Abstract: Provided herein are methods of determining a cognitive load of a sensorized device user in certain aspects. Provided herein are also methods of adjusting an interface between a user and a sensorized device in some aspects. Related devices, systems, and computer program products are also provided.

Abstract: A device may receive an X-ray image captured by a C-arm CBCT device at a particular position defined by a six-degree of freedom pose relative to an anatomy, and may process the X-ray image, with a machine learning model, to determine a predicted quality of next possible X-ray images provided by the C-arm CBCT device. The device may utilize the machine learning model, to identify a particular X-ray image, of the next possible X-ray images, with a greatest predicted quality and to update the six-degree of freedom pose based on the particular X-ray image. The device may provide, to the C-arm CBCT device, data that identifies the updated six-degree of freedom pose to cause the C-arm CBCT device to adjust to a new position based on the updated six-degree of freedom pose.

Abstract: Provided herein are methods of determining a cognitive load of a sensorized device user in certain aspects. Provided herein are also methods of adjusting an interface between a user and a sensorized device in some aspects. Related devices, systems, and computer program products are also provided.

Abstract: A device may receive, from an imaging device, a two-dimensional image of a patient being operated on by a user, where the two-dimensional image captures a portion of the patient, and where the portion of the patient is provided between a focal point of an imaging source of the imaging device and a detector plane of the imaging device. The device may translate the two-dimensional image along a frustum of the imaging source, and may generate one or more images in a three-dimensional space based on translating the two-dimensional image along the frustum of the imaging source. The device may provide the one or more images in the three-dimensional space to an augmented reality device associated with the user.

Abstract: A device may receive an X-ray image captured by a C-arm CBCT device at a particular position defined by a six-degree of freedom pose relative to an anatomy, and may process the X-ray image, with a machine learning model, to determine a predicted quality of next possible X-ray images provided by the C-arm CBCT device. The device may utilize the machine learning model, to identify a particular X-ray image, of the next possible X-ray images, with a greatest predicted quality and to update the six-degree of freedom pose based on the particular X-ray image. The device may provide, to the C-arm CBCT device, data that identifies the updated six-degree of freedom pose to cause the C-arm CBCT device to adjust to a new position based on the updated six-degree of freedom pose.

Abstract: Provided herein are methods of determining a cognitive load of a sensorized device user in certain aspects. Provided herein are also methods of adjusting an interface between a user and a sensorized device in some aspects. Related devices, systems, and computer program products are also provided.

Abstract: A device may receive an X-ray image captured by a C-arm CBCT device at a particular position defined by a six-degree of freedom pose relative to an anatomy, and may process the X-ray image, with a machine learning model, to determine a predicted quality of next possible X-ray images provided by the C-arm CBCT device. The device may utilize the machine learning model, to identify a particular X-ray image, of the next possible X-ray images, with a greatest predicted quality and to update the six-degree of freedom pose based on the particular X-ray image. The device may provide, to the C-arm CBCT device, data that identifies the updated six-degree of freedom pose to cause the C-arm CBCT device to adjust to a new position based on the updated six-degree of freedom pose.

Abstract: Provided herein are methods of detecting a pathology in an ear of a subject that include matching properties of captured images and/or videos with properties of an ear pathology model that is trained on a plurality of reference images and/or videos of ears of reference subjects, which properties of the ear pathology model are indicative of the pathology. Related kits, devices, systems, and computer program products are also provided.

Abstract: A computer-implemented method for displaying augmented reality (AR) content within an AR device coupled to one or more loupe lenses comprising: obtaining calibration parameters defining a magnified display portion within a display of the AR device, wherein the magnified display portion corresponds to boundaries encompassing the one or more loupe lenses; receiving the AR content for display within the AR device; and rendering the AR content within the display, wherein the rendering the AR content comprises: identifying a magnified portion of the AR content to be displayed within the magnified display portion, and rendering the magnified portion of the AR content within the magnified display portion.

Abstract: A device may receive an X-ray image captured by a C-arm CBCT device at a particular position defined by a six-degree of freedom pose relative to an anatomy, and may process the X-ray image, with a machine learning model, to determine a predicted quality of next possible X-ray images provided by the C-arm CBCT device. The device may utilize the machine learning model, to identify a particular X-ray image, of the next possible X-ray images, with a greatest predicted quality and to update the six-degree of freedom pose based on the particular X-ray image. The device may provide, to the C-arm CBCT device, data that identifies the updated six-degree of freedom pose to cause the C-arm CBCT device to adjust to a new position based on the updated six-degree of freedom pose.

Abstract: A device may receive, from an imaging device, a two-dimensional image of a patient being operated on by a user, where the two-dimensional image captures a portion of the patient, and where the portion of the patient is provided between a focal point of an imaging source of the imaging device and a detector plane of the imaging device. The device may translate the two-dimensional image along a frustum of the imaging source, and may generate one or more images in a three-dimensional space based on translating the two-dimensional image along the frustum of the imaging source. The device may provide the one or more images in the three-dimensional space to an augmented reality device associated with the user.

Abstract: The present invention is directed to a system and method for image to world registration for medical reality applications, using a world spatial map. This invention is a system and method to link any point in a fluoroscopic image to its corresponding position in the visual world using spatial mapping with a head mounted display (HMD) (world tracking). On a projectional fluoroscopic 2D image, any point on the image can be thought of as representing a line that is perpendicular to the plane of the image that intersects that point. The point itself could lie at any position in space along this line, located between the X-Ray source and the detector. With the aid of the HMD, a virtual line is displayed in the visual field of the user.