Abstract: A system, method and network architecture for facilitating remote care delivery involving a patient having an implantable medical device (IMD). Upon establishing a remote care session between a patient controller device and a clinician programmer, wherein the clinician and the patient are remotely located with respect to each other, telehealth consultation may be provided to the patient by the clinician via an audiovisual (AV) communications session channel. Responsive to determining that the patient requires remote therapy, one or more (re)programming instructions may be provided to the patient's IMD via a remote therapy session channel of the remote care session using an integrated graphical user interface (GUI) that may include suitable GUI controls for AV communications, remote session control as well as the remote programming of the patient's IMD.

Abstract: A system and method for facilitating device and application authentication between an external device and an implanted medical device (IMD), wherein a therapy application executing on the external device is operative to communicate with the IMD via wireless telemetry communications. A device authentication parameter may be decomposed into two key components, wherein one component may be stored in a cloud key vault and the other component may be distributed to the external device as an obfuscated portion embedded in the therapy application. Upon receiving the therapy application, the external device is operative to separately retrieve both key components and reconstitute the original authentication parameter therefrom, which may be presented to the IMD for authentication.

Abstract: The present disclosure is directed to providing digital health services. In some embodiments, systems and methods for conducting virtual or remote sessions between patients and clinicians are disclosed. During the sessions, media content (e.g., images, video content, audio content, etc.) may be captured as the patient performs one or more tasks. The media content may be presented to the clinician and used to evaluate a condition of the patient or a state of the condition, adjust treatment parameters, provide therapy, or other operations to treat the patient. The analysis of the media content may be aided by one or more machine learning/artificial intelligence models that analyze various aspects of the media content, augment the media content, or other functionality to aid in the treatment of the patient.

Abstract: A digital healthcare architecture including a cloud-based virtual clinic platform configured to facilitate remote therapy of one or more patients based on biometric authentication systems and methods. In an example arrangement, one or more biometric indicia of a user (e.g., a clinician and/or a patient) as well as one or more non-biometric input factors may be used in authenticating the user prior to granting access to a protected resource or application (e.g., a therapy application executing on a UE device) configured for effectuating remote programming of an implantable medical device (IMD) operative to provide therapy to the patient.

Abstract: The present disclosure is directed to providing digital health services. In some embodiments, systems and methods for conducting virtual or remote sessions between patients and clinicians are disclosed. During the sessions, media content (e.g., images, video content, audio content, etc.) may be captured as the patient performs one or more tasks. The media content may be presented to the clinician and used to evaluate a condition of the patient or a state of the condition, adjust treatment parameters, provide therapy, or other operations to treat the patient. The analysis of the media content may be aided by one or more machine learning/artificial intelligence models that analyze various aspects of the media content, augment the media content, or other functionality to aid in the treatment of the patient.

Abstract: A system and method for facilitating device and application authentication between an external device and an implanted medical device (IMD), wherein a therapy application executing on the external device is operative to communicate with the IMD via wireless telemetry communications. A device authentication parameter may be decomposed into two key components, wherein one component may be stored in a cloud key vault and the other component may be distributed to the external device as an obfuscated portion embedded in the therapy application. Upon receiving the therapy application, the external device is operative to separately retrieve both key components and reconstitute the original authentication parameter therefrom, which may be presented to the IMD for authentication.

Abstract: The present disclosure is directed to providing digital health services. In some embodiments, systems and methods for conducting virtual or remote sessions between patients and clinicians are disclosed. During the sessions, media content (e.g., images, video content, audio content, etc.) may be captured as the patient performs one or more tasks. The media content may be presented to the clinician and used to evaluate a condition of the patient or a state of the condition, adjust treatment parameters, provide therapy, or other operations to treat the patient. The analysis of the media content may be aided by one or more machine learning/artificial intelligence models that analyze various aspects of the media content, augment the media content, or other functionality to aid in the treatment of the patient.

Abstract: The present disclosure is directed to providing digital health services. In some embodiments, systems and methods for conducting virtual or remote sessions between patients and clinicians are disclosed. During the sessions, media content (e.g., images, video content, audio content, etc.) may be captured as the patient performs one or more tasks. The media content may be presented to the clinician and used to evaluate a condition of the patient or a state of the condition, adjust treatment parameters, provide therapy, or other operations to treat the patient. The analysis of the media content may be aided by one or more machine learning/artificial intelligence models that analyze various aspects of the media content, augment the media content, or other functionality to aid in the treatment of the patient.

Abstract: The present disclosure is directed to providing digital health services. In some embodiments, systems and methods for conducting virtual or remote sessions between patients and clinicians are disclosed. During the sessions, media content (e.g., images, video content, audio content, etc.) may be captured as the patient performs one or more tasks. The media content may be presented to the clinician and used to evaluate a condition of the patient or a state of the condition, adjust treatment parameters, provide therapy, or other operations to treat the patient. The analysis of the media content may be aided by one or more machine learning/artificial intelligence models that analyze various aspects of the media content, augment the media content, or other functionality to aid in the treatment of the patient.

Abstract: The present disclosure is directed to providing digital health services. In some embodiments, systems and methods for conducting virtual or remote sessions between patients and clinicians are disclosed. During the sessions, media content (e.g., images, video content, audio content, etc.) may be captured as the patient performs one or more tasks. The media content may be presented to the clinician and used to evaluate a condition of the patient or a state of the condition, adjust treatment parameters, provide therapy, or other operations to treat the patient. The analysis of the media content may be aided by one or more machine learning/artificial intelligence models that analyze various aspects of the media content, augment the media content, or other functionality to aid in the treatment of the patient.

Abstract: The present disclosure is directed to providing digital health services. In some embodiments, systems and methods for conducting virtual or remote sessions between patients and clinicians are disclosed. During the sessions, media content (e.g., images, video content, audio content, etc.) may be captured as the patient performs one or more tasks. The media content may be presented to the clinician and used to evaluate a condition of the patient or a state of the condition, adjust treatment parameters, provide therapy, or other operations to treat the patient. The analysis of the media content may be aided by one or more machine learning/artificial intelligence models that analyze various aspects of the media content, augment the media content, or other functionality to aid in the treatment of the patient.

Abstract: The present disclosure is directed to providing digital health services. In some embodiments, systems and methods for conducting virtual or remote sessions between patients and clinicians are disclosed. During the sessions, media content (e.g., images, video content, audio content, etc.) may be captured as the patient performs one or more tasks. The media content may be presented to the clinician and used to evaluate a condition of the patient or a state of the condition, adjust treatment parameters, provide therapy, or other operations to treat the patient. The analysis of the media content may be aided by one or more machine learning/artificial intelligence models that analyze various aspects of the media content, augment the media content, or other functionality to aid in the treatment of the patient.

Abstract: A digital healthcare architecture including a cloud-based virtual clinic platform configured to facilitate remote therapy of one or more patients based on biometric authentication systems and methods. In an example arrangement, one or more biometric indicia of a user (e.g., a clinician and/or a patient) as well as one or more non-biometric input factors may be used in authenticating the user prior to granting access to a protected resource or application (e.g., a therapy application executing on a UE device) configured for effectuating remote programming of an implantable medical device (IMD) operative to provide therapy to the patient.

Abstract: The present disclosure is directed to providing digital health services. In some embodiments, systems and methods for conducting virtual or remote sessions between patients and clinicians are disclosed. During the sessions, media content (e.g., images, video content, audio content, etc.) may be captured as the patient performs one or more tasks. The media content may be presented to the clinician and used to evaluate a condition of the patient or a state of the condition, adjust treatment parameters, provide therapy, or other operations to treat the patient. The analysis of the media content may be aided by one or more machine learning/artificial intelligence models that analyze various aspects of the media content, augment the media content, or other functionality to aid in the treatment of the patient.

Abstract: The present disclosure is directed to providing digital health services. In some embodiments, systems and methods for conducting virtual or remote sessions between patients and clinicians are disclosed. During the sessions, media content (e.g., images, video content, audio content, etc.) may be captured as the patient performs one or more tasks. The media content may be presented to the clinician and used to evaluate a condition of the patient or a state of the condition, adjust treatment parameters, provide therapy, or other operations to treat the patient. The analysis of the media content may be aided by one or more machine learning/artificial intelligence models that analyze various aspects of the media content, augment the media content, or other functionality to aid in the treatment of the patient.

Abstract: The present disclosure is directed to providing digital health services. In some embodiments, systems and methods for conducting virtual or remote sessions between patients and clinicians are disclosed. During the sessions, media content (e.g., images, video content, audio content, etc.) may be captured as the patient performs one or more tasks. The media content may be presented to the clinician and used to evaluate a condition of the patient or a state of the condition, adjust treatment parameters, provide therapy, or other operations to treat the patient. The analysis of the media content may be aided by one or more machine learning/artificial intelligence models that analyze various aspects of the media content, augment the media content, or other functionality to aid in the treatment of the patient.

Abstract: Implementations for adaptive context sensitive time division multiplexed scheduling and execution of tasks to be performed by a high frequency ablation system, such as an RF ablation system, are disclosed. The implementations may be effectuated in software, firmware, or both. Tasks may be categorized into categories corresponding to task priorities. Time blocks may be allocated during which execution of the tasks may be performed. The time blocks may be divided into time slots. A task may be assigned to a time slot based, at least in part, on a categorization priority of the task. Additionally, each task may be executed according to the schedule delineated by the time slots. An assignment of tasks to time slots may be adjusted based, at least in part, on data received at a high frequency ablation device of the high frequency ablation system.

Abstract: A system and method for facilitating remote care management involving a patient having an implantable medical device (IMD). Upon establishing a remote care session between a patient controller device and a clinician programmer, wherein the clinician and the patient are remotely located with respect to each other, input from the patient or the clinician may be received via a user interface control associated with a particular functionality or aspect of the remote care session, including audiovisual (AV) communications, remote therapy programming, and related context. Responsive to the user input, a dialog interface is effectuated at one of the patient controller device and/or the clinician programmer. A user characterization label is received via the dialog interface from the user, wherein the user characterization label is indicative of a subjective assessment of the particular functionality of the remote care session, which may be used in generating user-labeled data pertaining thereto.

Abstract: A system and method for facilitating remote care management involving a patient having an implantable medical device (IMD). Upon establishing a remote care session between a patient controller device and a clinician programmer, wherein the clinician and the patient are remotely located with respect to each other, input from the patient or the clinician may be received via a user interface control associated with a particular functionality or aspect of the remote care session, including audiovisual (AV) communications, remote therapy programming, and related context. Responsive to the user input, a dialog interface is effectuated at one of the patient controller device and/or the clinician programmer. A user characterization label is received via the dialog interface from the user, wherein the user characterization label is indicative of a subjective assessment of the particular functionality of the remote care session, which may be used in generating user-labeled data pertaining thereto.

Abstract: The present disclosure is directed to providing digital health services. In some embodiments, systems and methods for conducting virtual or remote sessions between patients and clinicians are disclosed. During the sessions, media content (e.g., images, video content, audio content, etc.) may be captured as the patient performs one or more tasks. The media content may be presented to the clinician and used to evaluate a condition of the patient or a state of the condition, adjust treatment parameters, provide therapy, or other operations to treat the patient. The analysis of the media content may be aided by one or more machine learning/artificial intelligence models that analyze various aspects of the media content, augment the media content, or other functionality to aid in the treatment of the patient.