Abstract: Augmented reality systems and methods for user health analysis. Methods for user health analysis may include collecting data for an initial prediction model and continuing to collect additional data based on one or more data criteria. The methods may further include updating the initial prediction model based on the additional data to produce a revised prediction model or causing an intervention to occur based on the additional data. The data may be collected by a display system including one or more sensors configured to collect user-specific data and a display device configured to present virtual content to a user. The display device may be configured to output light with variable wavefront divergence.

Abstract: Augmented reality systems and methods for user health analysis. Methods for user health analysis may include collecting data for an initial prediction model and continuing to collect additional data based on one or more data criteria. The methods may further include updating the initial prediction model based on the additional data to produce a revised prediction model or causing an intervention to occur based on the additional data. The data may be collected by a display system including one or more sensors configured to collect user-specific data and a display device configured to present virtual content to a user. The display device may be configured to output light with variable wavefront divergence.

Abstract: Augmented reality systems and methods for user health analysis. Methods for user health analysis may include collecting data for an initial prediction model and continuing to collect additional data based on one or more data criteria. The methods may further include updating the initial prediction model based on the additional data to produce a revised prediction model or causing an intervention to occur based on the additional data. The data may be collected by a display system including one or more sensors configured to collect user-specific data and a display device configured to present virtual content to a user. The display device may be configured to output light with variable wavefront divergence.

Abstract: Augmented reality systems and methods for user health analysis. Methods for user health analysis may include collecting data for an initial prediction model and continuing to collect additional data based on one or more data criteria. The methods may further include updating the initial prediction model based on the additional data to produce a revised prediction model or causing an intervention to occur based on the additional data. The data may be collected by a display system including one or more sensors configured to collect user-specific data and a display device configured to present virtual content to a user. The display device may be configured to output light with variable wavefront divergence.

Abstract: Augmented reality systems and methods for user health analysis. Methods for user health analysis may include collecting data for an initial prediction model and continuing to collect additional data based on one or more data criteria. The methods may further include updating the initial prediction model based on the additional data to produce a revised prediction model or causing an intervention to occur based on the additional data. The data may be collected by a display system including one or more sensors configured to collect user-specific data and a display device configured to present virtual content to a user. The display device may be configured to output light with variable wavefront divergence.

Abstract: The present disclosure pertains to a system configured to generate an adaptive embodied conversational agent to provide interactive virtual coaching to a subject. The system comprises a user interface, one or more hardware processors, and a display. The user interface is configured to obtain input information related to the subject. The one or more hardware processors are configured by machine-readable instructions to: determine a customized digital coaching plan for the subject; and generate visual and/or audio signals that convey the appearance and behavior of the adaptive embodied conversational agent based on the customized digital coaching plan, and/or based on a relationship parameter. The display is configured to receive the generated visual and/or audio signals and cause presentation of the adaptive embodied conversational agent on the display to provide the customized digital coaching plan to the subject interactively.

Abstract: Increasingly, conversational systems are used in coaching or supportive contexts, either in an embodied form (e.g., as an avatar in an app or website) or just in a speech-driven for (e.g. Siri). There is a need to keep such systems interesting and appealing over time in order to prevent the user from reducing use of the system or abandoning the system all together. The present system is configured to learn new expressions from user utterances and use them based on their predicted utility during interactions with the user. The present system includes components configured for learning new vocabulary and selecting vocabulary for generating new utterances from the system. This way, the system continually expands its vocabulary database with expressions familiar to and/or used by the user and will be able to engage the user with new utterances so that the user does not lose interest in the system.

Abstract: Methods and systems for distributed coaching. A plurality of distributed intervention processes each calculate a priority for an intervention technique based on received user data. Then, a central arbiter process selects at least one intervention technique based on the associated priorities to be transmitted to a user to provide a tailored coaching experience for the user.

Abstract: Methods and systems for coaching a user. The system and methods of various calculate at least one relationship determinant value based on a user's behavior. A relationship index value that represents the status of the relationship between a user and a virtual coach is calculated from the determinant value(s). At least one parameter of a coaching plan is then adjusted based on the calculated relationship index value.

Abstract: The present disclosure pertains to a system configured to generate an adaptive embodied conversational agent to provide interactive virtual coaching to a subject. The system comprises a user interface, one or more hardware processors, and a display. The user interface is configured to obtain input information related to the subject. The one or more hardware processors are configured by machine-readable instructions to: determine a customized digital coaching plan for the subject; and generate visual and/or audio signals that convey the appearance and behavior of the adaptive embodied conversational agent based on the customized digital coaching plan, and/or based on a relationship parameter. The display is configured to receive the generated visual and/or audio signals and cause presentation of the adaptive embodied conversational agent on the display to provide the customized digital coaching plan to the subject interactively.

Abstract: Increasingly, conversational systems are used in coaching or supportive contexts, either in an embodied form (e.g., as an avatar in an app or website) or just in a speech-driven for (e.g. Siri). There is a need to keep such systems interesting and appealing over time in order to prevent the user from reducing use of the system or abandoning the system all together. The present system is configured to learn new expressions from user utterances and use them based on their predicted utility during interactions with the user. The present system includes components configured for learning new vocabulary and selecting vocabulary for generating new utterances from the system. This way, the system continually expands its vocabulary database with expressions familiar to and/or used by the user and will be able to engage the user with new utterances so that the user does not lose interest in the system.

Abstract: Augmented reality systems and methods for user health analysis. Methods for user health analysis may include collecting data for an initial prediction model and continuing to collect additional data based on one or more data criteria. The methods may further include updating the initial prediction model based on the additional data to produce a revised prediction model or causing an intervention to occur based on the additional data. The data may be collected by a display system including one or more sensors configured to collect user-specific data and a display device configured to present virtual content to a user. The display device may be configured to output light with variable wavefront divergence.