Abstract: Sensory inputs of a user can be received by a computing device. At least one of the sensory inputs can include a physiological input providing a physiological measurement from a body of the user. Each sensory input can be processed in a unique one of a set of standards-defined sensory channels, each corresponding to a specific emotion dimension. Processing the sensory inputs can transform the physiological measurement into an emotion dimension value. The emotion dimension values from each of the sensory channels can be aggregated to generate at least one emotion datum value, which is a standards-defined value for an emotional characteristic of the user. Historical data for a user can be optionally collected and used by a learning and calibration component to improve the accuracy of the generated emotion datum values for a specific individual. A programmatic action driven by the emotion datum value can be performed.

Abstract: Sensory inputs of a user can be received by a computing device. At least one of the sensory inputs can include a physiological input providing a physiological measurement from a body of the user. Each sensory input can be processed in a unique one of a set of standards-defined sensory channels, each corresponding to a specific emotion dimension. Processing the sensory inputs can transform the physiological measurement into an emotion dimension value. The emotion dimension values from each of the sensory channels can be aggregated to generate at least one emotion datum value, which is a standards-defined value for an emotional characteristic of the user. Historical data for a user can be optionally collected and used by a learning and calibration component to improve the accuracy of the generated emotion datum values for a specific individual. A programmatic action driven by the emotion datum value can be performed.

Abstract: Sensory inputs of a user can be received by a computing device. At least one of the sensory inputs can include a physiological input providing a physiological measurement from a body of the user. Each sensory input can be processed in a unique one of a set of standards-defined sensory channels, each corresponding to a specific emotion dimension. Processing the sensory inputs can transform the physiological measurement into an emotion dimension value. The emotion dimension values from each of the sensory channels can be aggregated to generate at least one emotion datum value, which is a standards-defined value for an emotional characteristic of the user. Historical data for a user can be optionally collected and used by a learning and calibration component to improve the accuracy of the generated emotion datum values for a specific individual. A programmatic action driven by the emotion datum value can be performed.