An examination system having separate enabled interchangeable operating modes includes at least one medical device having a housing retaining an optical system. The examination system further includes an adapter that is configured for aligning a plurality of disparate smart devices with the optical system of the medical device when the adapter is attached to the medical device, thereby enabling multiple operating modes without modification to the device. In at least one version, common engagement features are provided on a plurality of medical devices to permit the adapter and an attached smart device to be used therewith interchangeably.

Devices, systems and methods are disclosed that allow a patient to self-treat epileptic seizures by electrical noninvasive stimulation of a vagus nerve. The system comprises a handheld stimulator that is applied to the surface of the patient's neck, wherein the stimulator comprises or is joined to a smartphone. A camera of the smartphone may be used to position and reposition the stimulator to a particular location on the patient's neck. The system may also comprise a base station that is used to meter the charging of a rechargeable battery within the stimulator. The base station and stimulator transmit data to one another regarding the status of a stimulation session.

Images are analyzed using sub-sectional component evaluation in order to augment classifier usage. An image of an individual is obtained. The face of the individual is identified, and regions within the face are determined. The individual is evaluated to be within a sub-sectional component of a population based on a demographic or based on an activity. An evaluation of content of the face is performed based on the individual being within a sub-sectional component of a population. The sub-sectional component of a population is used for disambiguating among content types for the content of the face. A Bayesian framework that includes a conditional probability is used to perform the evaluation of the content of the face, and the evaluation is further based on a prior event that occurred.

A wound characterization system that includes color calibration.

A mobile device based multi-analyte testing analyzer for use in medical diagnostic monitoring and screening, and a method of manufacturing the same are disclosed. A reflectance based, colorimetric test strip reader for use with a mobile device having a jack plug receiving socket, said test strip reader adapted for removably receiving a test strip having a test strip longitudinal axis, comprising a housing; a jack plug operably coupled to and extending from said housing and adapted for operable coupling with said jack plug receiving socket; a test strip adapter including structure defining a test strip receiving channel; a light source oriented within said housing for directing light toward said test strip receiving channel to illuminate a test strip arranged within said test strip adapter; and a light sensor oriented within said housing to sense light reflected from a test strip carried by said test strip receiving channel.

A receiver apparatus is configured to receive a first and second signal from one or more sensors, the first signal comprising a measure of one or more exercise parameters of the user at a first time period of an exercise session, and the second signal comprising a measure of the one or more exercise parameters at a second time period. A processor is configured to store the first and second signals in a memory, generate a fatigue signal based on a comparison of the measured one or more exercise parameters of the first signal to the respective measured one or more exercise parameters of the second signal, generate an exercise efficiency signal based on a comparison of the measured one or more exercise parameters of the second signal to an a priori exercise parameter threshold, and cause the exercise efficiency signal and the fatigue signal to be simultaneously displayed.

A system and method for camera-based stress determination. The method includes: determining a plurality of regions-of-interest (ROIs) of a body part; determining a set of bitplanes in a captured image sequence for each ROI that represent HC changes using a trained machine learning model, the machine learning model trained with a hemoglobin concentration (HC) changes training set, the HC changes training set trained using bitplanes from previously captured image sequences of other human individuals as input and received cardiovascular data as targets; determining an HC change signal for each of the ROIs based on changes in the set of determined bitplanes; for each ROI, determining intervals between heartbeats based on peaks in the HC change signal; determining heart rate variability using the intervals between heartbeats; determining a stress level using at least one determination of a standard deviation of the heart rate variability; and outputting the stress level.

In one embodiment, an apparatus (12) is presented that detects wireless signals from external devices (18) that uniquely identify each of the external devices, records, in memory (30), information about the external devices without access to an external database, and compares information from the external devices to determine a relative location of the wearable device without using additional, power-hungry position location functionality if there is a threshold match in the compared information. In some embodiments, the invention uses the determined relative location to trigger an action at another device. The invention, using self-contained functionality, enables improvements in same location or home location determination accuracy, memory conservation, and power consumption.

The present invention relates to a system and method for diagnosing potential diseases by making facial analysis via image processing techniques from photo and video data available in cloud storing unit and informing the user.

A smartphone-based hemoglobin (Hgb) assessment application quantitatively analyzes pallor in patient-sourced photos using image analysis algorithms to enable a noninvasive, accurate quantitative smartphone app for detecting anemia. A user takes a photo of his/her fingernail beds using the app and receives an accurate displayed Hgb level. Since fingernails do not contain melanocytes, the primary source of color of these anatomical features is blood Hgb. At the same time, quality control software minimizes the impact of common fingernail irregularities (e.g. leukonychia and camera flash reflection) on Hgb level measurement. Metadata recorded upon capturing the image is leveraged for determining a users' Hgb level thereby eliminating the need for external equipment. A personalized calibration of image data with measured Hgb levels improves the accuracy of the application.