The disclosed apparatus, systems and methods relate to tracking abdominal orientation and activity for purposes of preventing or treating conditions of pregnancy, respiratory diseases or other types of medical conditions. In certain specific embodiments, the system, device, or method relates to identifying abdominal or sleep position orientation risk values, calculating and updating a cumulative risk value, comparing the cumulative risk value to a threshold, and outputting a warning when the cumulative risk value crosses the threshold.

Provided are computer-implemented methods and systems for generating and/or utilizing data analysis algorithm(s) for providing operating instructions, enhancements and/or recommendations to optimize insertion of a medical instrument toward a target in a body of a patient based, inter alia, on data related to an automated medical device and/or to operation thereof.

Provided are computer-implemented methods and systems for generating and/or utilizing model(s) for determining optimized checkpoint locations along a trajectory in an image-guided procedure for inserting a medical instrument to a target in a body of a patient based, inter alia, on data related to an automated medical device and/or to operation thereof.

Methods and apparatus for guiding medical care based on sensor data from the gastrointestinal tract are described utilizing an apparatus which can be used with enteral feeding. Generally, the apparatus includes an elongated body having a length configured for insertion into a stomach and at least one pair of electrodes located along the length of the elongated body and positionable for placement within the stomach. A controller in electrical communication with the at least one pair of electrodes is included and the control may also be configured to measure a conductivity or impedance between the pair of electrodes and to determine a gastric residual volume of the stomach based on the measured conductivity or impedance.

Embodiments include a system for determining patient cardiovascular information which includes at least one computer system configured to receive patient-specific data regarding a geometry of an anatomical structure of a patient; create a model representing at least a portion of the anatomical structure of the patient based on the patient-specific data; determine a first blood flow rate at at least one point of interest in the model by using relations of individual-specific anatomic data to functional estimates of blood flow characteristics generated from a plurality of individuals; modify the model; determine a second blood flow rate at a point in the modified model corresponding to the at least one point of interest by using the relations of individual-specific anatomic data to functional estimates of blood flow characteristics; and determine a fractional flow reserve value as a ratio of the second blood flow rate to the first blood flow rate.

A computer-implemented method for estimating surface area and/or volume of a subject's body or body part. First, at least one image, including the subject's face, is obtained. The image is processed to determine facial image parameter(s) of the subject's face. The subject's characteristic(s) including age, weight, height, and/or gender—is/are also determined. A facial parametric model and the facial image parameters are used to determine facial shape parameters of the subject's face, where the facial parametric model relates specific values for facial image parameters to a respective 3D representation of a face having respective values for the facial shape parameters. A prediction model with the characteristic(s) and the facial shape parameters are used to predict a 3D representation of the subject's full body. The predicted 3D representation of the subject's full body is analyzed to estimate the surface area and/or volume of the subject's body or body part.

A measurement device is disclosed for measuring a change in one or more of a circumference or a perimeter of at least a portion of an object having a surface. The measurement device includes a first part for attachment to the object, a second part having a first portion moveable relative to a first portion of the first part, a determining device for determining a displacement of the first portion of the second part relative to the first portion of the first part caused by the object changing, and a biasing device for biasing the first part and the second part towards engagement. The measured displacement is for use in determining the change in one or more of a circumference or a perimeter of the object.

A system for image segmentation is provided. The system may obtain a target image including an ROI, and segment a preliminary region representative of the ROI from the target image using a first ROI segmentation model corresponding to a first image resolution. The system may segment a target region representative of the ROI from the preliminary region using a second ROI segmentation model corresponding to a second image resolution. At least one model of the first and second ROI segmentation models may at least include a first convolutional layer and a second convolutional layer downstream to the first convolutional layer. A count of input channels of the first convolutional layer may be greater than a count of output channels of the first convolutional layer, and a count of input channels of the second convolutional layer may be smaller than a count of output channels of the second convolutional layer.

A method of determining a likelihood of presence of at least one type of arthritis in a hand of a patient is provided, the method comprising capturing an image of a hand of the patient, processing the hand image to determine at least one first predictive value indicative of presence or absence of arthritis in the hand based on presence or absence of a plurality of identifiable hand features in the hand image, the identifiable hand features including visible physical hand features that are usable to diagnose arthritis in the hand, receiving patient information from the patient, the patient information comprising a plurality of responses to a plurality of respective questions that are relevant to diagnosing arthritis in the hand, and determining a likelihood of presence of at least one type of arthritis in the hand using the at least one first predictive value and the patient information.

Methods and apparatus for guiding medical care based on sensor data from the gastrointestinal tract are described utilizing an apparatus which can be used with enteral feeding. Generally, the apparatus includes an elongated body having a length configured for insertion into a stomach and at least one pair of electrodes located along the length of the elongated body and positionable for placement within the stomach. A controller in electrical communication with the at least one pair of electrodes is included and the control may also be configured to measure a conductivity or impedance between the pair of electrodes and to determine a gastric residual volume of the stomach based on the measured conductivity or impedance.