleration experienced by patient 102 by comparing a current acceleration value sensed by sensing circuitry 306 against an average acceleration value or previously sensed acceleration value stored in memory 304. In some examples, processing circuitry 302 determines a change in posture of patient 102 by comparing a current posture of patient 102 sensed by sensing circuitry 306 against a previously sensed posture stored in memory 304.
  • Processing circuitry 302 may store the changes in physiological parameter data 320 as data 316 in memory 304.
  • Processing circuitry 302 may store a magnitude of the change in physiological parameter (e.g., a magnitude of change in acceleration and/or g-force (g), an amount of time for a change from a first posture to a second posture) as data 316 in memory 304.
  • a magnitude of the change in physiological parameter e.g., a magnitude of change in acceleration and/or g-force (g), an amount of time for a change from a first posture to a second posture
  • processing circuitry 302 may compare changes in physiological parameter data 320 against threshold conditions 318 stored in memory 304 and may determine that patient 102 has experienced an external impact based on a determination that one or more changes in physiological parameter data 320 has satisfied a corresponding threshold condition. In some examples, processing circuitry 302 may determine that patient 102 has experienced an external impact based on a determination that each of two or more changes in physiological parameter data 320 has satisfied a corresponding threshold condition.
  • Threshold conditions 318 may include, but are not limited to, a threshold change (e.g., in magnitude, in rate of change) of acceleration experienced by patient 102, g-force on patient 102, of heart rate of patient 102, of respiration rate of patient 102, of blood oxygen saturation of patient 102, of stress hormone levels of patient 102, or the like.
  • IMD 104 receives threshold conditions 318, e.g., from patient computing devices 106, computing system 110, and/or client computing devices 128 and stores threshold conditions 318 in memory 304.
  • IMD 104 determines threshold conditions 318 based at least in part on physiological parameter data 320, e.g., based at least in part on average physiological parameter values.
  • Threshold conditions 318 may correspond to minimum changes of physiological parameters that correspond to effects of an external impact (e.g., of forces resulting from a vehicle collision, of forces resulting from a collision between patient 102 and an object, of forces sufficient to cause a concussion) on patient 102.
  • the minimum magnitude may be determined, e.g., by clinician 130, to cause IMD 104 to detect an external impact with a magnitude at least equal to the minimum magnitude.
  • Threshold conditions 318 may include a minimum magnitude of a single force detected by IMD 104 (e.g., along a single reference axis) or may be a total force detected by IMD 104 (e.g., along multiple axes).
  • the minimum magnitude of threshold conditions 318 may be greater than or equal to 10G. In some examples, the minimum magnitude of threshold conditions 318 is greater than or equal to 30G.
  • threshold conditions 318 include a threshold amount of time for patient 102 to transition from a first posture (e.g., a standing posture) to a second posture (e.g., a prone posture).
  • processing circuitry 302 compares a change in acceleration of patient 102 against a first threshold condition (e.g., a threshold change in acceleration) and determines that patient 102 has experienced an external impact based on a determination that the change in acceleration satisfies the first threshold condition (e.g., is greater than or equal to the threshold change in acceleration.
  • a first threshold condition e.g., a threshold change in acceleration
  • processing circuitry 302 compares a change in posture of patient 102 against a second threshold condition (e.g., a threshold period of time) and determines that patient 102 has experienced an external impact based on a determination that the change in posture satisfies the second threshold condition (e.g., that patient 102 has transitioned from a first posture to a posture over a period of time less than or equal to the threshold period of time).
  • a second threshold condition e.g., a threshold period of time
  • processing circuitry 302 may cause communication circuitry 310 to output a notification.
  • Communication circuitry 310 may output the notification to one or more of patient computing devices 106 or one or more wireless access points 124.
  • the notification may include information indicating that patient 102 has experienced the external impact.
  • processing circuitry 302 may cause communication circuitry 310 to output data 316 (e.g., physiological parameter data 320) in addition to or as a part of the notification.
  • Communication circuitry 310 may include any suitable hardware, firmware, software, or any combination thereof for wireless communicating with another device. Communication circuitry 310 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 nonproprietary wireless communication schemes.
  • FIG. 4 is a block diagram illustrating an example configuration of a patient computing device 106, which may correspond to either (or both operating in coordination) of patient computing devices 106A and 106B.
  • patient computing device 106 includes a smartphone, a laptop, a tablet computer, a personal digital assistant (PDA), a smartwatch, or other wearable computing device.
  • PDA personal digital assistant
  • computing device 106 may be logically divided into user space 402, kernel space 404, ad hardware 406.
  • Hardware 406 may include one or more hardware components that provide an operating environment for components executing in user space 402 and kernel space 404.
  • User space 402 and kernel space 404 may represent different sections or segmentations of memory, where kernel space 404 provides higher privileges to processes and threads than user space 402.
  • kernel space 404 may include operating system 432, which operates with higher privileges than components executing in user space 402.
  • hardware 406 includes processing circuitry 420, memory 422, one or more input devices 424, one or more output devices 426, one or more sensors 428, and communication circuitry 429.
  • computing device 106 may be any component or system that includes processing circuitry or other suitable computing environment for executing software instructions and, for example, need not necessarily include one or more elements shown in FIG. 4.
  • Processing circuitry 420 is configured to implement functionality and/or process instructions for execution within computing device 106.
  • processing circuitry 420 may be configured to receive and process instructions stored in memory 420 that provide functionality of components included in kernel space 404 and user space 402 to perform one or more operations in accordance with techniques of this disclosure.
  • Examples of processing circuitry 420 may include, any one or more microprocessors, controllers, GPUs, TPUs, DSPs, ASICs, FPGAs, or equivalent discrete or integrated logic circuitry.
  • Memory 422 may be configured to store information within computing device 106, for processing during operation of computing device 106.
  • Memory 422 in some examples, is described as a computer-readable storage medium.
  • memory 422 includes a temporary memory or a volatile memory. Examples of volatile memories include RAM, DRAM, SRAM, and other forms of volatile memories known in the art.
  • Memory 422 in some examples, also includes one or more memories configured for long-term storage of information, e.g., including non-volatile storage elements.
  • non-volatile storage elements include magnetic hard discs, optical discs, floppy discs, flash memories, or forms of electrically programmable memories (EPROM) or electrically erasable and programmable (EEPROM) memories.
  • EPROM electrically programmable memories
  • EEPROM electrically erasable and programmable
  • memory 422 includes cloud-associated storage.
  • One or more input devices 424 of computing device 106 may receive input, e.g., from patient 102, clinician 130, or another user. Examples of input are tactile, audio, kinetic, and optical input. Input devices 424 may include, as examples, a mouse, keyboard, voice responsive system, camera, buttons, control pad, microphone, presence-sensitive or touch-sensitive component (e.g., screen), or any other device for detecting input from a user or a machine.
  • One or more output devices 426 of computing device 106 may generate output, e.g., to patient 102 or another user. Examples of output are tactile, haptic, audio, and visual output.
  • Output devices 426 of computing device 106 may include a presencesensitive screen, sound card, video graphics adapter card, speaker, cathode ray tube (CRT) monitor, liquid crystal display (LCD), light emitting diodes (LEDs), or any type of device for generating tactile, audio, and/or visual output.
  • One or more sensors 428 of computing devices 106 may sense physiological parameters or physiological signals of patient 102.
  • Sensor(s) 428 may include electrodes, accelerometers (e.g., 3-axis accelerometers), IMUs, gyroscopes, optical sensors, impedance sensors, temperature sensors, pressure sensors, heart sound sensors (e.g., microphones or accelerometers), and other sensors.
  • Communication circuitry 429 of computing device 106 may communicate with other devices by transmitting and receiving data.
  • Communication circuitry 429 may receive data from IMD 104, such as physiological signals and/or physiological parameter values, from communication circuitry 310 in IMD 104.
  • Communication circuitry 429 may include a network interface card, such as an Ethernet card, an optical transceiver, a radio frequency transceiver, or any other type of device that can send and receive information.
  • communication circuitry 429 may include a radio transceiver configured for communication according to standards or protocols, such as 3G, 4G, 5G, WiFi (e.g., 802.11 or 802.15 ZigBee), Bluetooth®, or Bluetooth® Low Energy (BLE).
  • health monitoring application 410 executes in user space 402 of computing device 106.
  • Health monitoring application 410 may be logically divided into presentation layer 412, application layer 414, and data layer 416.
  • Presentation layer 412 may include a user interface (UI) component 430, which generates and renders user interfaces of health monitoring application 410.
  • UI user interface
  • Data layer 416 may include threshold condition data 450 and physiological parameter data 452, which may be received from IMD 104 via communication circuitry 429 and stored in memory 422 by processing circuitry 420.
  • Threshold condition data 450 may contain threshold conditions (e.g., threshold magnitudes of change, threshold rates of change, threshold periods of time) corresponding to different physiological parameters.
  • IMD 104 may receive threshold conditions from clinician 130, clinician computing device 128, computing system 110, or other computing devices or systems connected to network 108 (e.g., via input device(s) 424 and/or communication circuitry 429).
  • Computing device 106 may determine or receive changes in physiological parameter values and store the changes in physiological parameter values in physiological parameter data 452. In some examples, computing device 106 may receive the changes in physiological parameter values from IMD 104. In some examples, computing device 106 may determine changes in physiological parameter data 452 by comparing currently sensed physiological parameter values (e.g., by IMD 104 and/or sensor(s) 428) against an average or previously sensed physiological parameter value stored in physiological parameter data 452.
  • Application layer 414 may include, but is not limited to, an impact analyzer 440.
  • Impact analyzer 440 may determine that patient 102 has experienced an external impact based on a determination that changes in physiological parameters values (e.g., stored in physiological parameter data 452) satisfy one or more threshold conditions stored in threshold condition data 450.
  • computing device 106 receives a notification from IMD 104 indicating that patient 102 has experienced an external impact and impact analyzer 440 confirms that patient 102 has experienced an external impact based on sensed physiological signals and/or physiological parameters from sensor(s) 428.
  • FIG. 5 is a block diagram illustrating an operating perspective of HMS 116.
  • HMS 116 may be implemented in a computing system 110, which may include hardware components such as processing circuitry 112, memory 114, and communication circuitry, embodied in one or more physical devices.
  • FIG. 5 provides an operating perspective of HMS 116 when hosted as a cloud-based platform.
  • components of HMS 166 are arranged according to multiple logical layers that implement the techniques of this disclosure. Each layer may be implemented by one or more modules comprised of hardware, software, or a combination of hardware and software.
  • Computing devices such as patient computing devices 106 and/or client computing devices 128, operate as clients that communicate with HMS 116 via interface layer 500.
  • the computing devices typically execute client software applications, such as desktop application(s), mobile application(s), and web application(s).
  • Interface layer 500 represents a set of application programming interfaces (API) or protocol interfaces presented and supported by HMS 116 for the client software applications.
  • Interface layer 500 may be implemented with one or more web servers.
  • HMS 116 also includes an application layer 502 that represents a collection of services 506 for implementing the functionality ascribed to HMS 116 herein.
  • Application layer 502 receives information from client applications, e.g., data from patient computing devices 106, some or all of which may have been received from IMD 104, and further processes the information according to one or more of services 506 to respond to the information.
  • Application layer 502 may be implemented as one or more discrete software services 506 executed on one or more application server, e.g., physical or virtual machines. That is, the application servers provide runtime environments for execution of services 506.
  • the functionality interface layer 500 as described above and the functionality of application layer 502 may be implemented at the same server.
  • Services 506 may communicate via a logical service bus 511, Service bus 511 generally represents a logical interconnections or set of interfaces that allows different services 506 to send messages to other services, such as by a publish/subscription communication model.
  • Data layer 504 of HMS 116 provides persistence for information in HMS 116 using one or more data repositories 508.
  • a data repository 508, generally, may be any data structure or software that stores and/or manages data. Examples of data repositories 508 include, but are not limited to relational databases, multi-dimensional databases, maps, and/or hash tables.
  • each of services 510-514 is implemented in modular form within HMS 116. Although shown as separate modules for each service, in some examples the functionality of two or more services may be combined into a single module or component.
  • Each of services 510-514 may be implemented in software, hardware, or a combination of hardware and software.
  • services 510-514 may be implemented as standalone devices, separate virtual machines or containers, processes, threads or software instructions generally for execution on one or more physical processors.
  • Record management service 514 may store received data such as threshold condition data 520 and physiological parameter data 522 from client computing devices (e.g., from patient computing devices 106, IMD 104).
  • Impact detection service 510 may determine if patient 102 has experienced an external impact based on physiological parameter data 522. Impact detection service 510 may retrieve changes in physiological parameter values from physiological parameter data 522. Impact detection service 510 may determine the changes in physiological parameter values by comparing a magnitude of a currently sensed physiological parameter value against an average physiological parameter value or a previously sensed physiological parameter value. Impact detection service 510 may compare the changes in physiological parameter values against corresponding threshold conditions (e.g., a threshold magnitude of change, a threshold rate of change, a threshold time period for a change) stored in threshold condition data 520 and determine that patient 102 has experienced an external impact based on a determination that at least one threshold condition is satisfied.
  • threshold conditions e.g., a threshold magnitude of change, a threshold rate of change, a threshold time period for a change
  • Impact detection service 510 may cause HMS 116 to output a notification (e.g., to clinician computing devices 128, patient computing devices 106, and/or to other computing devices and/or systems connected to HMS 116 via network 108) in response to a determination that patient 102 has experienced an external impact.
  • a notification e.g., to clinician computing devices 128, patient computing devices 106, and/or to other computing devices and/or systems connected to HMS 116 via network 108 in response to a determination that patient 102 has experienced an external impact.
  • Post-impact monitoring service 512 may monitor physiological parameters of patient 102 after patient 102 has experienced an external impact to determine whether patient 102 is experiencing an effects of injury, incapacitation, or the like. In response to a determination by impact detection service 510 that patient 102 has experienced an external force, post-impact monitoring service 512 may determine whether physiological parameter values sensed after the determined external impact return to within corresponding threshold ranges of corresponding baseline physiological parameter values (e.g., average physiological parameter values). Deviation from baseline physiological parameter values by an amount greater than or equal to a threshold amount may indicate that patient 102 is experiencing additional external impacts (e.g., patient 102 is experiencing multiple external impacts in a single traffic collision) or that patient 102 is continuing to experience effects/injuries from the external impact.
  • additional external impacts e.g., patient 102 is experiencing multiple external impacts in a single traffic collision
  • Post-impact monitoring service 512 may cause HMS 116 to output a notification to computing devices (e.g., to client computing devices 128, to patient computing devices 106, and/or to other computing devices or systems connected to HMS 116 via network 108) indicating the changes in physiological parameter(s) in response to a determination that values for one or more physiological parameters continue to deviate from a corresponding baseline value by at least a threshold amount.
  • computing devices e.g., to client computing devices 128, to patient computing devices 106, and/or to other computing devices or systems connected to HMS 116 via network 108 indicating the changes in physiological parameter(s) in response to a determination that values for one or more physiological parameters continue to deviate from a corresponding baseline value by at least a threshold amount.
  • FIG. 6 is a flowchart illustrating an example process of determining that a patient has experienced an external impact. While the example process of FIG. 6 is described below primarily within reference to medical system 100 of FIG. 1, the example process may be performed individually or jointly by one or more components of system 100 (e.g., by one or more of IMD 104, patient computing devices 106, computing system 110 (e.g., HMS 116 of computing system 110), clinician computing devices 128, or any other computing device, system, or cloud computing environment connected to network 108).
  • IMD 104 patient computing devices 106
  • computing system 110 e.g., HMS 116 of computing system 110
  • System 100 may sense, via sensor(s) of system 100, physiological signals of patient 102 (602).
  • Sensor(s) may include electrodes 206 connected to IMD 104, sensor(s) 308 within or connected to IMD 104, sensor(s) 428 within or connected to patient computing devices 106, or any other sensors coupled to patient 102 and in communication with one or more components of system 100.
  • Sensor(s) may include, but are not limited to, accelerometers (e.g., 3-axis accelerometers), gyroscopes, IMUs, electrodes, blood oximeters microphones, oximeters, optical sensors, temperature sensors, pressure sensors, and/or chemical sensors.
  • System 100 may receive different physiological signals from different sensor(s).
  • System 100 may continuously or periodically sense physiological signals from patient 102.
  • system 100 may sense physiological signals in response to an input from patient 102, clinician 130, or a third party (e.g., a family member, a caretaker).
  • system 100 may sense physiological signals in response to specific data (e.g., location data) received by system 100.
  • specific data e.g., location data
  • system 100 may determine, based on location data of one or more patient computing devices 106, that patient 102 is at a location or is traveling at speeds indicative that patient 102 is operating or is within a motor vehicle. System 100 may then cause IMD 104 and/or patient computing devices 106 to begin sensing physiological signals from patient 102.
  • System 100 may determine physiological parameter values based on the sensed physiological signals (604).
  • Physiological parameters may include, but are not limited, an acceleration experienced by patient 102, a g-force on patient 102, a posture of patient 102 (e.g., whether patient 102 is standing, sitting, prone, crouching, kneeling, lying down), heart rate of patient 102, respiration rate of patient 102, blood oxygen saturation of patient 102, stress hormone level (e.g., adrenaline level) of patient 102, body temperature of patient 102, or the like.
  • System 100 may determine values for each physiological parameter based on one or more physiological signals.
  • System 100 may determine the acceleration experienced by patient 102, the g-force on patient 102 and the posture of patient 102 based on signals from one or more an accelerometer, a gyroscope, or an IMU.
  • System 100 may determine a heart rate of patient 102 based on ECG signals sensed from the heart of patient 102 (e.g., via electrodes 206 of IMD 104).
  • System 100 may determine a respiration rate of patient 102 based on sensed signals from one or more of an accelerometer, an IMU, or a microphone.
  • System 100 may determine change(s) in physiological parameter values of patient 102 (606).
  • System 100 may compare sensed physiological parameter values against stored physiological parameter values and may determine a magnitude of change and/or a rate of change for one or more physiological parameters.
  • Stored physiological parameter values may include an average physiological parameter value or a previously sensed physiological parameter value.
  • the previously sensed physiological parameter value may be sensed at a first time preceding a second time corresponding to the sensed physiological parameter values by at about up to 10 s.
  • system 100 compares two or more different sets of sensed physiological parameter values of patient 102, e.g., to prevent system 100 from identifying false-positive impacts.
  • system 100 may compare a first set of sensed physiological parameter values corresponding to a first time against stored physiological parameter values and/or a second set of sensed physiological parameter values corresponding to a second time to determine whether the first set of sensed physiological parameter values are consistent with changes in physiological parameter values resulting from an external impact.
  • System 100 may compare three, four, or five or more sets of sensed physiological parameter values of patient 102, e.g., to identify false-positive determinations.
  • the sets of sensed physiological parameter values may be sensed within a pre-determined period of time (e.g., within a period of up to 10 s).
  • System 100 may adjust one or more average physiological parameter values over time, e.g., based on changes in sensed physiological parameter values over time (e.g., over weeks, over months).
  • the adjusted average physiological parameter values may correspond to changes in physiology of patient 102 over time.
  • system 100 may adjust average heart rate and/or average respiration rate of patient 102 over time based on changes in sensed heart rate of patient 102 and/or changes in sensed respiration rate of patient 102, respectively, over time.
  • System 100 may determine whether change(s) in physiological parameter value satisfy one or more threshold conditions for an external impact (608).
  • Threshold conditions may be determined by a clinician (e.g., by clinician 130) to distinguish external impacts that system 100 is configured to identify (e.g., vehicle collisions, collisions between patient 102 and another individual or another object) from other external impacts (e.g., a fall).
  • Threshold conditions may include threshold changes in physiological parameters including, but are not limited to, a threshold magnitude of change, a threshold rate of change, or a threshold time for a specific change (e.g., from a first posture to a second posture).
  • system 100 Based on a determination that the change(s) in physiological parameter values do not satisfy one or more threshold conditions, (“NO” branch of 608), system 100 continues to sense physiological signals of patient 102 via sensor(s) (602). Based on a determination that the change(s) in physiological parameter values satisfy one or more threshold conditions (“YES” branch 608), system 100 may output a notification to an external device (610).
  • System 100 may store one or more threshold conditions for each physiological parameter monitored by system 100.
  • system 100 stores, for a change of acceleration experienced by patient 102, one or more threshold changes in acceleration, each threshold change in acceleration corresponding to a different external impact scenario.
  • System 100 may store a first threshold change in acceleration for external impacts consistent with a possible vehicle collision and a second threshold change in acceleration for external impacts consistent with an impact of a projectile on patient 102.
  • System 100 may compare each determined change in physiological parameter against a corresponding threshold condition (e.g., a threshold change in the same physiological parameter). System 100 may determine whether the determine change satisfies the corresponding threshold condition. In some examples, system 100 determines whether a magnitude of a change in acceleration experienced by patient 102 exceeds or is equal to a threshold magnitude of change in acceleration. The threshold magnitude of change in acceleration may be at least about 3G. In some examples, system 100 determines whether patient 102 transitions from a first posture to a second posture in less than a threshold period of time. A change in posture in less than or equal to the threshold period of time may indicate that the body of patient 102 is undergoing motion consistent with the results of an external impact (e.g., tumbling). For changes in posture, clinician 130 may specify the starting posture (i.e., the “first posture”) and the ending posture (i.e., the “second posture”). The starting and ending postures may correspond to motion of patient 102 consistent with the effects of external impact.
  • a threshold condition e.
  • system 100 may determine whether changes in two or more physiological parameters each satisfies a corresponding threshold condition. For example, system 100 may determine whether a change in acceleration experienced by patient 102 satisfies a first threshold condition and whether a change in posture of patient 102 satisfies a second threshold condition. By comparing changes in multiple physiological parameters against the corresponding threshold conditions, system 100 reduces a likelihood of a falsepositive or a false-negative determination.
  • System 100 may output a notification to a computing device (610).
  • Computing device(s) may include, but are not limited to, patient computing devices 106, clinician computing devices 128, computing system 110, and/or other computing devices in communication with network 108.
  • the notification may include an indication that patient 102 has experienced an external impact, the physiological parameter values, the determined changes in the physiological parameter values, a likely type of the external impact (e.g., traffic collision, impact of a projectile), location information of patient 102, a request for medical aid, and/or instructions that causes the computing device receiving the notification to output a request for medical aid.
  • a likely type of the external impact e.g., traffic collision, impact of a projectile
  • the notification includes instructions to cause one or more patient computing devices 106 to output (e.g., via output device(s) 426) a request to interface to patient 102.
  • system 100 may take no further action upon receiving user input (also referred to herein as “patient input”) from patient 102 (e.g., confirming receipt of the notification, confirming wellness of patient 102) within a threshold period of time, e.g., less than about five minutes.
  • System 100 may receive the user input via input device(s) 424 of patient computing device 106. If system 100 does not receive user input from patient 102 within the threshold period of time, system 100 may transmit a request for medical aid to a medical care provider or EMS provider.
  • system 100 may, in response to the determination, output the notification at a specified period of time (e.g., number of hours, days, weeks, months) after the occurrence of the change(s) in physiological parameter.
  • a specified period of time e.g., number of hours, days, weeks, months
  • System 100 may store the notification and information corresponding to the change(s) in physiological parameter values (e.g., the physiological parameter values, the time of the change(s), the sensed physiological signals).
  • Medical events may include, but are not limited to cardiac events such as sudden cardiac arrest, stroke, hemmorage, heart failure decompensation, or the like.
  • An external impact may contribute to, worsen, or cause one or more cardiac events and/or one or more other medical events (e.g., non-cardiac events) within a period of time (e.g., hours, days, weeks, months, years) after occurrence of the external impact.
  • Information corresponding to the external impact may facilitate diagnosis and/or treatment of the one or more cardiac events and/or the one or more other medical events.
  • System 100 may output the notification and/or information corresponding to an external impact in response to a determination by system 100 of an occurrence of a medical event related to an external impact (e.g., based on sensed physiological signals by system 100, based on clinician input, based on user input) after at least a threshold period of time.
  • System 100 may determine the relation between the medical event and the external impact based on a medical history of the user, the location of the external impact on the patient, the location of the medical event on the patient, and/or changes in physiological parameter values between the external impact and occurrence of the medical event.
  • System 100 may output, based on the type and/or severity of the medical event, the stored information, and/or the relationship between the medical event and the external impact, the notification.
  • the notification may include a likelihood that the external impact contributed and/or caused the medical event and/or an indication of the type of the medical event.
  • System 100 may repeat this process for each external impact stored within system 100.
  • FIG. 7 is a flowchart illustrating another example process of determining that a patient has experienced an external impact. While the example process of FIG. 7 is described below primarily within reference to medical system 100 of FIG. 1, the example process may be performed individually or jointly by one or more components of system 100 (e.g., by one or more of IMD 104, patient computing devices 106, computing system 110 (e.g., HMS 116 of computing system 110), clinician computing devices 128, or any other computing device, system, or cloud computing environment connected to network 108).
  • IMD 104 patient computing devices 106
  • computing system 110 e.g., HMS 116 of computing system 110
  • System 100 may sense, via sensor(s) of medical system 100, physiological signals of patient 102 (702). System 100 may determine physiological parameter values based on the sensed physiological signals (704). System 100 may determine change(s) in physiological parameter values (706). System 100 may perform any of steps 702-706 in accordance with the example process described above with respect to FIG. 6, e.g., in a same manner as steps 602-606 of FIG. 6, respectively.
  • System 100 may determine whether change(s) in physiological parameter values satisfy one or more threshold conditions of an external impact (708). System 100 may determine whether one or more threshold conditions are satisfied in accordance with other example process described above e.g., with respect to step 608 of FIG. 6. Based on a determination that the change(s) in physiological parameter values do not satisfy any threshold conditions (“NO” branch of 708), system 100 may continue to sense physiological signals of patient 102 (702).
  • system 100 may assign a weight for each physiological parameter (710).
  • System 100 may select physiological parameters that exhibit changes in parameter values that satisfy corresponding threshold conditions.
  • System 100 may then assign a separate weight for each selected physiological parameter.
  • Each weight may indicate an assigned significance of the corresponding physiological parameter in determining whether patient 102 has experienced an external impact.
  • Weights for each physiological parameter may be absolute or may be relative to other weights for other physiological parameters. In some examples, where weights are absolute, the weight for a physiological parameter may be constant regardless of the number and/or types of selected physiological parameters.
  • Types of selected physiological parameters may include, but are not limited to, acceleration experienced by patient 102, g- force on patient 102, posture of patient 102, body temperature of patient 102, respiration rate of patient 102, heart rate of patient 102, blood oxygen saturation of patient 102, or a stress hormone level of patient 102.
  • the weight for a physiological parameter may vary based on the number and/or types of the selected physiological parameters.
  • System 100 may receive weights for physiological parameters from clinician 130.
  • system 100 may apply a machine learning (ML) model to determine weights for physiological parameters.
  • the ML model may be trained via a training data set including changes in values of different physiological parameters and a corresponding indication of whether an individual (e.g., patient 102 and/or one or more other individuals) has experienced an external impact and/or a severity of the external impact.
  • System 100 may input a number of selected physiological parameters and a type of each selected physiological parameter into the ML model and receive weights for each of the selected physiological parameters as outputs of the ML model.
  • System 100 may determine, for each change in physiological parameter values that satisfies a corresponding threshold condition and based on the corresponding weight, a weighted score (712).
  • System 100 may determine a score for each change in physiological parameter values.
  • the score may be a ratio or percentage change from a baseline value (e.g., from an average physiological parameter value) or may be based on the magnitude of the change from the baseline value (e.g., based on a predetermined scale and/or based on previously sensed physiological parameter value changes).
  • System 100 then adjust each score by the corresponding weight for the physiological parameter to determine a weighted score.
  • system 100 may assign a change in acceleration of patient 102 with a magnitude of 3 g with a score of “50.”
  • System 100 may then adjust the determined score based on an assigned weight (e.g., “0.2”) to determine a weighted score (e.g., “10”).
  • the weighted score indicates a magnitude of the change adjusted by the relative significance of the physiological parameter in determining whether patient 102 experienced an external impact.
  • System 100 may determine an aggregate score based on a summation of two or more weighted scores (714). Due to the different weights assigned to different physiological parameters, system 100 may account for the relative importance of different physiological parameters as a part of the summation process to determine the aggregate score. In some examples, the weights for two or more physiological parameters (e.g., all of the physiological parameters) are equal. In such examples, changes to physiological parameters with the same weights would be assigned a same level of importance when system 100 determines the aggregate score. System 100 may then determine whether the aggregate score satisfies a threshold score of an external impact (716). The threshold score may correspond to a minimum score value corresponding to changes to physiological parameter values resulting from an external impact. The threshold score may be a threshold percentage change of physiological parameters, a threshold ratio of change of physiological parameters.
  • system 100 may continue to sense physiological signals from patient 102 (702). Based on a determination that the aggregate score satisfies the threshold score (“YES” branch of 716), system 100 may output a notification to a computing device. System 100 may determine that the aggregate score satisfies a threshold score by determining that the aggregate score is greater than or equal to the threshold score.
  • System 100 may output a notification in a same manner as previously described herein and the notification may include the same content as other example notifications previously described herein.
  • the techniques described in this disclosure may be implemented, at least in part, in hardware, software, firmware, or any combination thereof.
  • various aspects of the techniques may be implemented within one or more microprocessors, DSPs, ASICs, FPGAs, or any other equivalent integrated or discrete logic QRS circuitry, as well as any combinations of such components, embodied in external devices, such as physician or patient programmers, stimulators, or other devices.
  • the terms “processor” and “processing circuitry” may generally refer to any of the foregoing logic circuitry, alone or in combination with other logic circuitry, or any other equivalent circuitry, and alone or in combination with other digital or analog circuitry.
  • At least some of the functionality ascribed to the systems and devices described in this disclosure may be embodied as instructions on a computer-readable storage medium such as RAM, DRAM, SRAM, magnetic discs, optical discs, flash memories, or forms of EPROM or EEPROM.
  • the instructions may be executed to support one or more aspects of the functionality described in this disclosure.
  • the functionality described herein may be provided within dedicated hardware and/or software modules. Depiction of different features as modules or units is intended to highlight different functional aspects and does not necessarily imply that such modules or units must be 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 integrated within common or separate hardware or software components.
  • the techniques could be fully implemented in one or more circuits or logic elements.
  • the techniques of this disclosure may be implemented in a wide variety of devices or apparatuses, including an IMD, an external programmer, a combination of an IMD and external programmer, an integrated circuit (IC) or a set of ICs, and/or discrete electrical circuitry, residing in an IMD and/or external programmer.
  • Example 1 an implantable medical device (IMD) configured to be implanted within a patient, the IMD comprising: a plurality of sensors comprising an accelerometer; communications circuitry; and processing circuitry coupled to the plurality of sensors and to the communications circuitry, the processing circuitry being configured to: determine, based on sensed data from the accelerometer, a change in acceleration experienced by the patient and a change in posture of the patient; determine that the change in acceleration satisfies a first threshold condition; and that the change in posture satisfies a second threshold condition; and based on a determination that the change in acceleration satisfies the first threshold condition and that the change in posture satisfies the second threshold condition, cause the communications circuitry to transmit a notification indicating the occurrence of an external impact.
  • IMD implantable medical device
  • Example 2 the IMD of example 1, wherein the first threshold condition comprises a threshold change in acceleration experienced by the patient.
  • Example 3 the IMD of example 2, wherein to determine that the change in acceleration satisfies the threshold change in acceleration, the processing circuitry is configured to: compare a current acceleration detected by the accelerometer to an average acceleration detected by the accelerometer prior to the current acceleration; and determine that a difference between the current acceleration and the average acceleration satisfies the threshold change in acceleration.
  • Example 4 the IMD of any of examples 2 and 3, wherein the threshold change in acceleration is greater than or equal to 3G.
  • Example 5 the IMD of any of examples 1-4, wherein the second threshold condition comprises a change from a first posture to a second posture within a threshold time period.
  • Example 6 the IMD of example 5, wherein to determine the change in posture, the processing circuitry is configured to: determine, based on the sensed data, that the patient is in the first posture at a first time; and determine, based on the sensed data, that the patient is in the second posture at a second time, wherein the second time is different from the first time, and wherein to determine that the change in posture satisfies the second threshold condition, the processing circuitry is configured to: determine a time difference between the first time and the second time; compare the time difference against the threshold time period; and determine that the change in posture satisfies the second threshold condition based on a determination that the time difference is less than or equal to the threshold time period.
  • Example 7 the IMD of any of examples 1-6, wherein the processing circuitry is configured to: determine, based on the sensed data, values for one or more other physiological parameters; compare, based on the determination that the change in acceleration satisfies the first threshold condition and that the change in posture satisfies the second threshold condition, each of the one or more physiological parameter values against a corresponding threshold condition; and in response to a determination that the one or more physiological parameter values satisfy one or more threshold conditions, cause the communications circuitry to output the notification.
  • Example 8 the IMD of example 7, wherein the one or more physiological parameters comprises one or more of: a heart rate of the patient; a stress hormone level of the patient; a respiration rate of the patient; a body temperature of the patient; a blood pressure of the patient; an electroencephalogram (EEG) signal of the patient; a glucose level of the patient; impedance within tissue of the patient; or a blood oxygen saturation level of the patient.
  • EEG electroencephalogram
  • Example 9 the IMD of any of examples 7 and 8, wherein a plurality of physiological parameters comprises the change in acceleration, the change in posture, and the one or more physiological parameters, and wherein the processing circuitry is configured to: assign for each of the plurality of physiological parameters, a respective weight; determine, for each of the plurality of physiological parameters, in response to satisfaction of a corresponding threshold condition and based on the respective weight, a weighted score; determine an aggregate score based on a summation of a plurality of weighted scores; compare the aggregate score against a threshold score; and based on a determination that the aggregate score satisfies the threshold score, cause the communications circuitry to output the notification.
  • Example 10 the IMD of any of examples 1-9, wherein the processing circuitry is configured to: receive, from the computing device, an instruction to monitor the patient in response to notification; and cause the plurality of sensors to begin sensing data from the patient in response to the instruction.
  • Example 11 the IMD of any of examples 1-10, wherein the processing circuitry is configured to: in response to a determination that the change in acceleration satisfies the first threshold condition and the change in posture satisfies the second threshold condition, cause the communications circuitry to transmit a request for patient input to the computing device; and based on a determination that the processing circuitry did not receive the patient input within a threshold period of time, cause the communications circuitry to output the notification to the computing device.
  • Example 12 the IMD of any of examples 1-11, wherein the IMD is configured to be implanted in a torso of the patient.
  • Example 13 the IMD of any of examples 1-12, wherein one or more sensors of the plurality of sensors are configured to be implanted in a head of the patient.
  • Example 14 the IMD of any of examples 1-13, wherein one or more sensors of the plurality of sensors are configured to sense cardiac activity of a heart of the patient.
  • Example 15 the IMD of example 14, whereinto determine the change in posture of the patient, the processing circuitry is configured to: determine, via the one or more sensors, one or more of: a change in a heart rate of the patient; a change in the EEG of the patient; a change in blood pressure of the patient; and determine, based on the change in acceleration and the one or more of the change in the heart rate, the change in the EEG, or the change in blood pressure, the change in posture of the patient.
  • Example 16 the IMD of any of examples 1-15, wherein the IMD comprises an insertable cardiac monitor, and wherein the plurality of sensors comprises one or more electrodes.
  • Example 17 the IMD of example 16, wherein the insertable cardiac monitor comprises: a housing configured for subcutaneous implantation in the patient, the housing having a length between 40 millimeters (mm) and 60 mm between a first end and a second end, a width less than the length, and a depth less than the width; and the one or more electrodes comprising: a first electrode at or proximate to the first end of the housing, and a second electrode at or proximate to the second end of the housing, wherein the insertable cardiac monitor is configured to sense the cardiac signal via the first electrode and the second electrode.
  • the insertable cardiac monitor comprises: a housing configured for subcutaneous implantation in the patient, the housing having a length between 40 millimeters (mm) and 60 mm between a first end and a second end, a width less than the length, and a depth less than the width; and the one or more electrodes comprising: a first electrode at or proximate to the first end of the housing, and a second electrode at or proxi
  • Example 18 the IMD of any of examples 1-17, wherein the processing circuitry is configured to: determine, based on sensed signals from the plurality of sensors, that the user is experiencing a medical event; and cause the communications circuitry to output the notification in conjunction with an indication of the determined medical event.
  • Example 19 the IMD of example 18, wherein the processing circuitry is configured to cause the communications circuitry to output the notification at least a threshold number of hours after occurrence of the external impact.
  • Example 20 the IMD of any of examples 18 and 19, wherein the medical event comprises a cardiac event.
  • Example 21 the IMD of example 20, wherein the cardiac event comprises one or more of: sudden cardiac arrest; stroke; hemmorage; or heart failure decompensation
  • Example 22 a system comprising: an implantable medical device (IMD) configured to be implanted within a patient, the IMD comprising: a plurality of sensors comprising an accelerometer; an external computing device comprising a user interface; and processing circuitry configured to: receive, from the IMD, sensed data corresponding to values for a plurality of physiological parameters of the patient, the plurality of physiological parameters comprising an acceleration detected by the accelerometer of the IMD; determine, based on the received sensed data, changes to one or more physiological parameters of the plurality of physiological parameters, wherein the changes to the one or more physiological parameters comprises one or more of a change in acceleration experienced by the patient or a change in posture of the patient; compare the changes to each of the one or more physiological parameters to a correspond threshold condition of one or more threshold conditions; and based on a determination that the changes to the IMD
  • Example 23 the system of example 22, wherein the at least one threshold condition comprises a threshold change in posture of the patient, and wherein the threshold change in posture comprises a change from a first posture to a second posture within a threshold time period.
  • Example 24 the system of example 23, wherein to determine the change in posture, the processing circuitry is configured to: determine, based on the received sensed data, that the patient is in the first posture at a first time; and determine, based on the received sensed data, that the patient is in the second posture at a second time, wherein the second time is different from the first time, and wherein to determine that the change in posture satisfies the threshold change in posture, the processing circuitry is configured to: determine a time difference between the first time and the second time; compare the time difference against the threshold time period; and determine that the change in posture satisfies the threshold change in posture based on a determination that the time difference is less than or equals to the threshold time period.
  • Example 25 the system of any of examples 22-24, wherein the plurality of physiological parameters comprises one or more of: a heart rate of the patient; a stress hormone level of the patient; a respiration rate of the patient; a body temperature of the patient; a blood pressure of the patient; an electroencephalogram (EEG) signal of the patient; a glucose level of the patient; impedance within tissue of the patient; or a blood oxygen saturation level of the patient.
  • EEG electroencephalogram
  • Example 26 the system of any of examples 22-25, wherein the at least one threshold condition comprises a threshold change in acceleration experienced by the patient.
  • Example 27 the system of example 26, wherein to determine that the change in acceleration satisfies the threshold change in acceleration, the processing circuitry is configured to: compare a current acceleration detected by the acceleration to an average acceleration detected by the accelerometer prior to the current acceleration; and determine that a difference between the current acceleration and the average acceleration satisfies the threshold change in acceleration.
  • Example 28 the system of any of examples 26 and 27, wherein the threshold acceleration is greater than or equals to 3G.
  • Example 29 the system of any of examples 22-28, wherein the processing circuitry is configured to: assign a weight for each of the plurality of physiological parameters; determine, for each physiological parameter of the one or more physiological parameters that satisfy the corresponding threshold condition of the one or more threshold conditions and based on the respective weight, a weighted score; determine, based on a summation of the weighted scores, an aggregate score; compare the aggregate score against a threshold score; and based on a determination that the aggregate score satisfies the threshold score, cause the external computing device to output the notification.
  • Example 30 the system of any of examples 22-29, wherein the processing circuitry is configured to: receive, from the external computing device, information corresponding to a location of the patient; and based on receipt of the information, cause the IMD to sense data corresponding to the plurality of physiological parameters from the patient.
  • Example 31 the system of any of examples 22-30, wherein the processing circuitry is configured to: determine that the user interface of the external computing device did not receive patient input from the patient in response to the notification for a threshold period of time; and based on a determination that the user interface did not receive the patient input for the threshold period of time, output a request for medical aid to a medical care provider.
  • Example 32 the system of any of examples 22-31, wherein the processing circuitry is disposed within the IMD, and wherein the processing circuitry is configured to communicate with the external computing device via communications circuitry disposed within the IMD.
  • Example 33 the system of any of examples 22-32, wherein the processing circuitry comprises a processing circuitry of the external computing device.
  • Example 34 the system of any of examples 22-33, wherein the accelerometer is configured to be implanted within a torso of the patient.
  • Example 35 the system of any of examples 22-34, wherein one or more sensors of the plurality of sensors are configured to implanted in a head of the patient.
  • Example 36 the system of any of examples 22-35, wherein the IMD comprises an insertable cardiac monitor, and wherein the plurality of sensors comprises one or more electrodes.
  • Example 37 the system of example 36, wherein the insertable cardiac monitor comprises: a housing configured for subcutaneous implantation in the patient, the housing having a length between 40 millimeters (mm) and 60 mm between a first end and a second end, a width less than the length, and a depth less than the width; and the one or more electrodes comprising: a first electrode at or proximate to the first end of the housing, and a second electrode at or proximate to the second end of the housing, wherein the insertable cardiac monitor is configured to sense the cardiac signal via the first electrode and the second electrode.
  • the insertable cardiac monitor comprises: a housing configured for subcutaneous implantation in the patient, the housing having a length between 40 millimeters (mm) and 60 mm between a first end and a second end, a width less than the length, and a depth less than the width; and the one or more electrodes comprising: a first electrode at or proximate to the first end of the housing, and a second electrode at or proxi
  • Example 38 the system of any of examples 22-37, wherein the processing circuitry is configured to: receive an indication the user is experiencing a medical event; and cause the external computing device to display the notification to the patient via the user interface in conjunction with the determined medical event.
  • Example 39 the system of example 38, wherein the processing circuitry is configured to cause the external computing device to display the notification to the patient at least a threshold number of hours after occurrence of the external impact.
  • Example 40 a method for operating a medical system comprising an implantable medical device (IMD), the method comprising: sensing, via a plurality of sensors of the IMD configured to be implanted within a patient, information corresponding to a plurality of physiological parameters of the patient, wherein the plurality of sensors comprises an accelerometer; determining, by processing circuitry of the medical system and based on sensed information, changes to one or more physiological parameters of the plurality of physiological parameters, wherein the changes to the one or more physiological parameters comprise one or more of a change in acceleration experienced by the patient or a change in a posture of the patient; comparing, by the processing circuitry, the changes to each of the one or more physiological parameters to a corresponding threshold condition of one or more threshold conditions; and based on a determination that the changes to the one or more physiological parameters satisfy at least one threshold condition of the one or more threshold conditions, transmitting, by the processing circuitry and via communications circuitry of the IMD, a notification to a computing device.
  • IMD implantable medical device
  • Example 41 the method of example 40, wherein the at least one threshold condition comprises a threshold change in posture of the patient, and wherein the threshold change in posture comprises a change from a first posture to a second posture within a threshold time period.
  • Example 42 the method of example 41, wherein determining the change in posture of the patient comprises: determining, by the processing circuitry and based on the sensed information, that the patient is in the first posture at a first time, and determining, by the processing circuitry and based on the sensed information, that the patient is in the second posture at a second time, wherein the second time is different from the first time, and wherein determining that the change in posture satisfies the threshold change in posture comprises: determining, by the processing circuitry, a time difference between the first time and the second time, comparing, by the processing circuitry, the time difference against the threshold time period, and determining, by the processing circuitry, that the change in posture satisfies the threshold change in posture by determining that the time different is less than or equals to the threshold time period.
  • Example 43 the method of any of examples 40-42, wherein the plurality of physiological parameters comprises one or more of: a heart rate of the patient; a stress hormone level of the patient; a respiration rate of the patient; a body temperature of the patient; a blood pressure of the patient; an electroencephalogram (EEG) signal of the patient; a glucose level of the patient; impedance within tissue of the patient; or a blood oxygen saturation level of the patient.
  • the plurality of physiological parameters comprises one or more of: a heart rate of the patient; a stress hormone level of the patient; a respiration rate of the patient; a body temperature of the patient; a blood pressure of the patient; an electroencephalogram (EEG) signal of the patient; a glucose level of the patient; impedance within tissue of the patient; or a blood oxygen saturation level of the patient.
  • EEG electroencephalogram
  • Example 44 the method of any of examples 40-43, wherein the at least one threshold condition comprises a threshold change in acceleration experienced by the patient.
  • Example 45 the method of example 44, wherein comparing the changes to each of the one or more physiological parameters to the corresponding threshold condition comprises: comparing, by the processing circuitry, a current acceleration detected by the acceleration to an average acceleration detected by the accelerometer prior to the current acceleration; and determining, by the processing circuitry, that a difference between the current acceleration and the average acceleration satisfies the threshold change in acceleration.
  • Example 46 the method of any of examples 44 and 45, wherein the threshold acceleration is greater than or equals to 3G.
  • Example 47 the method of any of examples 40-44, further comprising: assigning, by the processing circuitry, a weight for each of the plurality of physiological parameters; determining, by the processing circuitry and for each physiological parameter of the one or more physiological parameters that satisfy the corresponding threshold condition of the one or more threshold conditions and based on the respective weight, a weighted score; determining, by the processing circuitry and based on a summation of the weighted scores, an aggregate score; comparing, by the processing circuitry, the aggregate score against a threshold score; and based on a determination that the aggregate score satisfies the threshold score, transmitting, by the processing circuitry and via the communications circuitry, the notification.
  • Example 48 the method of any of examples 40-47, wherein the accelerometer is configured to be implanted within a torso of the patient.
  • Example 49 the method of any of examples 40-48, wherein one or more sensors of the plurality of sensors are configured to be implanted in a head of the patient.
  • Example 50 the method of any of examples 40-49, wherein the processing circuitry comprises a processing circuitry of the computing device.
  • Example 51 the method of any of examples 40-50, wherein the IMD comprises an insertable cardiac monitor, and wherein the plurality of sensors comprises one or more electrodes.
  • Example 52 the method of example 51, wherein the insertable cardiac monitor comprises: a housing configured for subcutaneous implantation in the patient, the housing having a length between 40 millimeters (mm) and 60 mm between a first end and a second end, a width less than the length, and a depth less than the width; and the one or more electrodes comprising: a first electrode at or proximate to the first end of the housing, and a second electrode at or proximate to the second end of the housing, wherein the insertable cardiac monitor is configured to sense the cardiac signal via the first electrode and the second electrode.
  • the insertable cardiac monitor comprises: a housing configured for subcutaneous implantation in the patient, the housing having a length between 40 millimeters (mm) and 60 mm between a first end and a second end, a width less than the length, and a depth less than the width; and the one or more electrodes comprising: a first electrode at or proximate to the first end of the housing, and a second electrode at or proxi
  • Example 53 the method of any of examples 40-52, further comprising: determining, by the processing circuitry and based on the sensed information, that the patient is experiencing a medical event; and transmitting, by the processing circuitry and via the communications circuitry, the notification to the computing device in conjunction with the determined medical event.
  • Example 54 the method of example 53, wherein transmitting the notification to the computing device in conjunction with the determined medical event comprises: transmitting, by the processing circuitry and via the communications circuitry, the notification to the computing device at least a threshold number of hours after occurrence of the external impact.
  • Example 55 a computer-readable medium comprising instructions that, when executed, causes processing circuitry of a system to perform the method of any of examples 40-54.

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  • Measuring And Recording Apparatus For Diagnosis (AREA)

Abstract

L'invention concerne un dispositif médical implantable (IMD) configuré pour être implanté chez un patient, l'IMD comprenant : une pluralité de capteurs comprenant un accéléromètre ; une circuiterie de communication ; et une circuiterie de traitement couplée à la pluralité de capteurs et à la circuiterie de communication, la circuiterie de traitement étant configurée pour : déterminer, sur la base de données détectées provenant de l'accéléromètre, une variation de l'accélération subie par le patient et une variation de la posture du patient ; déterminer que la variation de l'accélération satisfait une première condition de seuil ; et que la variation de la posture satisfait une seconde condition de seuil ; et sur la base d'une détermination que la variation de l'accélération satisfait la première condition de seuil et que la variation de la posture satisfait la seconde condition de seuil, amener la circuiterie de communication à transmettre une notification à un dispositif informatique, la notification étant configurée pour amener le dispositif informatique à entrer en contact avec un fournisseur de soins médicaux.
PCT/IB2024/055651 2023-07-05 2024-06-10 Système de détection d'impact externe sur un patient Pending WO2025008691A1 (fr)

Applications Claiming Priority (2)

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US202363511952P 2023-07-05 2023-07-05
US63/511,952 2023-07-05

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WO2025008691A1 true WO2025008691A1 (fr) 2025-01-09

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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2016137907A2 (fr) * 2015-02-23 2016-09-01 Cardiac Pacemakers, Inc. Imd activé par capteur de tape
US11308783B2 (en) * 2019-05-29 2022-04-19 Medtronic, Inc. Medical device for fall detection
US11311312B2 (en) 2013-03-15 2022-04-26 Medtronic, Inc. Subcutaneous delivery tool

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11311312B2 (en) 2013-03-15 2022-04-26 Medtronic, Inc. Subcutaneous delivery tool
WO2016137907A2 (fr) * 2015-02-23 2016-09-01 Cardiac Pacemakers, Inc. Imd activé par capteur de tape
US11308783B2 (en) * 2019-05-29 2022-04-19 Medtronic, Inc. Medical device for fall detection

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