The present disclosure presents at least one communication interface for prediction of data related to health conditions, wherein the at least one communication interface is configured to receive health-related data, preferably comprising measurement data, from a first user device of a first user, associated with a first time and a first location. The at least one communication interface additionally comprises at least one processor configured to utilize said received health-related data to generate predictive data to be indicated to a second user device of a second user associated with a second time and a second location.

Techniques are disclosed for adjusting a transmission frequency of a physiological monitoring unit, which includes a capture unit and a receiver unit. The capture unit and the receiver unit are wirelessly connected together and are configured to exchange data on the transmission frequency by means of a programming unit.

A device for monitoring a patient includes a substrate, an adhesive layer coupled to a first side of the substrate, and a circuit board coupled to a second side of the substrate. The adhesive layer is configured to adhere to a patient. The device also includes a plurality of switches coupled to the circuit board. Each switch is associated with a respective condition and is switchable by a user between a first state indicating that a corresponding condition is believed to be associated with the patient and a second state indicating that the corresponding condition is not believed to be associated with the patient. The device also includes a wireless transmitter coupled to the circuit board. The wireless transmitter is configured to transmit medical information associated with the patient to a mobile device. The medical information includes data indicating a setting of each of the plurality of switches.

A steerable endoscope is provided with active steering control. An endoscope includes a flexible tubular body with first and second articulating segments, and a camera. In an embodiment, the endoscope includes an orientation sensor. A controller for the endoscope performs an automated analysis of an alignment between the motion axis of the endoscope and the viewing axis of the camera, and actively steers the endoscope to improve the alignment.

Multi-state engagement with continuous glucose monitoring (CGM) systems is described. Given the number of people that wear CGM systems and because CGM systems produce measurements continuously, a platform that provides a CGM system may have an enormous amount of data. This amount of data is practically, if not actually, impossible for humans to process. In implementations, a CGM platform includes a data analytics platform that obtains packages of glucose measurements provided by a CGM system and also obtains additional data associated with a user. The data analytics platform generates state information for the user by processing these CGM packages and the additional data, at least in part, by using one or more models. Based on this state information, the data analytics platform controls communication with the user, which may include generating intervention strategies to prevent users from transitioning to a negative state such as discontinuing use of the CGM system.

Systems and methods described provide dynamic and intelligent ways to change the required level of user interaction during use of a monitoring device. The systems and methods generally relate to real time switching between a first or initial mode of user interaction and a second or new mode of user interaction. In some cases, the switching will be automatic and transparent to the user, and in other cases user notification may occur. The mode switching generally affects the user’s interaction with the device, and not just internal processing. The mode switching may relate to calibration modes, data transmission modes, control modes, or the like.

A portable system is provided for measuring an analyte, such as acetone, in the breath or other bodily fluid of a user. The system includes a portable measurement device that analyzes fluid samples and generates corresponding measurements. The portable measurement device communicates with an application which runs on a smartphone or other mobile device of the user, and the application reports measurement data to a remote system.

A method and system for monitoring a user's intoxication including receiving a set of signals, derived from a set of samples collected from the user at a set of time points; providing a sobriety task to the user proximal to a time point of the set of time points; generating a performance dataset characterizing performance of the sobriety task by the user; receiving a supplementary dataset characterizing a demographic profile of the user and/or a physiological state of the user; determining a set of values of an intoxication metric, derived from the set of signals; generating a predicted temporal profile of the intoxication metric for the user based upon the set of values, the set of time points, and the supplementary dataset; generating an analysis of the user's sobriety based upon the performance dataset and the predicted temporal profile; and providing a notification to the user based upon the analysis.

In order to determine a degree of dementia of a user, contents are output through a user terminal, a voice of the user for a content acquired by a microphone of the user terminal is received, a spectrogram image is generated by visualizing the voice, and the degree of dementia of the user is determined by means of a convolutional neural network (CNN) and a deep neural network (DNN) based on the spectrogram image.

A method and apparatus for quantifying differences in human sensorimotor performance useful for diagnosing, assessing, and/or detecting brain injury and/or a neurological disorder, or identifying exceptional performance in a subject. In a task a subject's limb movement is restricted to a limited workspace and an object moves towards the limb. The objective of the task is for the subject to contact the object with the limb within a set time period. During the task a perturbation directed to the object and/or limb, or other feature of the environment, may occur on some trials, requiring a rapid motor correction in order to contact the object, or the subject may receive an alternative instruction on whether to interact with the object. Position data and/or motion data and/or kinetic data of the limb or portions thereof with respect to a presented object are obtained, and a data set is acquired for a plurality of trials. The acquired data set provides information about brain injury and/or a neurological disorder in the subject or exceptional capabilities of the subject.