A modular wristband and sensor system and method of using the same are disclosed. The system uses top and bottom sensor modules that contain conductive ports for connection to wristbands' conductive ports. The wristbands' conductive ports are electrically connected to wires embedded within each wristband segment. These allow for the transfer of data and power between the bands and the top and bottom sensor modules. Having power and data conducted through wristbands into sensors makes it possible for wristband sensors to have swappable bands while maintaining connectivity. Other embodiments include a wristband that includes swappable top and bottom sensor modules communicating wirelessly with each other.

A modular wristband and sensor system and method of using the same are disclosed. The system uses top and bottom sensor modules that contain conductive ports for connection to wristbands' conductive ports. The wristbands' conductive ports are electrically connected to wires embedded within each wristband segment. These allow for the transfer of data and power between the bands and the top and bottom sensor modules. Having power and data conducted through wristbands into sensors makes it possible for wristband sensors to have swappable bands while maintaining connectivity. Other embodiments include a wristband that includes swappable top and bottom sensor modules communicating wirelessly with each other.

This disclosure relates to technologies for a sensor network, machine-to-machine (M2M) communication, machine type communication (MTC), and Internet of Things (IoT). This disclosure can be utilized in intelligent services based on the above technologies, such as smart homes, smart buildings, smart cities, smart cars or connected cars, health care, digital education, retail sales, security and safety related services, etc. This disclosure relates to a method for generating an instruction for controlling equipment on the basis of biometric information, comprising: a step of obtaining at least one biometric information; a step of determining whether to calculate a calorific value by using stored biometric information and the obtained biometric information, and calculating the calorific value by using the stored biometric information and the obtained biometric information according to the determined result; and generating an instruction for controlling the equipment on the basis of the calculated calorific value.

This disclosure relates to technologies for a sensor network, machine-to-machine (M2M) communication, machine type communication (MTC), and Internet of Things (IoT). This disclosure can be utilized in intelligent services based on the above technologies, such as smart homes, smart buildings, smart cities, smart cars or connected cars, health care, digital education, retail sales, security and safety related services, etc. This disclosure relates to a method for generating an instruction for controlling equipment on the basis of biometric information, comprising: a step of obtaining at least one biometric information; a step of determining whether to calculate a calorific value by using stored biometric information and the obtained biometric information, and calculating the calorific value by using the stored biometric information and the obtained biometric information according to the determined result; and generating an instruction for controlling the equipment on the basis of the calculated calorific value.

A method and an apparatus for assessing an effect of a relaxation stimulus exposed to a human have been disclosed. The method comprises the steps of providing a skin conductance signal measured at an area of the human's skin through a time interval; detecting peaks in the skin conductance signal through the time interval; determining a rate of the peaks through the time interval; and determining the effect of the relaxation stimulus based on the determined rate of peaks through the time interval.

An illustrative system includes a brain interface system configured to be worn by a user and to output brain measurement data representative of brain activity of the user while the user is engaged in an electronic messaging session provided by an electronic messaging platform and a computing device configured to obtain the brain measurement data, determine, based on the brain measurement data, a graphical emotion symbol representative of a mental state of the user while the user is engaged in the electronic messaging session, and provide the graphical emotion symbol for use during the electronic messaging session.

A method, performed by a wearable device, of providing haptic feedback to a user is provided. The method includes obtaining profile data of the user, obtaining biometric data of the user by using one or more biosensors, calculating, based on the profile data and the biometric data of the user, a target contact pressure to be applied to a body of the user by one or more haptic actuators, measuring a current contact pressure applied to the body of the user by the one or more haptic actuators by using one or more pressure sensors, and adjusting the current contact pressure of the one or more haptic actuators based on the current contact pressure and the target contact pressure.

Disclosed herein is a system, including a mobile device; a sensor module attached to the mobile device, the sensor module including a temperature sensor, an infrared sensor, at least one conductance sensor, and at least one electromyography sensor; and an application installed on the mobile device, wherein during operation the application causes the mobile device to receive data from one or more of the temperature sensor, the infrared sensor, the at least one conductance sensor, and the at least one electromyography sensor, and to determine information about a stress level of a human subject based on the received data.

Disclosed herein is a system, including a mobile device; a sensor module attached to the mobile device, the sensor module including a temperature sensor, an infrared sensor, at least one conductance sensor, and at least one electromyography sensor; and an application installed on the mobile device, wherein during operation the application causes the mobile device to receive data from one or more of the temperature sensor, the infrared sensor, the at least one conductance sensor, and the at least one electromyography sensor, and to determine information about a stress level of a human subject based on the received data.

The present invention relates to a method to predict the risk of obtaining a stress related mood disorder or syndrome by a person, comprising a. Measuring at least three parameters comprising at least one sympathetic, one parasympathetic and one hormonal parameter during a stress response, said result of the measurement depicted as RS, RP and RH respectively; b. Estimate the value of one of these parameters by calculating it from the other two parameters; c. Predict the risk on basis of the deviation between calculated and measured value of the parameter that has been estimated in step b).