Abstract: Various implementations disclosed herein include devices, systems, and methods that provide customized feedback content during a meditation experience. For example, an example process may include obtaining physiological data via one or more sensors, determining that an attentive state based on the physiological data, customizing feedback content based on a user attribute to change the attentive state during the meditation mode, and providing the customized feedback content during the meditation mode after a delay time based on the user attribute.

Abstract: Identifying a state of a user (e.g., attentive, distracted, mind wandering, etc.) based on the user's physiological (e.g., pupillary) response to luminance change events in which a portion or all of the content quickly becomes brighter or dimmer.

Abstract: Some implementations disclosed herein present a computer-generated reality (CGR) environment in which a user participates in an activity, identify a cognitive state of the user (e.g., working, learning, resting, etc.) based on data regarding the user's body (e.g., facial expressions, hand movements, physiological data, etc.), and update the environment with a surrounding environment that promotes a cognitive state of the user for the activity.

Abstract: Some implementations disclosed herein provide systems, methods, and devices that use physiological data (e.g., indicative of surprise) of a user to determine that an unexpected user interface behavior occurred. In some implementations, a device having a processor implements a method. The method obtains, via a sensor, physiological data of a user during a period of time and uses the physiological data to determine a characteristic of the user during the period of time while the user is using the electronic device. The method identifies an unexpected user interface behavior occurring prior to the period of time based on the characteristic of the user during the period of time.

Abstract: Some implementations disclosed herein present a computer-generated reality (CGR) environment in which a user participates in an activity, identify a cognitive state of the user (e.g., working, learning, resting, etc.) based on data regarding the user's body (e.g., facial expressions, hand movements, physiological data, etc.), and update the environment with a surrounding environment that promotes a cognitive state of the user for the activity.

Abstract: Some implementations disclosed herein present multimedia content to a user, identify a comfort state of the user (e.g., happy, unhappy, distressed, etc.) based on body data of the user (e.g., facial expressions, hand movements, physiological data, etc.), and update the multimedia content based on the identified comfort state.

Abstract: Various implementations disclosed herein include devices, systems, and methods that determine an attentive state of a user based on physiological data associated with a physiological response of the user to an auditory stimulus. For example, an example process may include selecting an auditory stimulus based on a characteristic of an environment, presenting the auditory stimulus to a user, obtaining, using a sensor, first physiological data associated with a physiological response of the user to the auditory stimulus, and assessing an attentive state of the user based on the physiological response of the user to the auditory stimulus.

Abstract: Some implementations disclosed herein provide systems, methods, and devices that predict or otherwise determined aspects of a user-to-object contact using physiological data, e.g., from eye tracking or an electromyography (EMG) sensor. Such a determination of user-to-object contact may be used for numerous purposes.

Abstract: Various implementations disclosed herein include devices, systems, and methods that determine an attentive state of a user during an experience (e.g., visual and/or auditory content that could include real-world physical environment, virtual content, or a combination of each) based on the user's gaze characteristic(s) to enhance the experience. For example, an example process may include obtaining physiological data associated with a gaze of a user during an experience, determine a gaze characteristic during a segment of the experience based on the obtained physiological data, and determine that the user has a first attentive state during the segment of the experience based on classifying the gaze characteristic of the user during the segment of the experience.

Abstract: Some implementations disclosed herein identify a state of a user (e.g., attentive, distracted, mind wandering, etc.) based on the user's physiological (e.g., pupillary) response to luminance change events in which a portion or all of the content quickly becomes brighter or dimmer.

Abstract: Identifying a state of a user (e.g., attentive, distracted, mind wandering, etc.) based on the user's physiological (e.g., pupillary) response to luminance change events in which a portion or all of the content quickly becomes brighter or dimmer.

Abstract: One exemplary implementation displays a visual characteristic associated with an object on a display of a device and utilizes a sensor of the device to obtain physiological data associated with a pupillary response of a user to the visual characteristic. The device adjusts the visual characteristic based on the obtained physiological data to enhance pupillary responses of the user to the object and displays the adjusted visual characteristic to the user. For example, the adjusted visual characteristic may be selected based on previously identified pupillary responses of the user to particular visual characteristics.

Abstract: Some implementations disclosed herein present a computer-generated reality (CGR) environment in which a user participates in an activity, identify a cognitive state of the user (e.g., working, learning, resting, etc.) based on data regarding the user's body (e.g., facial expressions, hand movements, physiological data, etc.), and update the environment with a surrounding environment that promotes a cognitive state of the user for the activity.

Abstract: Some implementations disclosed herein identify a state of a user (e.g., attentive, distracted, mind wandering, etc.) based on the user's physiological (e.g., pupillary) response to luminance change events in which a portion or all of the content quickly becomes brighter or dimmer.