Abstract: The disclosure provides methods and systems for determining an emotional fitness metrics for users. A physiological parameter of the user is measured during a group activity using at least one biosensor to acquire a measured signal. The measured signal of the user is compared to a measured signal for the physiological parameter of one or more additional users as measured when the one or more additional users perform the group activity. An emotional connectivity may be calculated based on a synchronicity of the measured signal of the user with the measured signal of the one or more additional users, as well as a cognitive appraisal metric, a resilience metric and an emotional fitness metric. Connectivity values for user pairings for a group activity can be computed based a synchronicity in a time-series correlation for the physiological parameters for permutations of the user pairings for the group activity.

Abstract: The disclosure provides methods and systems for determining an emotional fitness metrics for users. A physiological parameter of the user is measured during a group activity using at least one biosensor to acquire a measured signal. The measured signal of the user is compared to a measured signal for the physiological parameter of one or more additional users as measured when the one or more additional users perform the group activity. An emotional connectivity may be calculated based on a synchronicity of the measured signal of the user with the measured signal of the one or more additional users, as well as a cognitive appraisal metric, a resilience metric and an emotional fitness metric. Connectivity values for user pairings for a group activity can be computed based a synchronicity in a time-series correlation for the physiological parameters for permutations of the user pairings for the group activity.

Abstract: The disclosure provides methods and systems for determining an emotional fitness metrics for users. A physiological parameter of the user is measured during a group activity using at least one biosensor to acquire a measured signal. The measured signal of the user is compared to a measured signal for the physiological parameter of one or more additional users as measured when the one or more additional users perform the group activity. An emotional connectivity may be calculated based on a synchronicity of the measured signal of the user with the measured signal of the one or more additional users, as well as a cognitive appraisal metric, a resilience metric and an emotional fitness metric. Connectivity values for user pairings for a group activity can be computed based a synchronicity in a time-series correlation for the physiological parameters for permutations of the user pairings for the group activity.

Abstract: There is described a system for providing an interface with personalized products or product recommendations by capturing user data with sensors and computing a physical and/or emotional signature of the user. The user data comprises at least image data, text input, biometric data, and audio data, and may have been captured using one or more sensors on the user device. The user data is processed using at least: facial analysis; body analysis; eye tracking; behavioural analysis; social network analysis; location analysis; user's activities analysis; speech analysis, and text analysis. Based on the user data, one or more states of one or more cognitive-affective competencies of the user may be determined. An is determined, based on the one or more states of the one or more cognitive-affective competencies of the user. Based on the physical and/or emotional signature, one or more personalized products or product recommendations are generating for improving the emotional signature or physical signature.