An apparatus for predicting a body temperature is provided. The apparatus includes an external environment/activity estimation neural network configured to detect at least one facial region as a region of interest from an input thermal image of a target person to be measured, and estimate an environmental type including an external temperature and participation in physical activity based on a temperature of the at least one region of interest. The apparatus further includes a body temperature prediction neural network configured to predict a body temperature of the target person based on the environmental type estimated by the external environment/activity estimation neural network and the temperature of the at least one region of interest.

An apparatus for estimating a core body temperature of an object is provided. The apparatus may include a heat flow sensor configured to measure a first heat flux from an object, a first temperature sensor positioned under a thermal conducting material and configured to measure a surface temperature of the object, a second temperature sensor positioned above the thermal conducting material and configured to measure a surface temperature of the thermal conducting material, and a processor configured to obtain a second heat flux by calibrating the first heat flux based on the surface temperature of the object and the surface temperature of the thermal conducting material, and configured to estimate a core body temperature of the object based on the obtained second heat flux and the surface temperature of the object.

This document discusses, among other things, systems and methods to compensate for the effects of temperature on sensors, such as analyte sensor. An example method may include determining a temperature-compensated glucose concentration level by receiving a temperature signal indicative of a temperature parameter of an external component, receiving a glucose signal indicative of an in vivo glucose concentration level, and determining a compensated glucose concentration level based on the glucose signal, the temperature signal, and a delay parameter.

Methods, systems and computer program products provide for a Risk Assessment Engine that receives body ambient temperature data captured by a sensor in contact with a person. The Risk Assessment Engine characterizes types of activities performed by the person during a time range associated with the body ambient temperature data. The Risk Assessment Engine determines a risk classification individualized for the person based on respective workloads and the corresponding allocations of work and rest experienced by the person during performance of the characterized types of activities.

A smartphone or other mobile computer device, general purpose or specialized, wherein the smartphone device is configured to actively control the configuration of one or more bladders, compartments, chambers or internal sipes and one or more sensors located in either one or both of a sole or a removable inner sole insert of the footwear of the user and/or located in an apparatus worn or carried by the user, glued unto the user, or implanted in the user. The one or more bladders, compartments, chambers, or sipes, and one or more sensors are configured for computer control. A sole and/or a removable inner sole insert for footwear, including one or more bladders, compartments, chambers, internal sipes and sensors in the sole and/or in a removable insert; or on an insole; all being configured for control by a smartphone or other mobile computer device, general purpose or specialized.

A wearable device configured to secure to skin of a user and noninvasively measure body temperature of the user can include first and second pairs of temperature sensors configured to generate one or more signals responsive to detected thermal energy, a thermally conductive element positioned at least partially between the second pair of temperature sensors, and one or more hardware processors configured to receive the one or more signals generated by each of said first and second pairs of temperature sensors and determine one or more body temperature values of the user based on at least comparisons between different ones of the first and second pairs of temperature sensors. In some implementations, the wearable device includes thermally conductive probes for transmitting thermal energy toward ones of the first and second pairs of temperature sensors and a substrate positioned between the probes and the skin.

A system for screening persons' temperatures comprises an imaging device configured to generate imagery data, including infrared image data, of a first scene and a second scene. The system receives imagery data from the first scene, identifies persons in the scene using the imagery data, and determines each person's temperature. The system further compares the persons' temperatures to a threshold and indicates a person should be directed to the second scene if the person's temperature is above a threshold. Subsequently, the system determines and compares the person's temperature in the second scene and provides an indication if the person's temperature exceeds a second threshold. Further, a confidence factor can be associated with determinations of persons' temperatures.

A computer device generates a response to an emergency being reported by a plurality of sensor devices. The memory contains a sensor data engine and a determinant code calculator. The computer device determines the likelihood of an emergency based on received sensor data and, in some embodiments, answers received from an information provider. The sensor data engine receives external sensor data, determines data values associated with the external sensor data, and calculates an emergency likelihood based on the data values. The determinant code calculator generates a determinant code based on the calculated likelihood, and provides the code to an emergency responder system to generate an emergency dispatch response.

A method of calibrating an analyte measurement system is provided.

Remote health services may be provided, for example, in real time, based on values of health metrics monitored remotely, and in some embodiments, continuously, for a recipient. The system may include a mobile health device configured to continually monitor or intermittently detect values of one or more health metrics. A mobile health device may be locally coupled to a recipient, and may include a health sensor that detects values of one or more health metrics of the recipient. Servers may be remotely coupled to the mobile health device and provide one or more health services based at least in part on health metric values detected by the health device. Providing the services may include determining health communication characteristics, and sending health communications from one or more servers to the mobile health device according to determined health communication characteristics.